[1]
|
Burr Settles.
Active learning literature survey.
Computer Sciences Technical Report 1648, University of
Wisconsin–Madison, 2009.
[ .pdf ]
|
[2]
|
Hussein Mozannar and David Sontag.
Consistent estimators for learning to defer to an expert, 2020.
[ arXiv ]
|
[3]
|
Ozan Sener and Silvio Savarese.
Active learning for convolutional neural networks: A core-set
approach, 2017.
[ arXiv ]
|
[4]
|
Yazhou Yang and Marco Loog.
Active learning using uncertainty information, 2017.
[ arXiv ]
|
[5]
|
Simon Tong and Daphne Koller.
Support vector machine active learning with applications to text
classification.
J. Mach. Learn. Res., 2:45–66, March 2002.
[ DOI |
http ]
|
[6]
|
Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Rachel Bellamy, and Klaus Mueller.
Explainable active learning (xal): An empirical study of how local
explanations impact annotator experience, 2020.
[ arXiv ]
|
[7]
|
Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis, and Xiaojin Zhu.
Teaching a black-box learner.
volume 97 of Proceedings of Machine Learning Research, pages
1547–1555, Long Beach, California, USA, 09–15 Jun 2019. PMLR.
[ .html |
.pdf ]
|
[8]
|
Chenguang Wang, Laura Chiticariu, and Yunyao Li.
Active learning for black-box semantic role labeling with neural
factors.
In Proceedings of the Twenty-Sixth International Joint
Conference on Artificial Intelligence, IJCAI-17, pages 2908–2914, 2017.
[ DOI |
http ]
|
[9]
|
Neil Rubens, Vera Sheinman, Ryota Tomioka, and Masashi Sugiyama.
Active learning in black-box settings.
Austrian Journal of Statistics, 40:125–135, Feb. 2016.
[ http ]
|
[10]
|
Disi Ji, R. Logan, Padhraic Smyth, and M. Steyvers.
Bayesian evaluation of black-box classifiers.
2019.
|
[11]
|
Pengcheng Li, Jinfeng Yi, and Lijun Zhang.
Query-efficient black-box attack by active learning, 2018.
[ arXiv ]
|
[12]
|
David Cortes.
Adapting multi-armed bandits policies to contextual bandits
scenarios, 2018.
[ arXiv ]
|
[13]
|
Djallel Bouneffouf, Romain Laroche, Tanguy Urvoy, Raphaël Feraud, and
Allesiardo Robin.
Contextual bandit for active learning active thompson sampling.
11 2014.
|
[14]
|
Richard S. Sutton and Andrew G. Barto.
Reinforcement Learning: An Introduction.
The MIT Press, second edition, 2018.
[ .html ]
|
[15]
|
Yaqing Wang, Quanming Yao, James Kwok, and Lionel M. Ni.
Generalizing from a few examples: A survey on few-shot learning,
2019.
[ arXiv ]
|
[16]
|
Mark Woodward and Chelsea Finn.
Active one-shot learning, 2017.
[ arXiv ]
|
[17]
|
Janet Vertesi and David Ribes.
DigitalSTS: a field guide for science & technology studies.
2019.
|
[18]
|
Digitized Coral Reefs, March 2019.
[ http ]
|
[19]
|
Frederik Zuiderveen Borgesius.
Discrimination, artificial intelligence, and algorithmic
decision-making.
Study, Council of Europe, Directorate General of Democracy,
Strasbourg, 2018.
[ http ]
|
[20]
|
Louise Amoore.
Doubt and the Algorithm: On the Partial Accounts of Machine
Learning.
Theory, Culture & Society, 36(6):147–169, November 2019.
[ DOI |
http ]
|
[21]
|
Louise Amoore.
Introduction: Thinking with Algorithms: Cognition and
Computation in the Work of N. Katherine Hayles.
Theory, Culture & Society, 36(2):3–16, March 2019.
[ DOI |
http ]
|
[22]
|
Berkeley J Dietvorst, Joseph P Simmons, and Cade Massey.
Algorithm Aversion: People Erroneously Avoid Algorithms
After Seeing Them Err.
Journal of Experimental Psychology, 144(1):114–126, 2015.
[ DOI ]
|
[23]
|
Mike Ananny and Kate Crawford.
Seeing without knowing: Limitations of the transparency ideal and
its application to algorithmic accountability.
New Media & Society, 20(3):973–989, March 2018.
Publisher: SAGE Publications.
[ DOI |
http ]
|
[24]
|
Malte Ziewitz.
Governing Algorithms: Myth, Mess, and Methods.
Science, Technology, & Human Values, 41(1):3–16, January
2016.
https://journals-sagepub-com.uaccess.univie.ac.at/doi/full/10.1177/0162243915608948.
[ DOI |
http ]
|
[25]
|
Sue Newell and Marco Marabelli.
Strategic opportunities (and challenges) of algorithmic
decision-making: A call for action on the long-term societal effects of
‘datification’.
The Journal of Strategic Information Systems, 24(1):3–14,
March 2015.
[ DOI |
http ]
|
[26]
|
Christine Holmberg, Christine Bischof, and Susanne Bauer.
Making Predictions: Computing Populations.
Science, Technology, & Human Values, 38(3):398–420, May 2013.
[ DOI |
http ]
|
[27]
|
Lilian Edwards and Michael Veale.
Slave to the Algorithm? Why a ‘right to an explanation’ is
probably not the remedy you are looking for.
Duke Law and Technology Review, pages 18–84, November 2017.
[ DOI |
http ]
|
[28]
|
Stéphane Couture.
The Ambiguous Boundaries of Computer Source Code and Some
of Its Political Consequences.
In Digital STS, page 21. Routledge, New York, first edition
edition.
|
[29]
|
Steve Sawyer, Ingrid Erickson, and Mohammad Hossein Jarrahi.
Infrastructural Competence.
In Digital STS. A Field Guide for Science &
Technology Studies, page 13. Princeton University Press, Princeton,
first edition edition, 2019.
|
[30]
|
Nerea Calvillo.
Digital Visualizations for Thinking with the Environment.
page 16.
|
[31]
|
Camilla A Hawthorne.
Dangerous Networks Internet Regulations as Racial Border
Control in Italy.
H awthorne, page 20.
|
[32]
|
Daniel Cardoso Llach.
Software Comes to Matter: Toward a Material History of
Computational Design.
Design Issues, 31(3):41–54, July 2015.
[ DOI |
http ]
|
[33]
|
Taina Bucher.
The algorithmic imaginary: exploring the ordinary affects of
Facebook algorithms.
Information, Communication & Society, 20(1):30–44, January
2017.
[ DOI |
http ]
|
[34]
|
Sally A. Applin and Michael D. Fischer.
New technologies and mixed-use convergence: How humans and
algorithms are adapting to each other.
In 2015 IEEE International Symposium on Technology and
Society (ISTAS), pages 1–6, Dublin, Ireland, November 2015. IEEE.
[ DOI |
http ]
|
[35]
|
Kevin Hamilton, Karrie Karahalios, Christian Sandvig, and Motahhare Eslami.
A path to understanding the effects of algorithm awareness.
In Proceedings of the extended abstracts of the 32nd annual
ACM conference on Human factors in computing systems – CHI EA ’14,
pages 631–642, Toronto, Ontario, Canada, 2014. ACM Press.
[ DOI ]
|
[36]
|
Geoffrey C. Bowker and Susan Leigh Star.
Sorting things out: classification and its consequences.
Inside technology. MIT Press, Cambridge, Mass, 2000.
[ http ]
|
[37]
|
Intae Choi.
Digital era governance: IT corporations, the state, and
e-Government.
International Review of Public Administration, 21(4):359–361,
October 2016.
[ DOI |
http ]
|
[38]
|
Julia Black.
Managing Regulatory Risks and Defining the Parameters of
Blame: A Focus on the Australian Prudential Regulation
Authority.
Law html_ent glyph=”@amp;”
ascii=”&”/ Policy, 28(1):1–30, January 2006.
[ DOI |
http ]
|
[39]
|
Thomas Arnold and Matthias Scheutz.
The “big red button” is too late: an alternative model for the
ethical evaluation of AI systems.
Ethics and Information Technology, 20(1):59–69, March 2018.
[ DOI |
http ]
|
[40]
|
Algorithmic Fairness and Opacity Working Group.
[ http ]
|
[41]
|
Dana Wilson-Kovacs.
An Ethnographic Approach to Researching the Introduction of
New Forensic DNA Technologies in Policing in the UK.
SAGE Research Methods Cases in Sociology, page 19, 2018.
[ DOI ]
|
[42]
|
Muhammad Habib ur Rehman, Chee Sun Liew, Assad Abbas, Prem Prakash Jayaraman,
Teh Ying Wah, and Samee U. Khan.
Big Data Reduction Methods: A Survey.
Data Science and Engineering, 1(4):265–284, December 2016.
[ DOI |
http ]
|
[43]
|
Darren Quick and Kim-Kwang Raymond Choo.
Big forensic data reduction: digital forensic images and electronic
evidence.
Cluster Computing, 19(2):723–740, June 2016.
[ DOI |
http ]
|
[44]
|
Virginia Eubanks.
Automating inequality: How high-tech tools profile, police,
and punish the poor.
St. Martin’s Press, New York, first edition edition, 2018.
|
[45]
|
Frank Pasquale.
The black box society: The secret algorithms that control
money and information.
Harvard University Press, Harvard, August 2016.
|
[46]
|
Gina Neff, Anissa Tanweer, Brittany Fiore-Gartland, and Laura Osburn.
Critique and contribute: A practice-based framework for improving
critical data studies and data science.
Big data, 5(2):85–97, 2017.
|
[47]
|
David Lyon.
Surveillance as Social Sorting: Privacy, Risk and
Automated Discrimination.
Taylor and Francis, Florence, 2005.
OCLC: 1027592731.
[ http ]
|
[48]
|
Jingshan Huang, Alec Yasinsac, and Patrick J. Hayes.
Knowledge Sharing and Reuse in Digital Forensics.
In 2010 Fifth IEEE International Workshop on
Systematic Approaches to Digital Forensic Engineering, pages
73–78, Oakland, 2010. IEEE.
[ DOI |
http ]
|
[49]
|
Technologiesouveränität erlangen – die neue Cyberagentur.
Library Catalog: www.bmvg.de.
[ http ]
|
[50]
|
Tim Niesen, Martin Scheid, Peter Fettke, and Wim Wuyts.
Getting Ready for the Future of the Tax Function. Global
Survey on Digital Tax Maturity and AI Readiness.
Study, WTS Global, DFK, Rotterdam.
|
[51]
|
APA.
Künstliche Intelligenz: Österreichische Strategie verzögert
sich.
DER STANDARD, August 2016.
[ http ]
|
[52]
|
Kompetenzzentrum Öffentliche IT.
(Un)ergründlich – Künstliche Intelligenz als
Ordnungsstifterin Öffentliche IT (ÖFIT).
Library Catalog: www.oeffentliche-it.de.
[ http ]
|
[53]
|
Europol.
Do criminals dream of electric sheep? How technology shapes the
future of crime and law enforcement.
Technical report, Europol, Den Haag, 2019.
[ .pdf ]
|
[54]
|
Europol.
Trustworthy AI Requires Solid Cybersecurity, October 2019.
Library Catalog: www.europol.europa.eu.
[ http ]
|
[55]
|
Matthias Monroy.
EU-weite Nutzung von Vorratsdaten bei Banken soll
Finanzermittlungen erleichtern, December 2018.
Library Catalog: netzpolitik.org.
[ http ]
|
[56]
|
Kevin Marschall.
Rechtsverträgliche Gestaltung IT-forensischer Systeme:
Eine Untersuchung am Beispiel der Aufdeckung und Beweisbarkeit von
Versicherungsbetrug.
DuD-Fachbeiträge. Springer Fachmedien, Wiesbaden, 1st ed
edition, 2019.
[ http ]
|
[57]
|
Rosemarie Pexa.
Daten sind nicht neutral., August 2018.
[ http ]
|
[58]
|
Stefan Meier.
Digitale Forensik in Unternehmen.
page 190.
|
[59]
|
Tanja Klenk, Frank Nullmeier, and Göttrik Wewer.
Handbuch Digitalisierung in Staat und Verwaltung.
Springer Fachmedien Wiesbaden : Imprint: Springer VS,, Wiesbaden :,
2019.
|
[60]
|
Florian Krahmer.
Mythos Überwachungsstaat – Über die alltägliche digitale
Polizeiarbeit in Sachsen.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 215–234.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[61]
|
Dirk Kunze.
Basiskompetenzen im Bereich Cybercrime und digitale Spuren.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 161–181.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[62]
|
Thomas-Gabriel Rüdiger and P. Saskia Bayerl.
Digitale Polizeiarbeit: Von Herausforderungen zu Chancen.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 11–15.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[63]
|
Martin H. W. Möllers.
Die Interaktion zwischen Mensch und Computer – Chancen und
Nutzen für Bürgerinnen und Bürger, für Polizeibehörden und das
Polizeiverwaltungsverfahren.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 39–62.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[64]
|
Heike Krischok.
Das Internet in der polizeilichen Gefahrenabwehr.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 237–257.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[65]
|
Aleksandra Sowa and Fred-Mario Silberbach.
Cyber Security Intelligence – Kollaborative Ansätze gegen
Cyber- und Computerkriminalität.
In Thomas-Gabriel Rüdiger and Petra Saskia Bayerl, editors,
Digitale Polizeiarbeit: Herausforderungen und Chancen, pages 109–128.
Springer Fachmedien, Wiesbaden, 2018.
[ DOI |
http ]
|
[66]
|
Kriminalistik Zeitschrift für Wissenschaft und Praxis.
Library Catalog: www.cfmueller.de.
[ .html ]
|
[67]
|
Organisationsbüro der Strafverteidigervereinigungen.
Strafverteidigervereinigungen Organisationsbüro –
Aktuelle Entwicklungen der (Straf)Rechtspolitik.
[ http ]
|
[68]
|
Casten Momsen.
Digitale Beweismittel im Strafprozess.
In Die Akzeptanz des Rechtsstaats in der Justiz, pages
173 — 196, Freiburg, 2013. Organisationsbüro Strafverteidigervereinigung.
[ .html ]
|
[69]
|
André Schulz.
Künstliche Intelligenz – Hilfsmittel oder Konkurrenz für
die Polizei.
Der Kriminalist. Bund deutscher Kriminalbeamter, 3/2017:3,
2017.
[ http ]
|
[70]
|
Heiko Artkämper, Andrea von Buddenbrock, and Horst Clages.
Kriminalitätsbekämpfung – ein Blick in die Zukunft.
Stuttgart : München : Hannover : Berlin : Weimar : Dresden :
Boorberg, 2015.
[ http ]
|
[71]
|
Buzzfeed.
BuzzFeed News Trained A Computer To Search For
Hidden Spy Planes. This Is What We Found.
[ http ]
|
[72]
|
Peter Aldhous.
Here’s How BuzzFeed News Trained A Computer To
Search For Hidden Spy Planes, August 2017.
Library Catalog: www.buzzfeednews.com.
[ http ]
|
[73]
|
Fraunhofer Academy.
Fortbildung Multimedia-Forensik für Ermittlungsverfahren
(Bild, Video, Audio).
Library Catalog: www.cybersicherheit.fraunhofer.de.
[ .html ]
|
[74]
|
Desrues Georgen.
Smart Home: Der Mensch als Schwachstelle des intelligenten
Wohnens, February 2015.
Library Catalog: www.profil.at.
[ http ]
|
[75]
|
Joachim Eschemann.
Transkript zum Hintergrundgespräch “Predictive Policing in
Deutschland”, October 2018.
Library Catalog: www.stiftung-nv.de.
[ http ]
|
[76]
|
Danyal Bayaz.
Finanzmarktaufsicht: Innovation braucht Kontrolle.
Wiwo.de, pages 1–2, November 2018.
[ .html ]
|
[77]
|
Stiftung Münchner Sicherheitskonferenz (gemeinnützige) GmbH.
Munich Security Report 2020.
Library Catalog: securityconference.org.
[ http ]
|
[78]
|
ProPress Verlagsgesellschaft m.b.H.
Europaeischer Polizeikongress.
Library Catalog: www.europaeischer-polizeikongress.de.
[ http ]
|
[79]
|
Marina Walker Guevara.
We Used AI to Identify the Sex of 340,000 People Harmed
by Medical Devices, November 2019.
Library Catalog: www.icij.org.
[ http ]
|
[80]
|
Mara Cabra.
How the ICIJ Used Neo4j to Unravel the Panama Papers, May
2016.
Library Catalog: neo4j.com Section: Blog.
[ http ]
|
[81]
|
Marina Walker Guevara.
How Artificial Intelligence Can Help Us Crack More
Panama Papers Stories, March 2019.
Library Catalog: www.icij.org Section: Blog.
[ http ]
|
[82]
|
Bam Thomas.
ICIJ / datashare, March 2020.
original-date: 2016-04-20T07:52:07Z.
[ http ]
|
[83]
|
ICIJ.
Datashare: Help test and improve our latest journalism tool,
February 2019.
Library Catalog: www.icij.org Section: Blog.
[ http ]
|
[84]
|
What is Datashare? FAQs about our document analysis software, November
2019.
Library Catalog: www.icij.org Section: Blog.
[ http ]
|
[85]
|
Linda Sonyerd.
Victimisation Devices: the case of Arica Vicitims vs Boliden.
Library Catalog: sts.univie.ac.at.
[ http ]
|
[86]
|
Veronique Greenwood.
How Science Is Putting a New Face on Crime Solving,
June 2016.
Library Catalog: www.nationalgeographic.com Section: Magazine.
[ http ]
|
[87]
|
Paul Roberts.
Expert Evidence and Scientific Proof in Criminal
Trials.
Routledge, New York, July 2017.
[ DOI |
http ]
|
[88]
|
Stiftung Neue Verantwortung.
Publikationen Stiftung Neue Verantwortung (SNV).
[ http ]
|
[89]
|
Mary L. Gray and Siddharth Suri.
Ghost Work (International Edition): How to Stop
Silicon Valley from Building a New Global Underclass.
First Edition. Mariner Books, Boston, 2019.
|
[90]
|
Jasanoff Sheila.
Representation and Re-Presentation in Litigation Science.
Environmental Health Perspectives, 116(1):123–129, January
2008.
Publisher: Environmental Health Perspectives.
[ DOI |
http ]
|
[91]
|
Shahmin Sharafat, Zara Nasar, and Syed Waqar Jaffry.
Data mining for smart legal systems.
Computers & Electrical Engineering, 78:328–342, September
2019.
[ DOI |
http ]
|
[92]
|
Ira Torresi.
The Photographic Image: Truth or Sign?
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 125–141. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[93]
|
Joseph Dumit.
Picturing Personhood.
January 2004.
[ http ]
|
[94]
|
Damian Schofield.
Virtual Evidence in the Courtroom.
In Harrison Hao Yang and Steve Chi-Yin Yuen, editors, Handbook
of Research on Practices and Outcomes in Virtual Worlds and
Environments, volume 1, pages 200–216. IGI Global, Hershey, PA, January
2012.
Journal Abbreviation: Handbook of Research on Practices and Outcomes
in Virtual Worlds and Environments.
[ DOI |
http ]
|
[95]
|
Shihchieh Chou and Tai-Ping Hsing.
Text Mining Technique for Chinese Written Judgment of
Criminal Case.
In Hsinchun Chen, Michael Chau, Shu-hsing Li, Shalini Urs, Srinath
Srinivasa, and G. Alan Wang, editors, Intelligence and Security
Informatics, Lecture Notes in Computer Science, pages 113–125,
Berlin, Heidelberg, 2010. Springer.
[ DOI ]
|
[96]
|
Louise Amoore and Rita Raley.
Securing with algorithms: Knowledge, decision, sovereignty.
Security Dialogue, 48(1):3–10, February 2017.
[ DOI |
http ]
|
[97]
|
David M. Berry.
Against infrasomatization : Towards a critical theory of
algorithms.
In Data politics: worlds, subjects, rights, Routledge Studies
in International Political Sociology, pages 43 — 63. Routledge,
London, New York, March 2019.
[ DOI |
http ]
|
[98]
|
Fred Chris Smith and Erin E. Kenneally.
Electronic Evidence and Digital Forensics Testimony in
Court.
In John J. Barbara, editor, Handbook of Digital and
Multimedia Forensic Evidence, pages 103–132. Humana Press, Totowa,
NJ, 2008.
[ DOI |
http ]
|
[99]
|
Glenn Porter.
Visual culture in forensic science.
Australian Journal of Forensic Sciences, 39(2):81–91, December
2007.
Publisher: Taylor & Francis _eprint:
https://doi.org/10.1080/00450610701650054.
[ DOI |
http ]
|
[100]
|
Roland Bal.
How to Kill with a Ballpoint: Credibility in Dutch Forensic
Science.
Science, Technology, & Human Values, 30(1):52–75, January
2005.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[101]
|
Aesthetics of Law and Culture : Texts, Images, Screens.
[ http ]
|
[102]
|
Ken Fowle and Damian Schofield.
Visualising forensic data: investigation to court.
page 11.
|
[103]
|
D. Tait.
Rethinking the role of the image in justice: visual evidence and
science in the trial process.
Law, Probability and Risk, 6(1-4):311–318, October 2007.
[ DOI |
http ]
|
[104]
|
Karen Petroski.
Visual Legal Commentary.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 671–696. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[105]
|
Joseph Pugliese.
The Alleged Liveness of “Live”: Legal Visuality,
Biometric Liveness Testing and the Metaphysics of Presence.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 649–669. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[106]
|
Marco Wan and Janny Leung.
A Tale of Many Newspapers: Perversion, Criminality, and
Scopophilia in the Edison Chen Scandal.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 873–889. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[107]
|
Denis J. Brion.
The Criminal Trial as Theater: The Semiotic Power of the
Image.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 329–359. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[108]
|
Roshan de Silva Wijeyeratne.
The Mandala State in Pre-British Sri Lanka: The
Cosmographical Terrain of Contested Sovereignty in the Theravada
Buddhism Tradition.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 573–598. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[109]
|
Christopher Mark Hutton.
Linguistic Landscape, Law and Reflexive Modernity.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 599–613. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[110]
|
Neal Feigenson.
Visual Common Sense.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 105–124. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[111]
|
Ronnie Lippens.
Law, Code, and Governance in Prophetic Painting: Notes on
the Emergence of Early, High, and Late Modern Forms of Life and
Governance.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 445–467. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[112]
|
David Rolph.
Looking Again at Photographs and Privacy: Theoretical
Perspectives on Law’s Treatment of Photographs as Invasions of
Privacy.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 205–224. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[113]
|
Christian Mosbæk Johannessen.
A Multimodal Social Semiotic Approach to Shape in the
Forensic Analysis of Trademarks.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 283–306. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[114]
|
Paolo Heritier.
Law and Image: Towards a Theory of Nomograms.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 25–48. Springer Netherlands, Dordrecht, 2014.
[ DOI |
http ]
|
[115]
|
Hanneke van Schooten.
Visualization Between Fictitious Law and Factual Behaviour:
A Pragmatic-Institutional Analysis.
In Anne Wagner and Richard K. Sherwin, editors, Law, Culture
and Visual Studies, pages 143–157. Springer Netherlands, Dordrecht,
2014.
[ DOI |
http ]
|
[116]
|
Didier Bigo, Isin Engin, and Evelyn Ruppert.
Digital data and the transnational intelligence space.
In Didier Bigo and Laurent Bonelli, editors, Data politics:
worlds, subjects, rights, Routledge Studies in International Political
Sociology, pages 100 — 122. Routledge, London, New York, March 2019.
[ DOI |
http ]
|
[117]
|
Nick Seaver.
Algorithms as culture: Some tactics for the ethnography of
algorithmic systems.
Big Data & Society, 4(2):1–12, December 2017.
[ DOI |
http ]
|
[118]
|
Aj Macones, As Lev-Toaff, Ga Macones, Jw Jaffe, and Vb Williams.
Legal aspects of obstetric sonography.
American Journal of Roentgenology, 153(6):1251–1254, December
1989.
[ DOI |
http ]
|
[119]
|
Félix Tréguer.
Seeing like Big Tech : Security assemblages, technology, and
the future of state bureaucracy.
In Data Politics. Routledge, New York, March 2019.
[ DOI |
http ]
|
[120]
|
Didier Bigo, Engin Isin, Evelyn Ruppert, Engin Isin, and Evelyn Ruppert.
Data Politics : Worlds, Subjects, Rights.
Routledge, March 2019.
[ DOI |
http ]
|
[121]
|
Daniele Nicola Pica.
The rhythms of interaction with mobile technologies: Tales
from the police.
Ph.D., London School of Economics and Political Science (United
Kingdom), England, 2006.
[ http ]
|
[122]
|
Ezekiel Dixon-Román.
Algo-Ritmo: More-Than-Human Performative Acts and the
Racializing Assemblages of Algorithmic Architectures.
Cultural Studies – Critical Methodologies, 16(5):482–490,
October 2016.
[ DOI |
http ]
|
[123]
|
Mireille Hildebrandt.
Algorithmic regulation and the rule of law.
Philosophical Transactions. Series A, Mathematical, Physical,
and Engineering Sciences, 376(2128), September 2018.
[ DOI ]
|
[124]
|
Aryn Martin, Natasha Myers, and Ana Viseu.
The politics of care in technoscience.
Social Studies of Science, 45(5):625–641, October 2015.
[ DOI |
http ]
|
[125]
|
Diana E. Forsythe.
Studying those who study us: an anthropologist in the world of
artificial intelligence.
Writing science. Stanford UnivPress, Stanford, Calif., 2001.
|
[126]
|
User Devrand.
texty/amber-methodology. How to use machine learning to find
interesting places on satellite maps.
Library Catalog: github.com.
[ http ]
|
[127]
|
Jesus Rodriguez.
Introducing Snorkel, January 2019.
Library Catalog: towardsdatascience.com.
[ http ]
|
[128]
|
Aman Goel.
How to manage noisy data, April 2018.
Library Catalog: magoosh.com Section: Data Analysis.
[ http ]
|
[129]
|
Dynamische Risiko Analyse Systeme (DyRiAS).
Library Catalog: atlas.algorithmwatch.org.
[ http ]
|
[130]
|
Niedersaechsisches Ministerium fuer Inneres und Sport.
Polizei Niedersachsen geht neue Wege: Mit PreMAP gegen
Einbrecher, December 2016.
[ .html ]
|
[131]
|
Algorithm Watch.
KrimPro – Atlas der Automatisierung.
[ http ]
|
[132]
|
Einsatz des Predictive Policing bei der Berliner Polizei.
Library Catalog: kleineanfragen.de.
[ http ]
|
[133]
|
Social network analysis: How to guide.
Social Network Analysis, page 14.
|
[134]
|
Katharina A. Zweig.
1. Fallstudie: Sollte soziale Netzwerkanalyse in der Polizei
zur Analyse von Bandenstrukturen verwendet werden?, November 2016.
Library Catalog: algorithmwatch.org Section: Fallstudie.
[ http ]
|
[135]
|
Wolf J. Schünemann.
Cybersicherheit.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–11.
Springer, Wiesbaden, 2020.
[ DOI |
http ]
|
[136]
|
Sven Becker and Dirk Labudde.
Computergestützte Gesichtsweichteil- und Tatortrekonstruktion.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 59–87. Springer, Berlin,
Heidelberg, 2017.
[ DOI |
http ]
|
[137]
|
Kevin Marschall.
Chancen und Risiken IT-forensischer Systeme.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 141–182. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[138]
|
Dirk Labudde.
Biometrie und die Analyse digitalisierter Spuren.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 25–58. Springer, Berlin,
Heidelberg, 2017.
[ DOI |
http ]
|
[139]
|
Hartmut Luge.
Audioforensik.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 215–238. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[140]
|
Directorate-General for Communications Networks European Commission, Content
and Technology.
Artificial Intelligence for Europe. Communication from the
Commission to the European Council, the Council of Europe, the
European Economic and Social Committee and the Committee of the
Regions.
Technical Report COM(2018) 237, Europäische Kommission, Brüssel,
2018.
|
[141]
|
ARGUMENTUM – Rechnergestützte Analyse von Argumentationsstrukturen.
[ http ]
|
[142]
|
David Freeman Engstrom and Daniel E Ho.
Algorithmic Accountability in the administrative state. CSAS
Working Paper.
Yale Journal on Regulation, 37(Forthcoming):19 — 34, 2020.
|
[143]
|
Kevin Marschall.
(Verfassungs-)Rechtliche Vorgaben, Funktion und Bedeutung.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 119–139. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[144]
|
Mary Elizabeth Luka and Mélanie Millette.
(Re)framing Big Data: Activating Situated Knowledges and
a Feminist Ethics of Care in Social Media Research.
Social Media + Society, 4(2):1–10, April 2018.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[145]
|
Michael Spranger and Dirk Labudde.
Textforensik.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 167–198. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[146]
|
Kevin Marschall.
Technik und Verfahren IT-forensischer Untersuchungen.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 83–118. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[147]
|
Sebastian Haunss and Lena Ulbricht.
Staatliche Regulierung durch Big Data und Algorithmen.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–9. Springer
Fachmedien, Wiesbaden, 2020.
[ DOI |
http ]
|
[148]
|
Bioforscher.de.
MoNa – Mobile Network Analyzer.
[ http ]
|
[149]
|
Hessisches Ministerium für Inneres und Sport.
Hessen Data, 2020.
|
[150]
|
European Commission.
Transaction-Network-Analysis-Tool (TNA), May 2019.
|
[151]
|
Bundesministerium für Finanzen.
Predictive Analytics Competence Center PACC.
|
[152]
|
Bundesministeriums des Innern, für Bau und Heimat.
Zentrale Stelle für Informationstechnik im Sicherheitsbereich
ZITIS, March 2020.
[ .html ]
|
[153]
|
Yaroslava Tymoshchuk.
Leprosy of the Land, 2018.
[ http ]
|
[154]
|
Bundesamt für Sicherheit in der Informationstechnik.
Leitfaden “IT-Forensik”.
Government 1.01, Bundesamt für Sicherheit in der
Informationstechnik, Bonn, March 2011.
[ http ]
|
[155]
|
Kevin Marschall.
Rechtliche Kriterien für IT-forensische Systeme.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 211–399. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[156]
|
Kevin Marschall.
Rechtliche Anforderungen an IT-forensische Systeme.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 183–209. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[157]
|
European Commission.
On Artificial Intelligence. A European approach to excellence
and trust.
White Paper COM(2020) 65, European Commission, Unit A1 Robots and
Artificial Intelligence, Brüssel, 2020.
[ http ]
|
[158]
|
Tina Geweniger, Marika Kaden, and Thomas Villmann.
Methoden des maschinellen Lernens und der Computational
Intelligence zur Auswertung heterogener Daten in der digitalen
Forensik.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 239–263. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[159]
|
Christian Hummert.
Malware Forensics.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 199–214. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[160]
|
Fritz Esterer.
Künstliche Intelligenz im Steuerbereich. Digitalisierung und
Potentiale.
|
[161]
|
Christian Djeffal.
Künstliche Intelligenz.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–12.
Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[162]
|
Kevin Marschall.
Gestaltungsziele IT-forensischer Systeme.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 401–452. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[163]
|
Dirk Labudde and Michael Spranger, editors.
Forensik in der digitalen Welt: Moderne Methoden der
forensischen Fallarbeit in der digitalen und digitalisierten realen
Welt.
Springer, Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[164]
|
Dirk Pawlaszczyk.
Digitaler Tatort, Sicherung und Verfolgung digitaler Spuren.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 113–166. Springer,
Berlin, Heidelberg, March 2017.
[ DOI |
http ]
|
[165]
|
Constantin Houy, Oliver Gutermuth, Sharam Dadashnia, and Peter Loos.
Digitale Polizeiarbeit.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–10.
Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[166]
|
Frank Czerner.
Digitale Forensik zwischen (Online-)Durchsuchung,
Beschlagnahme und Datenschutz.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 265–300. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[167]
|
Bundesministerium für Finanzen.
Die österreichische Steuer- und Zollverwaltung
Geschäftsbericht 2018, 2020.
[ .pdf ]
|
[168]
|
Basanta E. P. Thapa.
Die datengesteuerte Verwaltung.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–10.
Springer Fachmedien, Wiesbaden, 2020.
[ DOI |
http ]
|
[169]
|
Lena Ulbricht.
Data mining für responsive Politikgestaltung.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–10.
Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[170]
|
Julia Moehrmann and Gunther Heidemann.
Efficient annotation of image data sets for computer vision
applications.
In Proceedings of the 1st International Workshop on Visual
Interfaces for Ground Truth Collection in Computer Vision
Applications, VIGTA ’12, pages 1–6, Capri, Italy, May 2012. Association
for Computing Machinery.
[ DOI |
http ]
|
[171]
|
Benji Meltzer.
Spinning up an annotation team, March 2019.
Library Catalog: medium.com.
[ http ]
|
[172]
|
Clemens Mewald.
Data: A key requirement for your Machine Learning (ML)
product, September 2018.
Library Catalog: medium.com.
[ http ]
|
[173]
|
Vikram Singh Bisen.
Why Data Annotation is Important for Machine Learning and
AI?, February 2020.
Library Catalog: medium.com.
[ http ]
|
[174]
|
Matthias Leese.
The new profiling: Algorithms, black boxes, and the failure of
anti-discriminatory safeguards in the European Union.
Security Dialogue, 45(5):494–511, October 2014.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[175]
|
Kevin D. Haggerty and Richard V. Ericson.
The surveillant assemblage.
British Journal of Sociology, 51(4):605–622, 2000.
Place: Oxford, UK Publisher: Blackwell Publishing.
[ DOI ]
|
[176]
|
Sean Erwin.
Living by Algorithm: Smart Surveillance and the Society of
Control.
Humanities and Technology Review, Volume 34(Fall 2015):28–69,
2015.
|
[177]
|
Ned Rossiter.
Organized Networks / The Aesthetics of Algorithmic
Experience.
Library Catalog: nedrossiter.org.
[ http ]
|
[178]
|
Min Kyung Lee, Daniel Kusbit, Evan Metsky, and Laura Dabbish.
Working with Machines: The Impact of Algorithmic and
Data-Driven Management on Human Workers.
In Proceedings of the 33rd Annual ACM Conference on
Human Factors in Computing Systems, CHI ’15, pages 1603–1612,
Seoul, April 2015. Association for Computing Machinery.
[ DOI |
http ]
|
[179]
|
Martin Berg.
Participatory trouble: Towards an understanding of algorithmic
structures on Facebook.
Cyberpsychology: Journal of Psychosocial Research on
Cyberspace, 8(3), October 2014.
Number: 3.
[ DOI |
http ]
|
[180]
|
Christian Sandvig.
Seeing the Sort: The Aesthetic and Industrial Defense of
“The Algorithm”, November 2014.
Library Catalog: median.newmediacaucus.org.
[ http ]
|
[181]
|
Paško Bilić.
Search algorithms, hidden labour and information control.
Big Data & Society, 3(1):1–9, June 2016.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[182]
|
Jakob Arnoldi.
Computer Algorithms, Market: Manipulation and the
Institutionalization of High Frequency Trading.
Theory, Culture & Society, 33(1):29 — 52, February 2015.
[ DOI |
http ]
|
[183]
|
Donald MacKenzie.
How Algorithms Interact: Goffman’s ‘Interaction Order’
in Automated Trading – Donald MacKenzie, 2019.
Theory, Culture & Society, March 2019.
[ http ]
|
[184]
|
Adam Hayes.
Active construction of passive investors: roboadvisors and
algorithmic ‘low-finance’ Socio-Economic Review
Oxford Academic.
Socio-Economic Review, 0(0):1–28, 2019.
[ DOI |
http ]
|
[185]
|
Marc Lenglet Seyfert and Ann-Christina Lange Robert.
On studying algorithms ethnographically: Making sense of objects of
ignorance – Ann-Christina Lange, Marc Lenglet, Robert Seyfert,
2019.
Organization, October 2018.
[ http ]
|
[186]
|
Wendy Espeland Yung, Vincent.
Ethical dimensions of quantification – Wendy Espeland, Vincent
Yung, 2019.
Social Science Information, May 2019.
[ http ]
|
[187]
|
Rafał Dreżewski, Jan Sepielak, and Wojciech Filipkowski.
System supporting money laundering detection.
Digital Investigation, 9(1):8–21, June 2012.
[ DOI |
http ]
|
[188]
|
Susann Wagenknecht, Min Lee, Caitlin Lustig, Jacki O’Neill, and Himanshu Zade.
Algorithms at Work: Empirical Diversity, Analytic
Vocabularies, Design Implications.
In Proceedings of the 19th ACM Conference on Computer
Supported Cooperative Work and Social Computing Companion,
CSCW ’16 Companion, pages 536–543, San Francisco, California, USA,
February 2016. Association for Computing Machinery.
[ DOI |
http ]
|
[189]
|
Nick Bernards and Malcolm Campbell-Verduyn.
Understanding technological change in global finance through
infrastructures.
Review of International Political Economy, 26(5):773–789,
September 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/09692290.2019.1625420.
[ DOI |
http ]
|
[190]
|
Matt Carlson.
The Robotic Reporter.
Digital Journalism, 3(3):416–431, May 2015.
Publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2014.976412.
[ DOI |
http ]
|
[191]
|
Matt Carlson.
News Algorithms, Photojournalism and the Assumption of
Mechanical Objectivity in Journalism.
Digital Journalism, 7(8):1117–1133, September 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2019.1601577.
[ DOI |
http ]
|
[192]
|
Yanfang Wu.
Is Automated Journalistic Writing Less Biased? An
Experimental Test of Auto-Written and Human-Written News
Stories.
Journalism Practice, 0(0):1–21, October 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/17512786.2019.1682940.
[ DOI |
http ]
|
[193]
|
Full article: Is Automated Journalistic Writing Less Biased? An
Experimental Test of Auto-Written and Human-Written News
Stories.
[ http ]
|
[194]
|
T. Franklin Waddell.
Attribution Practices for the Man-Machine Marriage: How
Perceived Human Intervention, Automation Metaphors, and Byline
Location Affect the Perceived Bias and Credibility of Purportedly
Automated Content.
Journalism Practice, 13(10):1255–1272, November 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/17512786.2019.1585197.
[ DOI |
http ]
|
[195]
|
Neil Thurman, Konstantin Dörr, and Jessica Kunert.
When Reporters Get Hands-on with Robo-Writing.
Digital Journalism, 5(10):1240–1259, January 2017.
Publisher: Routledge.
[ DOI |
http ]
|
[196]
|
M. Al Fahdi, N.L. Clarke, F. Li, and S.M. Furnell.
A suspect-oriented intelligent and automated computer forensic
analysis.
Digital Investigation, 18(1):65 — 76, September 2016.
[ DOI |
http ]
|
[197]
|
Caitlin Lustig, Katie Pine, Bonnie Nardi, Lilly Irani, Min Kyung Lee, Dawn
Nafus, and Christian Sandvig.
Algorithmic Authority: the Ethics, Politics, and Economics of
Algorithms that Interpret, Decide, and Manage.
In Proceedings of the 2016 CHI Conference Extended
Abstracts on Human Factors in Computing Systems, CHI EA ’16,
pages 1057–1062, San Jose, California, USA, May 2016. Association for
Computing Machinery.
[ DOI |
http ]
|
[198]
|
Rob Kitchin.
Code/space: software and everyday life.
Software studies. MIT Press, Cambridge, Massachusetts, 2011.
[ http ]
|
[199]
|
Builders of the Vision: Software and the Imagination of Design, 1st
Edition (Paperback) – Routledge.
ISBN: 9780415744997 Library Catalog: www.routledge.com Publisher:
Routledge.
[ http ]
|
[200]
|
Adrian Mackenzie.
Programming subjects in the regime of anticipation: Software
studies and subjectivity.
Subjectivity, 6(4):391–405, December 2013.
[ DOI |
http ]
|
[201]
|
Nick Seaver.
Algorithmic Recommendations and Synaptic Functions.
Limn, 1(2):1, 2012.
[ http ]
|
[202]
|
Devin Kennedy.
The machine in the market: Computers and the infrastructure of
price at the New York Stock Exchange, 1965–1975 – Devin
Kennedy, 2017.
Social Studies of Science, November 2017.
[ http ]
|
[203]
|
Grahame F. Thompson.
Time, trading and algorithms in financial sector security.
New Political Economy, 22(1):1–11, January 2017.
Publisher: Routledge _eprint:
https://doi.org/10.1080/13563467.2016.1183116.
[ DOI |
http ]
|
[204]
|
Mitali Nitish Thakor.
Algorithmic Detectives Against Child Trafficking:
Data, Entrapment, and the New Global Policing Network.
Doctor of Philosophy in History, Anthropology, and Science,
Technology and Society, Massachusetts Institute of Technology, Cambridge,
Massachusetts, August 2016.
[ http ]
|
[205]
|
Christian Borch and Ann-Christina Lange.
High-frequency Trader Subjectivity: Emotional Attachment and
Discipline in an Era of Algorithms.
Socio-Economic Review, 15(2):283–306, 2017.
Publisher: Oxford University Press.
[ DOI |
http ]
|
[206]
|
Mareile Kaufmann, Simon Egbert, and Matthias Leese.
Predictive Policing and the Politics of Patterns.
The British Journal of Criminology, 59(3):674–692, April 2019.
Publisher: Oxford Academic.
[ DOI |
http ]
|
[207]
|
Nicholas A. Christakis.
How AI Will Rewire Us, March 2019.
Library Catalog: www.theatlantic.com Section: Technology.
[ http ]
|
[208]
|
Michele Willson.
Algorithms (and the) everyday.
Information, Communication & Society, 20(1):137–150, 2017.
Publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2016.1200645.
[ DOI |
http ]
|
[209]
|
Btihaj Ajana.
Augmented borders: Big Data and the ethics of immigration
control.
Journal of Information, Communication and Ethics in Society,
13(1):58–78, 2015.
Publisher: Emerald Group Publishing Limited.
[ DOI ]
|
[210]
|
Peter Müller and Nikolaus Pöchhacker.
Algorithmic Risk Assessment als Medium des Rechts.
Österreichische Zeitschrift für Soziologie, 44(1):157–179,
June 2019.
[ DOI |
http ]
|
[211]
|
Elias G. Carayannis, David F. J. Campbell, and Marios Panagiotis
Efthymiopoulos, editors.
Handbook of Cyber-Development, Cyber-Democracy, and
Cyber-Defense.
Springer International Publishing, Basel, 2018.
[ http ]
|
[212]
|
David Bollier.
The Promise and Peril of Big Data.
Technical report, The Aspen Institute, Washington, 2010.
|
[213]
|
Simon Egbert and Susanne Krasmann.
Predictive Policing. Eine ethnographische Studie neuer
Technologien zur Vorhersage von Straftaten und ihre Folgen für die
polizeiliche Praxis. Abschlussbericht.
Abschlussbericht, Universität Hamburg, Hamburg, April 2019.
[ .pdf ]
|
[214]
|
Simon Egbert and Susanne Krasmann.
Die „Pre-Cops“: Wie Algorithmen die
Polizeiarbeit verändern, April 2019.
Library Catalog: geschichtedergegenwart.ch.
[ http ]
|
[215]
|
Ramin Skibba and Ramin Skibba.
Hidden algorithms could already be helping compute your fate, October
2018.
Library Catalog: www.fastcompany.com.
[ http ]
|
[216]
|
Adrian Mackenzie.
The production of prediction: What does machine learning want?
European Journal of Cultural Studies, 18(4-5):429–445, August
2015.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[217]
|
Carrie Dossick, Laura Osburn, and Gina Neff.
Innovation through practice: The messy work of making technology
useful for architecture, engineering and construction teams.
Engineering, Construction and Architectural Management,
ahead-of-print(ahead-of-print), January 2019.
[ DOI |
http ]
|
[218]
|
Susanne Krasmann.
The logic of the surface: on the epistemology of algorithms in times
of big data.
Information, Communication & Society, pages 1–14, February
2020.
Publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2020.1726986.
[ DOI |
http ]
|
[219]
|
Maia Apelt and Norma Möllers.
BMBF-Projekt MuViT-Soz. Soziologische Perspektiven auf
Musterkennung und Video Tracking. Schlussbericht.
BMBF-Projekt MuViT-Soz BMBF 13N10959, Univ. Potsdam, Potsdam,
2013.
Artwork Size: Online-Ressource (67 S., 872 KB) Medium:
application/pdf.
[ DOI |
http ]
|
[220]
|
Kami Chavis.
The Pitfalls of Police Technology: A Minority Report.
In Tamara Rice Lave and Eric J. Miller, editors, The Cambridge
Handbook of Policing in the United States, pages 451–472. Cambridge
University Press, 1 edition, July 2019.
[ DOI |
http ]
|
[221]
|
The Cambridge Handbook of Policing in the United States, July 2019.
ISBN: 9781108354721 9781108420556 9781108430500 Library Catalog:
www-cambridge-org.uaccess.univie.ac.at Publisher: Cambridge University Press.
[ DOI |
www: ]
|
[222]
|
C. Clausner, S. Pletschacher, and A. Antonacopoulos.
Scenario Driven In-depth Performance Evaluation of Document
Layout Analysis Methods.
In 2011 International Conference on Document Analysis
and Recognition, pages 1404–1408, Beijing, China, September 2011. IEEE.
[ DOI |
http ]
|
[223]
|
Xiaojin Zhu and Andrew B. Goldberg.
Introduction to Semi-Supervised Learning.
Synthesis Lectures on Artificial Intelligence and Machine
Learning, 3(1):1–130, January 2009.
Publisher: Morgan & Claypool Publishers.
[ DOI |
http ]
|
[224]
|
Stevie Chancellor, Eric P. S. Baumer, and Munmun De Choudhury.
Who is the “Human” in Human-Centered Machine Learning:
The Case of Predicting Mental Health from Social Media,
November 2019.
[ http ]
|
[225]
|
Anja Bechmann and Geoffrey C Bowker.
Unsupervised by any other name: Hidden layers of knowledge
production in artificial intelligence on social media.
Big Data & Society, 6(1):1–11, January 2019.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[226]
|
Steven Gustafson.
The human-side of artificial intelligence and machine learning, June
2016.
[ http ]
|
[227]
|
Diogo Carvalho, Eduardo Pereira, and Jaime Cardoso.
Machine Learning Interpretability: A Survey on Methods and
Metrics.
Electronics, 8(8):832–864, 2019.
Publisher: Multidisciplinary Digital Publishing Institute.
[ DOI |
http ]
|
[228]
|
Mike Quartararo.
Who’s Afraid Of Machine Learning?
Library Catalog: abovethelaw.com.
[ http ]
|
[229]
|
Paul McFarlane.
Why the police should use machine learning – but very carefully,
August 2019.
Library Catalog: theconversation.com.
[ http ]
|
[230]
|
Annette Vestby and Jonas Vestby.
Machine Learning and the Police: Asking the Right
Questions.
Policing: A Journal of Policy and Practice, September 2019.
[ DOI |
http ]
|
[231]
|
Aleš Završnik.
Algorithmic justice: Algorithms and big data in criminal justice
settings.
European Journal of Criminology, pages 1–20, September 2019.
Publisher: SAGE Publications.
[ DOI |
http ]
|
[232]
|
Aleš Završnik.
Criminal justice, artificial intelligence systems, and human rights.
ERA Forum, 20(4):567–583, March 2020.
[ DOI |
http ]
|
[233]
|
E. Sudheer Kumar and C. Shoba Bindu.
Medical Image Analysis Using Deep Learning: A
Systematic Literature Review.
In Arun K. Somani, Seeram Ramakrishna, Anil Chaudhary, Chothmal
Choudhary, and Basant Agarwal, editors, Emerging Technologies in
Computer Engineering: Microservices in Big Data Analytics,
Communications in Computer and Information Science, pages 81–97,
Singapore, 2019. Springer.
[ DOI ]
|
[234]
|
Alexander Selvikvåg Lundervold and Arvid Lundervold.
An overview of deep learning in medical imaging focusing on MRI.
Zeitschrift für Medizinische Physik, 29(2):102–127, May 2019.
[ DOI |
http ]
|
[235]
|
Gaurav.
Creating High Quality Annotated Training Data for
Radiology AI, September 2019.
Library Catalog: towardsdatascience.com.
[ http ]
|
[236]
|
Martin J. Willemink, Wojciech A. Koszek, Cailin Hardell, Jie Wu, Dominik
Fleischmann, Hugh Harvey, Les R. Folio, Ronald M. Summers, Daniel L. Rubin,
and Matthew P. Lungren.
Preparing Medical Imaging Data for Machine Learning.
Radiology, 295(1):4–15, February 2020.
Publisher: Radiological Society of North America.
[ DOI |
http ]
|
[237]
|
Kristin Asdal, Brita Brenna, and Ingunn Moser, editors.
Technoscience: the politics of interventions.
Unipub, Oslo, 2007.
OCLC: ocn178194648.
|
[238]
|
Kristin Asdal, Brita Brenna, and Ingunn Moser.
The Politics of Interventions. A History of STS.
In Technoscience: The Politics of Intervention, pages 7
— 56. Unipub, Oslo, December 2007.
|
[239]
|
Btihaj Ajana.
Metric Culture: Ontologies of Self-Tracking
Practices.
Emerald Group Publishing, September 2018.
Google-Books-ID: eBxtDwAAQBAJ.
|
[240]
|
Andrew Barry.
Political machines: governing a technological society.
The Athlone Press, London New York, first published. edition, 2001.
|
[241]
|
Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, and
Eric Horvitz.
Updates in Human-AI Teams: Understanding and Addressing the
Performance/Compatibility Tradeoff.
Proceedings of the AAAI Conference on Artificial Intelligence,
33(01):2429–2437, July 2019.
Number: 01.
[ DOI |
http ]
|
[242]
|
Saleema Amershi, Maya Cakmak, William Bradley Knox, and Todd Kulesza.
Power to the People: The Role of Humans in Interactive
Machine Learning.
AI Magazine, 35(4):105–120, December 2014.
Number: 4.
[ DOI |
http ]
|
[243]
|
Peter Flach.
Performance Evaluation in Machine Learning: The Good, the
Bad, the Ugly, and the Way Forward.
In Proceedings of the AAAI Conference on Artificial
Intelligence, volume 33, pages 9808–9814, Honolulu, Hawaii, July 2019.
Association for the Advancement of Artificial Intelligence.
Number: 01.
[ DOI |
http ]
|
[244]
|
Melanie Feinberg.
A Design Perspective on Data.
In Proceedings of the 2017 CHI Conference on Human
Factors in Computing Systems, CHI ’17, pages 2952–2963, Denver,
Colorado, USA, May 2017. Association for Computing Machinery.
[ DOI |
http ]
|
[245]
|
Jin Wu, Wu-Mo Pan, Jian-Ming Jin, and Qing-Ren Wang.
Performance evaluation and benchmarking on document layout analysis
algorithms.
In Proceedings of the 2003 International Conference on
Machine Learning and Cybernetics, volume 4, pages 2246–2250 Vol.4,
Xi’an, China, November 2003. IEEE.
[ DOI ]
|
[246]
|
Galal M. Binmakhashen and Sabri A. Mahmoud.
Document Layout Analysis: A Comprehensive Survey.
ACM Computing Surveys, 52(6):109:1–109:36, October 2019.
[ DOI |
http ]
|
[247]
|
Michael Muller, Ingrid Lange, Dakuo Wang, David Piorkowski, Jason Tsay, Vera
Liao, Casey Dugan, and Thomas Erickson.
How Data Science Workers Work with Data.
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, page 14, Glasgow, 2019. ACM.
[ DOI |
http ]
|
[248]
|
Ákos Kiss and Tamás Szirányi.
Evaluation of manually created ground truth for multi-view people
localization.
In Proceedings of the International Workshop on Video and
Image Ground Truth in Computer Vision Applications, VIGTA ’13,
pages 1–6, St. Petersburg, Russia, June 2013. Association for Computing
Machinery.
[ DOI |
http ]
|
[249]
|
Ming-Tung Hong and Claudia Müller-Birn.
Conceptualization of Computer-Supported Collaborative
Sensemaking.
In Companion of the 2017 ACM Conference on Computer
Supported Cooperative Work and Social Computing, CSCW ’17
Companion, pages 199–202, Portland, Oregon, USA, February 2017.
Association for Computing Machinery.
[ DOI |
http ]
|
[250]
|
David Ribes.
Notes on the Concept of Data Interoperability: Cases from an
Ecology of AIDS Research Infrastructures.
In Proceedings of the 2017 ACM Conference on Computer
Supported Cooperative Work and Social Computing, CSCW ’17, pages
1514–1526, Portland, Oregon, USA, February 2017. Association for Computing
Machinery.
[ DOI |
http ]
|
[251]
|
Samir Passi and Steven J. Jackson.
Data Vision: Learning to See Through Algorithmic
Abstraction.
In Proceedings of the 2017 ACM Conference on Computer
Supported Cooperative Work and Social Computing, pages 2436
–2447, Portland, February 2020. Association for Computing Machinery.
arXiv: 2002.03387 version: 1.
[ DOI |
http ]
|
[252]
|
Jakko Kemper and Daan Kolkman.
Transparent to whom? No algorithmic accountability without a
critical audience.
Information, Communication & Society, 22(14):2081–2096,
December 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2018.1477967.
[ DOI |
http ]
|
[253]
|
Data practice, data science.
Library Catalog: easst.net.
[ http ]
|
[254]
|
Samir Passi and Steven J. Jackson.
Trust in Data Science: Collaboration, Translation, and
Accountability in Corporate Data Science Projects.
Proceedings of the ACM on Human-Computer Interaction,
2(CSCW):136:1–136:28, November 2018.
[ DOI |
http ]
|
[255]
|
Kathleen H. Pine and Max Liboiron.
The Politics of Measurement and Action.
In Proceedings of the 33rd Annual ACM Conference on
Human Factors in Computing Systems, CHI ’15, pages 3147–3156,
Seoul, Republic of Korea, April 2015. Association for Computing Machinery.
[ DOI |
http ]
|
[256]
|
Jeffrey Heer Carreras, Tye Rattenbury, Sean Kandel, and Joseph Hellerstein
Connor.
Principles of Data Wrangling.
[ http ]
|
[257]
|
Anders O. Flaglien.
The Digital Forensics Process.
In Digital Forensics, pages 13–49. John Wiley & Sons, Ltd,
New York, 2017.
Section: 2 _eprint:
https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119262442.ch2.
[ DOI |
http ]
|
[258]
|
A. Antonacopoulos, D. Karatzas, and D. Bridson.
Ground Truth for Layout Analysis Performance Evaluation.
In Horst Bunke and A. Lawrence Spitz, editors, Document
Analysis Systems VII, pages 302–311, Berlin, Heidelberg, 2006.
Springer Berlin Heidelberg.
|
[259]
|
J. Mena.
Machine Learning Forensics for Law Enforcement,
Security, and Intelligence.
Taylor & Francis, 2011.
[ http ]
|
[260]
|
Christen Mader, C. Cas, T. Abou-Chadi, A. Bernstein, N. Braun Binder,
D. Dell’Aglio, L Fábián, D. George, A. Gohdes, L. Hilty, M. Kneer,
J. Krieger-Lamina, H. Licht, A. Scherer, C. Som, P. Sutter, and F. Thouvenin.
Wenn Algorithmen für uns entscheiden: Chancen und Risiken
der künstlichen Intelligenz, volume 72 of TA-Swiss
Publikationsreihe.
TA-Swiss, Zürich, 2020.
|
[261]
|
Florian Jaton.
We get the algorithms of our ground truths: Designing referential
databases in digital image processing.
Social Studies of Science, 47(6):811–840, 2017.
SAGE Publications.
[ DOI |
http ]
|
[262]
|
Daniel Neyland.
Bearing Account-able Witness to the Ethical Algorithmic
System.
Science, Technology, & Human Values, 41(1):50–76, January
2016.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[263]
|
Matthias Monroy.
„Vom Tatort bis zum Gerichtssaal“: EU will mehr
Qualität in der digitalen Kriminaltechnik, 2016.
[ http ]
|
[264]
|
Linzi Wilson-Wilde.
The international development of forensic science standards—a
review.
Forensic science international, 288:1–9, 2018.
Publisher: Elsevier.
[ DOI ]
|
[265]
|
Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos, and Elena L. Glassman.
Proxy Tasks and Subjective Measures Can Be Misleading in
Evaluating Explainable AI Systems.
In IUI ’20, pages 454 — 464, New York, January 2020.
Association for Computing Machinery.
[ DOI |
http ]
|
[266]
|
Sam Levin.
‘Bias deep inside the code’: the problem with AI ‘ethics’ in
Silicon Valley.
The Guardian, page 1, March 2019.
[ http ]
|
[267]
|
Craig S. Smith.
Dealing With Bias in Artificial Intelligence.
The New York Times, November 2019.
[ .html ]
|
[268]
|
Max Schrems.
Kämpf um deine Daten.
edition a, Wien, 2014.
|
[269]
|
Confronting Black Boxes: A Shadow Report of the New York City
Automated Decision System Task Force.
Technical report, AI Now Institute, New York, December 2019.
|
[270]
|
Michael Wiesmüller, Ingo Hegny, Alexander Banfield-Mumb-Mühlhaim, Markus
Triska, Erich Prem, and Bernhard Dachs.
Artificial Intelligence Mission Austria 2030 – Die Zukunft
der Künstlichen Intelligenz in Österreich gestalten.
Technical report, Bundesministerium für Verkehr, Innovatoin,
Technologie; Bundesministerium für Digitalisierung und Wirtschaftsstandort,
Wien, 2019.
[ .pdf ]
|
[271]
|
Kashmir Hill.
Wrongfully Accused by an Algorithm.
The New York Times, June 2020.
[ .html ]
|
[272]
|
Österreichisches Bundeskriminalamt and Österreichisches Bundesministerium
für Inneres.
Österreichisches Bundeskriminalamt: Abteilungem im BK, 2020.
[ http ]
|
[273]
|
Muzayen Al-Youssef.
Predictive Policing: Wie die Polizei Verbrechen voraussagt.
DER STANDARD, page 1, November 2018.
[ http ]
|
[274]
|
Shira Ovide.
When the Police Treat Software Like Magic.
The New York Times, page 0, June 2020.
[ .html ]
|
[275]
|
Fondazione Prada.
Kate Crawford, Trevor Paglen: Training Humans. Fondazione
Prada, 2020.
[ http ]
|
[276]
|
Wolf Zimmer.
Die Legende von der Sharing Economy.
In Wolf Zimmer, editor, Ansturm der Algorithmen: Die
Verwechslung von Urteilskraft mit Berechenbarkeit, Die blaue Stunde
der Informatik, pages 77–82. Springer, Berlin, Heidelberg, 2019.
[ DOI |
http ]
|
[277]
|
Vinícius Fagundes, Raul Fernandes, Carlos Santos, and Tatiana Tavares.
Visualization of Climate Data from User Perspective:
Evaluating User Experience in Graphical User Interfaces and
Immersive Interfaces.
In Sakae Yamamoto, editor, Human Interface and the
Management of Information: Information, Knowledge and Interaction
Design, Lecture Notes in Computer Science, pages 55–70, Cham, 2017.
Springer International Publishing.
[ DOI ]
|
[278]
|
Human Interface and the Management of Information: Information,
Knowledge and Interaction Design :.
Lecture Notes in Computer Science 10273, Vancouver, Canada,
September 2017. Springer International Publishing.
[ DOI |
http ]
|
[279]
|
Eckhard Fuchs.
Bildung im Zeichen der Globalisierung.
Handbuch der Erziehungswissenschaft, pages 857–868, August
2008.
Publisher: Ferdinand Schöningh Section: Handbuch der
Erziehungswissenschaft.
[ DOI |
http ]
|
[280]
|
Sheila Jasanoff.
States of knowledge:: the co-production of science and social
order.
International Library of Sociology. Routledge,, London; New York,
2004.
[ http ]
|
[281]
|
Eike Kühl.
Covid-19: Mit künstlicher Intelligenz gegen das Coronavirus.
Die Zeit, March 2020.
[ http ]
|
[282]
|
Universität Wien.
Library Catalog: www.univie.ac.at.
[ http ]
|
[283]
|
Kari Paul.
Facebook to pay $52m for failing to protect moderators from
‘horrors’ of graphic content.
The Guardian, page 1, May 2020.
Section: Technology.
[ http ]
|
[284]
|
Jörg Niewöhner.
Co-Laborative Anthropology: Crafting Reflexivities
experimentally.
In Jukka Jouhki and Tytti Steel, editors, Ethnologinen tulkinta
ja analyysi. Kohti avoimempaa tutkimusprosessia / Ethnological
interpretation and analysis: Towards a transparent research process, pages
81 — 125. Ethnos, Helsinki, 2016.
[ http ]
|
[285]
|
Chris Anderson.
The End of Theory: The Data Deluge Makes the Scientific
Method Obsolete.
Wired, 15(06), June 2008.
[ http ]
|
[286]
|
European Commission.
General Data Protection Regulation, May 2018.
|
[287]
|
Dave Eggers.
The circle.
A Borzoi book. Knopf ua, New York, NY [u.a.], 1. ed.. edition,
2013.
|
[288]
|
Mikkel Flyverbom and Anders Koed Madsen.
Sorting data out Unpacking big data value chains and algorithmic
knowledge production.
2015.
|
[289]
|
David Martin, Benjamin V. Hanrahan, Jacki O’Neill, and Neha Gupta.
Being a turker.
In Proceedings of the 17th ACM conference on Computer
supported cooperative work & social computing, CSCW ’14, pages 224–235,
Baltimore, Maryland, USA, February 2014. Association for Computing Machinery.
[ DOI |
http ]
|
[290]
|
European Commission.
The European Agenda on Security.
COM COM(2015)185, European Commission, Strasbourg, April 2015.
[ http ]
|
[291]
|
Dean Wilson.
Platform Policing and the Real-Time Cop.
Surveillance & Society, 17(1/2):69–75, 2019.
Place: Kingston Publisher: Surveillance Studies Network.
[ DOI |
http ]
|
[292]
|
P. Jeffrey Brantingham.
The Logic of Data Bias and Its Impact on Place- Based
Predictive Policing.
Ohio State Journal of Criminal Law, 15(2):473–486, 2018.
Accepted: 2018-06-08T19:11:09Z Publisher: Ohio State University.
Moritz College of Law.
[ DOI |
http ]
|
[293]
|
Algorithmic regulation: A critical interrogation – Universität Wien.
[ http ]
|
[294]
|
The scored society: due process for automated predictions. – Universität
Wien.
[ http ]
|
[295]
|
Andrew Norman Wilson.
ScanOps, 2012.
[ .html ]
|
[296]
|
Arjen van Dalen.
The Algorihtms behind the Headlines. How machine-written news
redefines the core skills of human journalists.
Journalism Practice: The Future of Journalism 2011: Developments
and Debates, 6(5-6):648–658, 2012.
Publisher: Taylor & Francis Group.
[ DOI |
http ]
|
[297]
|
THE ALGORITHMS BEHIND THE HEADLINES: How machine-written news
redefines the core skills of human journalists: Journalism Practice:
Vol 6, No 5-6.
[ http ]
|
[298]
|
Joel Ross, Lilly Irani, M. Six Silberman, Andrew Zaldivar, and Bill Tomlinson.
Who are the crowdworkers? Shifting demographics in mechanical turk.
In CHI ’10 Extended Abstracts on Human Factors in
Computing Systems, CHI EA ’10, pages 2863–2872, Atlanta, Georgia,
USA, April 2010. Association for Computing Machinery.
[ DOI |
http ]
|
[299]
|
Who are the crowdworkers? CHI ’10 Extended Abstracts on
Human Factors in Computing Systems.
[ http ]
|
[300]
|
J. Ross, I. Irani, M. Six Silberman, A. Zladivar, and B. Tomlinson.
Ross, J., Irani, I., Silberman, M. Six, Zaldivar, A.,
and Tomlinson, B. (2010). “Who are the Crowdworkers?: Shifting
Demographics in Amazon Mechanical Turk”. In: CHI EA 2010.
(2863-2872).
CHI EA, pages 2863 — 2871, 2010.
|
[301]
|
EUR-Lex – 32016R0679 – EN – EUR-Lex.
Library Catalog: eur-lex.europa.eu.
[ http ]
|
[302]
|
European Commission.
High-Level Expert Group on Artificial Intelligence, 2018.
Library Catalog: ec.europa.eu.
[ http ]
|
[303]
|
Alexandra Chouldechova.
Fair prediction with disparate impact: A study of bias in
recidivism prediction instruments.
Big Data, 5(2):153–163, October 2016.
arXiv: 1610.07524.
[ DOI |
http ]
|
[304]
|
Sabine Gless.
Predictive Policing – In Defense of ‘True Positives’.
In Emre Bayamlıoğlu, Irina Baraliuc, Liisa Janssens, and Mireille
Hildebrandt, editors, Being Profiled: Cogitas Ergo Sum. 10
Years of Profiling the European Citizen., pages 76 — 83. Amsterdam
University Press, Amsterdam, September 2018.
[ http ]
|
[305]
|
Sabine Gless.
AI in the Courtroom: A Comparative Analysis of Machine
Evidence in Criminal Trials.
Georgetown Journal of International Law, 51(2):195 — 253, May
2020.
[ DOI |
http ]
|
[306]
|
Sarah Inman and David Ribes.
” Beautiful Seams” Strategic Revelations and Concealments.
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, pages 1–14, Glasgow, Scotland Uk, 2019.
Association for Computing Machinery.
[ DOI ]
|
[307]
|
Sarah Myers West, Meredith Whittaker, and Kate Crawford.
Discriminating Systems: Gender, Race and Power in
Artificial Intelligence.
Technical report, AI Now Institute, New York, February 2020.
Accepted: 2020-03-05T20:42:23Z Publisher: Georgia Institute of
Technology.
[ http ]
|
[308]
|
Taking European Knowledge Society Seriously Sciences
Citoyennes.
[ http ]
|
[309]
|
Ulrike Felt.
Taking European knowledge society seriously.
Technical Report EUR 22700, European Commission, Brussels, July 2007.
ISBN: 9789279048265 Publisher: Publications Office of the European
Union.
[ http ]
|
[310]
|
Science and governance: taking European knowledge society seriously.
Library Catalog: www.researchgate.net.
[ http ]
|
[311]
|
Ulrike Felt.
“Response-able Practices” or “New Bureaucracies of
Virtue”: The Challenges of Making RRI Work in Academic
Environments.
In Lotte Asveld, Rietje van Dam-Mieras, Tsjalling Swierstra, Saskia
Lavrijssen, Kees Linse, and Jeroen van den Hoven, editors, Responsible
Innovation 3: A European Agenda?, pages 49–68. Springer
International Publishing, Cham, 2017.
[ DOI |
http ]
|
[312]
|
“Response-able Practices” or “New Bureaucracies of Virtue”:
The Challenges of Making RRI Work in Academic Environments.
Library Catalog: www.researchgate.net.
[ http ]
|
[313]
|
Sheila Jasanoff and Sang-Hyun Kim.
Dreamscapes of Modernity.
University of Chicago Press, Chicago, IL, 2015.
[ .html ]
|
[314]
|
Sheila Jasanoff.
Genealogies of STS.
Social Studies of Science, 42(3):435–441, June 2012.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[315]
|
Council of Europe and Committee of experts on internet intermediaries.
Algorithms and human rights – Study on the human rights dimensions
of automated data processing techniques and possible regulatory implications.
Council of Europe Study (2017) 12, Council of Europe, Brussels,
March 2018.
[ .html ]
|
[316]
|
Anna Lauren Hoffmann.
Data Violence and How Bad Engineering Choices Can
Damage Society, April 2018.
Library Catalog: medium.com.
[ http ]
|
[317]
|
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam
Choudhary, Evan P. Hamilton, and Derek Roth.
A comparative study of fairness-enhancing interventions in machine
learning.
In Proceedings of the Conference on Fairness,
Accountability, and Transparency, FAT* ’19, pages 329–338, Atlanta,
GA, USA, January 2019. Association for Computing Machinery.
[ DOI |
http ]
|
[318]
|
Black in AI.
Black in AI, 2020.
Library Catalog: blackinai.github.io.
[ http ]
|
[319]
|
ACM FAccT.
ACM Conference on Fairness, Accountability, and
Transparency (ACM FAccT), May 2020.
[ http ]
|
[320]
|
Österreichischer Rat für Robotik und Künstliche Intelligenz.
Österreichischer Rat für Robotik und Künstliche
Intelligenz, 2020.
Library Catalog: www.acrai.at.
[ http ]
|
[321]
|
Isabella Grabski.
Fairness in Machine Learning, January 2020.
Library Catalog: sitn.hms.harvard.edu.
[ http ]
|
[322]
|
Fabia Schäufele.
Profiling zwischen sozialer Praxis und technischer Prägung:
Ein Vergleich von Flughafensicherheit und Credit-Scoring.
Springer VS Research. Springer VS, Wiesbaden, 2017.
|
[323]
|
CriPA.
Crime Predictive Analytics (CriPA), February 2020.
Library Catalog: www.kiras.at.
[ http ]
|
[324]
|
Algorithm Watch.
Gesichtserkennung. Atlas der Automatisierung., 2020.
Library Catalog: atlas.algorithmwatch.org.
[ http ]
|
[325]
|
Girls Who Code.
Girls Who Code, 2020.
Library Catalog: girlswhocode.com.
[ http ]
|
[326]
|
Paola Tubaro, Antonio A Casilli, and Marion Coville.
The trainer, the verifier, the imitator: Three ways in which human
platform workers support artificial intelligence.
Big Data & Society, 7(1), January 2020.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[327]
|
Lora Aroyo and Chris Welty.
Truth Is a Lie: Crowd Truth and the Seven Myths of
Human Annotation.
AI Magazine, 36(1):15–24, March 2015.
Number: 1.
[ DOI |
http ]
|
[328]
|
Ted Striphas.
Algorithmic culture.
European Journal of Cultural Studies, 18(4-5):395–412, 2015.
Place: London, England Publisher: SAGE Publications.
[ DOI |
http ]
|
[329]
|
Kelley Cotter.
Playing the visibility game: How digital influencers and algorithms
negotiate influence on Instagram.
New Media & Society, 21(4):895–913, 2019.
Place: London, England Publisher: SAGE Publications.
[ DOI ]
|
[330]
|
Excavating AI, February 2020.
Library Catalog: www.excavating.ai.
[ http ]
|
[331]
|
Mary South.
You Will Never Be Forgotten.
The New Yorker, January 2020.
[ http ]
|
[332]
|
Emma Grey Ellis.
Why Social Media Companies Frown on ‘Gaming the
Algorithm’, November 2019.
[ http ]
|
[333]
|
Olivia Solon.
Artist reveals disembodied workers scanning books for Google.
Wired UK, January 2014.
Section: Art.
[ http ]
|
[334]
|
Cindy Greenman.
Exploring the Impact of Artificial Intelligence on the
Accounting Profession.
Journal of Research in Business, Economics and Management,
8(3):1451–1454, March 2017.
[ http ]
|
[335]
|
Stefan Strohmeier and Franca Piazza.
Artificial Intelligence Techniques in Human Resource
Management — A Conceptual Exploration.
In Cengiz Kahraman and Sezi Çevik Onar, editors, Intelligent
Techniques in Engineering Management: Theory and Applications,
Intelligent Systems Reference Library, pages 149–172. Springer
International Publishing, Cham, 2015.
[ DOI |
http ]
|
[336]
|
Technologietrend: Die KI-Revolution im Rechnungswesen.
Library Catalog: www.handelsblatt.com.
[ .html ]
|
[337]
|
Institut für musterbasierte Prognosetechnik.
PRECOBS im Einsatz, 2020.
[ .html ]
|
[338]
|
danah boyd and Kate Crawford.
Critical Questions for Big Data. Provocations for a cultural,
technological, and scholarly phenomenon.
Information, Communication & Society, 15(5):662–679, June
2012.
Publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2012.678878.
[ DOI |
http ]
|
[339]
|
Institut für Arbeitsmarkt- und Berufsforschung.
Könnte ein Roboter meinen Job machen? Jetzt online testen!,
2020.
Library Catalog: job-futuromat.iab.de.
[ http ]
|
[340]
|
Yadong Cui.
Artificial Intelligence and Judicial Modernization.
Springer Nature, September 2019.
Google-Books-ID: 2M2wDwAAQBAJ.
|
[341]
|
arXiv.org e-Print archive.
[ http ]
|
[342]
|
David Alvarez-Melis and Tommi Jaakkola.
A causal framework for explaining the predictions of black-box
sequence-to-sequence models.
arXiv.org, November 2017.
Place: Ithaca Publisher: Cornell University Library, arXivorg.
[ http ]
|
[343]
|
Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, and
Wojciech Samek.
Layer-wise Relevance Propagation for Neural Networks with
Local Renormalization Layers.
In Artificial Neural Networks and Machine Learning –
ICANN 2016, volume 9887 of Lecture Notes in Computer Science,
pages 1–8, Cham, April 2016. Springer.
arXiv: 1604.00825.
[ DOI |
http ]
|
[344]
|
Michael van Lent, William Fisher, and Michael Mancuso.
An explainable artificial intelligence system for small-unit tactical
behavior.
In Proceedings of the 16th conference on Innovative
applications of artifical intelligence, IAAI’04, pages 900–907, San Jose,
California, June 2004. AAAI Press.
|
[345]
|
Fabian Muniesa.
Is a Stock Exchange a Computer Solution?: Explicitness,
Algorithms and the Arizona Stock Exchange.
International Journal of Actor Network Theory and Technological
Innovation, 3(1):1 — 15, 2011.
[ DOI ]
|
[346]
|
K. Krasnow Waterman and Jim Hendler.
Getting the Dirt on Big Data.
Big Data, 1(3):137–140, September 2013.
[ DOI |
http ]
|
[347]
|
M. Hildebrandt and L. Janssens.
The New Imbroglio. Living with machine algorithms, 2016.
Pages: 55–60.
[ http ]
|
[348]
|
Hannah Kuchler.
Max Schrems: the man who took on Facebook — and won, April
2018.
Library Catalog: www.ft.com.
[ http ]
|
[349]
|
The New Imbroglio. Living with machine algorithms › Research
Explorer.
[ .html ]
|
[350]
|
Jackie Snow.
Algorithms are making American inequality worse.
MIT Technology Review, page 1, January 2018.
[ http ]
|
[351]
|
Are Emily and Greg More Employable than Lakisha and Jamal? A
Field Experiment on Labor Market Discrimination on JSTOR.
[ http ]
|
[352]
|
Ian Bogost.
The Cathedral of Computation.
The Atlantic, page 1, January 2015.
[ http ]
|
[353]
|
Bundespolizeipräsidium Potsdam.
Abschlussbericht des Bundespolizeipräsidiums zum Teilprojekt 1
“Biometrische Gesichtserkennung” am Bahnhof Berlin Südkreuz.
Teilprojekt 1, Bundespolizeipräsidium Potsdam, Potsdam, September
2018.
[ http ]
|
[354]
|
Projekt zur Gesichtserkennung erfolgreich.
Library Catalog: www.bmi.bund.de.
[ http ]
|
[355]
|
Bundesanstalt für Finanzdienstleistungsaufsicht.
Big Data trifft auf künstliche Intelligenz. Herausforderungen
und Implikationen für Aufsicht und Regulierung von
Finanzdienstleistungen.
Technical report, Bundesanstalt für Finanzdienstleistungsaufsicht,
Bonn, June 2018.
[ .html ]
|
[356]
|
Åsa Mäkitalo and Roger Säljö.
Invisible People: Institutional Reasoning and Reflexivity in
the Production of Services and”Social Facts” in Public Employment
Agencies.
Mind, Culture, and Activity, 9(3):160–178, August 2002.
Publisher: Routledge _eprint:
https://doi.org/10.1207/S15327884MCA0903_02.
[ DOI |
http ]
|
[357]
|
Roland Atzmüller and Christoph Hermann.
Veränderung öffentlicher Beschäftigung im Prozess der
Liberalisierung und Privatisierung. Rekommodifizierung von Arbeit und
Herausbildung eines neoliberalen Arbeitsregimes.
Österreichische Zeitschrift für Soziologie, 29(4):30–48,
December 2004.
Place: Wiesbaden Publisher: VS Verlag für Sozialwissenschaften.
[ DOI ]
|
[358]
|
Rob Kitchin.
The data revolution: big data, open data, data infrastructures
& their consequences.
Sage, Los Angeles, Calif. [u.a.], 1. publ.. edition, June 2014.
|
[359]
|
David Beer.
Metric power.
Palgrave Macmillan, London, 2016.
[ http ]
|
[360]
|
Daniel Victor.
Microsoft Created a Twitter Bot to Learn From Users. It
Quickly Became a Racist Jerk.
The New York Times, March 2016.
[ .html ]
|
[361]
|
Siva Vaidhyanathan.
The Politics Machine.
In Anti-social Media. How Facebook disconnects us and
undermines democracy, page 276. Oxford University Press, New York, 2018.
|
[362]
|
Konrad Lischka and Anita Klingel.
Wenn Maschinen Menschen bewerten.
Technical Report 1, Bertelsmann-Stiftung, Gütersloh, 2017.
[ http ]
|
[363]
|
Jason Radford and Kenneth Joseph.
Theory In, Theory Out: The Uses of Social Theory in
Machine Learning for Social Science.
Frontiers in Big Data, 3, 2020.
Publisher: Frontiers.
[ DOI |
http ]
|
[364]
|
Doris Allhutter, Florian Cech, Fabian Fischer, Gabriel Grill, and Astrid Mager.
Algorithmic Profiling of Job Seekers in Austria: How
Austerity Politics Are Made Effective.
Frontiers in Big Data, 3, 2020.
Publisher: Frontiers.
[ DOI |
http ]
|
[365]
|
Carl Benedikt Frey and Michael A. Osborne.
The future of employment: How susceptible are jobs to
computerisation?
Technological Forecasting and Social Change, 114:254–280,
January 2017.
[ DOI |
http ]
|
[366]
|
The Future of Employment: How susceptible are jobs to computerisation?
Library Catalog: www.oxfordmartin.ox.ac.uk.
[ http ]
|
[367]
|
Melanie Arntz, Terry Gregory, and Ulrich Zierahn.
The Risk of Automation for Jobs in OECD Countries: A
Comparative Analysis.
Organisation for Economic Co-operation and Developmen,
01(189):1 — 34, May 2016.
Publisher: OECD.
[ DOI |
http ]
|
[368]
|
Richard Baldwin.
White-Collar Robots Are Coming for Jobs.
Wall Street Journal, January 2019.
[ http ]
|
[369]
|
Könnte ein Roboter meinen Job machen? Jetzt online testen!
Library Catalog: job-futuromat.iab.de.
[ http ]
|
[370]
|
Eduardo Porter.
Don’t Fight the Robots. Tax Them.
The New York Times, February 2019.
[ .html ]
|
[371]
|
Elizabeth E. Joh.
The Consequences of Automating and Deskilling the Police.
UCLA Law Review, 134(1):135 — 164, September 2019.
[ http ]
|
[372]
|
Cinthya Grajeda, Frank Breitinger, and Ibrahim Baggili.
Availability of datasets for digital forensics – And what is
missing.
Digital Investigation, 22:94–105, August 2017.
[ DOI |
http ]
|
[373]
|
Kristian Lum and William Isaac.
To predict and serve?
Significance, 13(5):14–19, 2016.
_eprint:
https://rss.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1740-9713.2016.00960.x.
[ DOI |
http ]
|
[374]
|
Bilel Benbouzid.
To predict and to manage. Predictive policing in the United
States.
Big Data & Society, 6(1):1–13, January 2019.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[375]
|
Won Kim, Byoung-Ju Choi, Eui-Kyeong Hong, Soo-Kyung Kim, and Doheon Lee.
A Taxonomy of Dirty Data.
Data Mining and Knowledge Discovery, 7(1):81–99, January 2003.
[ DOI |
http ]
|
[376]
|
Rashida Richardson, Jason Schultz, and Kate Crawford.
Dirty Data, Bad Predictions: How Civil Rights
Violations Impact Police Data, Predictive Policing Systems, and
Justice.
SSRN Scholarly Paper ID 3333423, Social Science Research
Network, Rochester, NY, March 2019.
[ http ]
|
[377]
|
David Watson.
Digital Forensics Processing and Procedures: Meeting the
Requirements of ISO 17020, ISO 17025, ISO 27001 and Best Practice
Requirements.
Syngress, Amsterdam, 2013.
[ http ]
|
[378]
|
Doug Laney.
3D Data Management: Controlling Data Volume, Velocity
and Variety. Stanford, application delivery strategies.
Meta Group, (File 949), February 2001.
|
[379]
|
3D Data Management: Controlling Data Volume, Velocity, and
Variety BibSonomy.
[ http ]
|
[380]
|
Richard Herschel and Virginia M. Miori.
Ethics & Big Data.
Technology in Society, 49:31–36, May 2017.
[ DOI |
http ]
|
[381]
|
Laura Mahrenbach and Katja Mayer.
Framing Policy Visions of Big Data in Emerging States.
Canadian Journal of Communication, 45(1), February 2020.
[ DOI |
http ]
|
[382]
|
European Commission.
Amended proposal for a Council Directive on the protection of
individuals with regard to the processing of personal data and on the free
movement of such data.
COM COM (92) 422, European Commission, Brussels, 1992.
[ http ]
|
[383]
|
Solon Barocas, Sophie Hood, and Malte Ziewitz.
Governing Algorithms: A Provocation Piece.
Rochester, NY, March 2013. Social Science Research Network.
[ DOI |
http ]
|
[384]
|
Massimo Pigliucci.
The end of theory in science?
EMBO Reports, 10(6):534, June 2009.
[ DOI |
http ]
|
[385]
|
Algorithm Watch.
AI Ethics Guidelines Global Inventory, April 2020.
Library Catalog: inventory.algorithmwatch.org.
[ http ]
|
[386]
|
Joint Research Centre.
Artificial Intelligence – A European Perspective.
Technical Report EUR 29425 EN, European Commission, Ispra, Italy,
2018.
doi:10.2760/11251 ISBN 978-92-79-97217-1 ISSN 1831-9424.
|
[387]
|
Gloria Bozyigit.
Regulating the digital single market: the emergence of digital
identities and the EU’s adaptation & implementation of relevant
policies.
Wien, 2019.
|
[388]
|
Bruno Latour.
Why Has Critique Run out of Steam? From Matters of Fact
to Matters of Concern.
Critical Inquiry, 30(2):225–248, January 2004.
Publisher: The University of Chicago Press.
[ DOI |
http ]
|
[389]
|
Why Has Critique Run Out of Steam? From Matters of Fact to
Matters of Concern.
Library Catalog: www.researchgate.net.
[ http ]
|
[390]
|
Sarah Brayne.
Big Data Surveillance: The Case of Policing.
American Sociological Review, 82(5):977–1008, August 2017.
[ DOI |
http ]
|
[391]
|
Full article: Attribution Practices for the Man-Machine Marriage:
How Perceived Human Intervention, Automation Metaphors, and
Byline Location Affect the Perceived Bias and Credibility of
Purportedly Automated Content.
[ http ]
|
[392]
|
Norman P. Lewis and Stephenson Waters.
Data Journalism and the Challenge of Shoe-Leather
Epistemologies.
Digital Journalism, 6(6):719–736, June 2018.
Publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2017.1377093.
[ DOI |
http ]
|
[393]
|
Mark J. Carlotto.
Effect of errors in ground truth on classification accuracy.
International Journal of Remote Sensing, 30(18):4831–4849,
August 2009.
Publisher: Taylor & Francis _eprint:
https://doi.org/10.1080/01431160802672864.
[ DOI |
http ]
|
[394]
|
Patrick Vos de Haan and Andreas Kämpfer.
Künstliche Intelligenz und ihre Bedeutung für die Polizei.
Zusammenfassung des Vortrags, Bundeskriminalamt, Wiesbaden, June
2019.
[ .html ]
|
[395]
|
Tal Zarsky.
The Trouble with Algorithmic Decisions: An Analytic Road
Map to Examine Efficiency and Fairness in Automated and Opaque
Decision Making.
Science, Technology, & Human Values, 41(1):118–132, January
2016.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[396]
|
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, and
Hanna Wallach.
Improving fairness in machine learning systems: What do industry
practitioners need?
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, pages 1–16, Glasgow, Scotland Uk, 2019.
Association for Computing Machinery.
arXiv: 1812.05239.
[ DOI |
http ]
|
[397]
|
Jessica Fjeld, Nele Achten, Hannah Hilligoss, Adam Nagy, and Madhulika
Srikumar.
Principled Artificial Intelligence: Mapping Consensus in
Ethical and Rights-Based Approaches to Principles for AI.
SSRN Scholarly Paper ID 3518482, Social Science Research
Network, Rochester, NY, January 2020.
[ DOI |
http ]
|
[398]
|
Working with Machines: The Impact of Algorithmic and Data-Driven
Management on Human Workers.
Library Catalog: www.researchgate.net.
[ http ]
|
[399]
|
Daniel Beunza and Yuval Millo.
Blended automation: integrating algorithms on the floor of the New
York Stock Exchange.
Discussion Paper 38, London School of Economics and Political
Science, 2015.
[ http ]
|
[400]
|
Jenna Burrell.
How the Machine ‘Thinks:’ Understanding Opacity in Machine
Learning Algorithms, 2015.
[ http ]
|
[401]
|
Principled Artificial Intelligence Berkman Klein Center,
February 2020.
Library Catalog: cyber.harvard.edu.
[ http ]
|
[402]
|
Viola Schmid and Hanno Bauer.
Zur „Beweiskraft informationstechnologischer Expertise”.
In Helmut Redekker and Peter Hoppen, editors, DGRI Jahrbuch
2011, pages 259 — 266. Verlag Dr. Otto Schmidt, Köln, 2012.
[ http ]
|
[403]
|
Landeskriminalamt Rheinland Pfalz and und Polizeirecht der Universität Trier
(ISP).
Wirtschaftskriminalität im digitalen Zeitalter. 5. Trierer
Forum zum Recht der Inneren Sicherheit (TRIFORIS), 2019.
[ .pdf ]
|
[404]
|
Kate Crawford, Dobbe Roel, Theodora Dryer, Joy Lisi Rankin, Rashida Richardson,
Genevieve Fried, Ben Green, Elisabeth Kaziunas, Amba Kak, Varoon Mathur, Erin
McElroy, Andrea Nil Sanchez, Jason Schultz, Sarah Myers West, and Meredith
Whittaker.
AI Now 2019 Report.
Technical report, AI Now Institute, New York, 2019.
[ http ]
|
[405]
|
Adrian Mackenzie.
Machine learners: archaeology of a data practice.
The MIT Press, Cambridge, Massachusetts London, England, 2017.
|
[406]
|
Charles Camic.
The Handbook of Science and Technology Studies.
Contemporary Sociology: A Journal of Reviews, 38(3):272–273,
2009.
Place: Los Angeles, CA Publisher: SAGE Publications.
[ DOI ]
|
[407]
|
Canberra Law’s Experts Conference.
Expertise in regulation and law.
Ashgate, Aldershot, 2004.
|
[408]
|
Gary Edmond and David Mercer.
Experts and Expertise in Legal and Regulatory Settings.
In Gary Edmond, editor, Expertise in regulation and law, pages
1 — 32. Ashgate, Aldershot, 2004.
|
[409]
|
Paul Edwards.
A vast machine: computer models, climate data, and the politics
of global warming.
MIT Press, Cambridge, Massachusetts, February 2013.
[ http ]
|
[410]
|
Teun Zuiderent-Jerak.
Situated intervention: : sociological experiments in health
care.
Inside technology. The MIT Press,, Cambridge, Massachusetts :, 2015.
|
[411]
|
Jörg Niewöhner.
Epigenetics: localizing biology through co-laboration.
New Genetics and Society: EPIGENETICS AND SOCIETY: POTENTIAL,
EXPECTATIONS, AND CRITICISMS, 34(2):219–242, 2015.
Publisher: Routledge.
[ DOI |
http ]
|
[412]
|
Barbara Prainsack.
Unchaining research: Processes of dis/empowerment and the social
study of criminal law and investigation.
In Knowledge, Technology and Law, Law, Science and
Society, pages 71–85. Routledge, London; New York, September 2014.
Publisher: Taylor and Francis Inc.
[ .html ]
|
[413]
|
G. Rees.
Making the colposcope “forensic”: The medico-legal management of a
controversial visualisation device.
In Knowledge, Technology and Law: At the Intersection of
Socio-Legal and Science & Technology Studies, Law, Science and
Society, pages 86 — 103. Routledge, London ; New York :, 2015.
Publisher: Newcastle University.
[ http ]
|
[414]
|
Emilie Cloatre and Martin Pickersgill.
Knowledge, Technology and Law. Introduction.
In Knowledge, Technology and Law, Law, Science and
Society, pages 1–15. Routledge, London; New York, 2015.
|
[415]
|
Doris Ipsmiller.
Projektbeschreibung für Förderansuchen. K.Rex: Knowledge
Recognition for Evidence EXtraction, January 2018.
|
[416]
|
Doris Ipsmiller.
Kurzzusammenfassung K.Rex, November 2019.
|
[417]
|
Bruno Latour.
Science in action: how to follow scientists and engineers
through society.
Open UnivPress, Milton Keynes, 1. publ.. edition, 1987.
|
[418]
|
Thomas Parke Hughes.
Networks of power: electrification in Western society,
1880-1930.
Johns Hopkins UnivPress, Baltimore, Md. [u.a.], softshell books ed..
edition, 1993.
|
[419]
|
Christine Borgman, Peter Darch, Irene Pasquetto, and Morgan Wofford.
Our knowledge of knowledge infrastructures: Lessons learned and
future directions.
Report of Knowledge Infrastructures Workshop, 27 27, UCLA:
Center for Knowledge Infrastructures, Los Angeles, 2020.
|
[420]
|
Maximilian Fochler, Ulrike Felt, and Ruth Müller.
Unsustainable Growth, Hyper-Competition, and Worth in Life
Science Research: Narrowing Evaluative Repertoires in Doctoral
and Postdoctoral Scientists’ Work and Lives.
Minerva, 54(2):175–200, June 2016.
[ DOI |
http ]
|
[421]
|
Brian Larkin.
The Politics and Poetics of Infrastructure.
Annual Review of Anthropology, 42(1):327–343, 2013.
_eprint: https://doi.org/10.1146/annurev-anthro-092412-155522.
[ DOI |
http ]
|
[422]
|
Susan Leigh Star and Karen Ruhleder.
Steps Toward an Ecology of Infrastructure: Design and
Access for Large Information Spaces.
Information Systems Research, 7(1):111–134, 1996.
[ DOI ]
|
[423]
|
Stephen C. Slota and Geoffrey C Bowker.
How Infrastructures Matter.
In The Handbook of Science and Technology Studies,
pages 529 — 554. MIT Press, Cambridge, Massachusetts :, 4th edition, 2017.
|
[424]
|
Frederik J. Zuiderveen Borgesius.
Strengthening legal protection against discrimination by algorithms
and artificial intelligence.
The International Journal of Human Rights, 0(0):1–22, March
2020.
Publisher: Routledge _eprint:
https://doi.org/10.1080/13642987.2020.1743976.
[ DOI |
http ]
|
[425]
|
David Ribes.
STS, Meet Data Science, Once Again.
Science, Technology, & Human Values, 44(3):514–539, May 2019.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[426]
|
Keith Hawkins.
Themes, Perspectives, Questions.
Oxford University Press.
Publication Title: Law as Last Resort Section: Law as Last Resort.
[ http ]
|
[427]
|
Große Strafrechtskommission des deutschen Richterbundes.
Das Verhältnis von Gericht, Staatsanwaltschaft und Polizei
im Ermittlungsverfahren, strafprozessuale Regeln und faktische
(Fehl-?)Entwicklungen, 2008.
|
[428]
|
Linde Verlag www.lindeverlag.at.
Strafverfolgung auf dem Prüfstand Linde
Verlag.
[ http ]
|
[429]
|
Sheila Jasanoff.
Ordering Life: Law and the Normalization of Biotechnology.
Politeia, 17(62):34–50, 2011.
|
[430]
|
Sheila Jasanoff.
Law, Science, and Technology, 2015.
Library Catalog: sheilajasanoff.org.
[ http ]
|
[431]
|
Annelise Riles.
Anthropology, Human Rights, and Legal Knowledge: Culture in
the Iron Cage.
American Anthropologist, 108(1):52–65, 2006.
Publisher: [American Anthropological Association, Wiley].
[ http ]
|
[432]
|
Keith Hawkins.
Law as last resort: : prosecution decision-making in a
regulatory agency.
Oxford socio-legal studies. Oxford University Press,, Oxford :, 2002.
|
[433]
|
Simon A. Cole and Alyse Bertenthal.
Science, Technology, Society, and Law.
Annual Review of Law and Social Science, 13(1):351–371, 2017.
_eprint: https://doi.org/10.1146/annurev-lawsocsci-110316-113550.
[ DOI |
http ]
|
[434]
|
Henning (Ed.) Laux.
Bruno Latours Soziologie der »Existenzweisen«:
Einführung und Diskussion.
transcript, September 2016.
Publication Title: Bruno Latours Soziologie der »Existenzweisen«.
[ http ]
|
[435]
|
Bruno Latour.
An inquiry into modes of existence: an anthropology of the
moderns.
[ http ]
|
[436]
|
An inquiry into modes of existence : an anthropology of the moderns –
Universität Wien.
[ http ]
|
[437]
|
Lukas Klingholz.
Entscheidungsunterstützung mit Künstlicher Intelligenz.
Wirtschaftliche Bedeutung, gesellschaftliche Herausforderungen,
menschliche Verantwortung.
Technical report, Bundesverband Informationswirtschaft,
Telekommunikation und neue Medien e. V., Berlin, 2017.
[ .pdf ]
|
[438]
|
Da-Yu Kao, Ni-Chen Wu, and Fuching Tsai.
The Governance of Digital Forensic Investigation in Law
Enforcement Agencies.
In 2019 21st International Conference on Advanced
Communication Technology (ICACT), pages 61–65, February 2019.
ISSN: 1738-9445.
[ DOI ]
|
[439]
|
Rami M. Mohammad.
A Neural Network based Digital Forensics Classification.
In Proceedings of the 2018 IEEE/ACS 15th International
Conference on Computer Systems and Applications (AICCSA), pages
1–7, Aqaba, Jordan, October 2018. IEEE.
ISSN: 2161-5330.
[ DOI |
http ]
|
[440]
|
Lukas Staffler and Oliver Jany.
Künstliche Intelligenz und Strafrechtspflege – eine
Orientierung.
Zeitschrift für Internationale Strafrechtsdogmatik,
15(4):164–177, 2020.
Publisher: Editors of ZIS.
[ .pdf ]
|
[441]
|
FPFIS team.
AI Watch – Artificial Intelligence in public services, July
2020.
Library Catalog: ec.europa.eu.
[ http ]
|
[442]
|
Fieke Jansen.
Data Driven Policing in the Context ofEurope.
Technical report, Data Justice Lab, 2018.
|
[443]
|
Stefania Milan and Lonneke Van der Velden.
The alternative epistemologies of data activism.
Digital Culture & Society, 2(2):57–74, January 2015.
Publisher: transcript.
[ DOI ]
|
[444]
|
The Stanford Open Policing Project.
Library Catalog: openpolicing.stanford.edu.
[ http ]
|
[445]
|
White Collar Crime Risk Zones.
Library Catalog: whitecollar.thenewinquiry.com.
[ http ]
|
[446]
|
Pratyusha Kalluri.
Don’t ask if artificial intelligence is good or fair, ask how it
shifts power.
Nature, 583(7815):169–169, July 2020.
Number: 7815 Publisher: Nature Publishing Group.
[ DOI |
http ]
|
[447]
|
Chelsea Barabas, Colin Doyle, JB Rubinovitz, and Karthik Dinakar.
Studying up: reorienting the study of algorithmic fairness around
issues of power.
In Proceedings of the 2020 Conference on Fairness,
Accountability, and Transparency, FAT* ’20, pages 167–176, Barcelona,
Spain, January 2020. Association for Computing Machinery.
[ DOI |
http ]
|
[448]
|
Timothy Bollé, Eoghan Casey, and Maëlig Jacquet.
The role of evaluations in reaching decisions using automated systems
supporting forensic analysis.
Forensic Science International: Digital Investigation,
34(301016):1–13, July 2020.
[ DOI |
http ]
|
[449]
|
Joshua I James and Pavel Gladyshev.
Challenges with Automation in Digital Forensic
Investigations.
Technical report, March 2013.
[ http ]
|
[450]
|
Elwin van ‘t Wout, Christian Pieringer, David Torres Irribarra, Kenzo Asahi,
and Pilar Larroulet.
Machine learning for policing: a case study on arrests in Chile.
Policing and Society, pages 1–15, June 2020.
[ DOI |
http ]
|
[451]
|
Nickson M. Karie, Victor R. Kebande, and H.S. Venter.
Diverging deep learning cognitive computing techniques into cyber
forensics.
Forensic Science International: Synergy, 1:61–67, 2019.
[ DOI |
http ]
|
[452]
|
Davide Ariu, Giorgio Giacinto, and Fabio Roli.
Machine learning in computer forensics (and the lessons learned from
machine learning in computer security).
In Proceedings of the 4th ACM workshop on Security and
artificial intelligence, pages 99–104, Chicago, Illinois, USA, 2011. ACM
Press.
[ DOI |
http ]
|
[453]
|
Brian Rappert, Hannah Wheat, and Dana Wilson-Kovacs.
Rationing bytes: managing demand for digital forensic examinations.
Policing and Society, pages 1–14, July 2020.
[ DOI |
http ]
|
[454]
|
Sheila Jasanoff and Sang-Hyun Kim.
Containing the atom: Sociotechnical imaginaries and nuclear power
in the United States and South Korea.
Minerva, 47(2):119, 2009.
Publisher: Springer.
|
[455]
|
Uwe Ewald.
Künstliche Intelligenz – Digitale Mustererkennung als
Ermittlungsansatz, 2020.
[ http ]
|
[456]
|
Jasmin Cosic and Miroslav Baca.
Do we have full control over integrity in digital evidence life
cycle?
In Proceedings of the ITI 2010, 32nd International
Conference on Information Technology Interfaces, pages 429–434,
Cavtat, Croatia, June 2010. IEEE.
|
[457]
|
Matthias Purkhart.
Rechtliche und praktische Probleme im Zusammenhang mit der
Sicherstellung, Auswertung und Verwendung von Daten im
Strafverfahren.
WU Wien, 2017.
|
[458]
|
Ulrike Felt.
Leben in Nanowelten: Zur Ko-Produktion von Nano und
Gesellschaft.
In Technologisierung gesellschaftlicher Zukünfte, pages
19–37. Springer, 2010.
|
[459]
|
Günter Ropohl.
Ethik und Technikbewertung.
Suhrkamp, 1996.
|
[460]
|
Ohio State Journal of Criminal Law.
Round Table on Big Data and Criminal Law.
In Ohio State Journal of Criminal Law: Volume 15:2.
2018.
[ http ]
|
[461]
|
Ric Simmons.
Big Data and Procedural Justice: Legitimizing Algorithms in
the Criminal Justice System.
SSRN Electronic Journal, 2020.
[ DOI |
http ]
|
[462]
|
Barbara B Kawulich.
Participant observation as a data collection method.
In Forum qualitative sozialforschung/forum: Qualitative social
research, volume 6, 2005.
Issue: 2.
|
[463]
|
Siegfried Lamnek.
Qualitative sozialforschung: lehrbuch.
Beltz, 2005.
|
[464]
|
Robert K Merton.
Focused interview.
Simon and Schuster, 2008.
|
[465]
|
Ulrike Felt and Susanne Öchsner.
Reordering the “World of Things”: The Sociotechnical
Imaginary of RFID Tagging and New Geographies of Responsibility.
Science and engineering ethics, 25(5):1425–1446, 2019.
Publisher: Springer.
|
[466]
|
Astrid Mager and Christian Katzenbach.
Future imaginaries in the making and governing of digital technology:
Multiple, Contested, Commodified.
SocArXiv. August, 25, 2020.
|
[467]
|
NDR.
Einbrecher-Jagd per App: Software zu ungenau.
NDR 1 Niedersachsen, page 1, January 2019.
[ .html ]
|
[468]
|
Cybercrime Polizei NRW.
[ http ]
|
[469]
|
APA.
Künstliche Intelligenz soll in Deutschland Kinderpornografie
im Netz erkennen.
DER STANDARD, page 1, May 2019.
[ http ]
|
[470]
|
Chris Boyd and Pete Forster.
Time and date issues in forensic computing—a case study.
Digital Investigation, 1(1):18–23, February 2004.
[ DOI |
http ]
|
[471]
|
Rob Kitchin.
Big Data, new epistemologies and paradigm shifts.
Big Data & Society, 1(1):1–12, April 2014.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[472]
|
Käthe von Bose, editor.
Körper, Materialitäten, Technologien.
Wilhelm Fink, Paderborn, 2018.
[ http ]
|
[473]
|
Jonathan Rotner.
How can Ethics make better AI products?
Technical report, MITRE.
|
[474]
|
United Nations Interregional (UNICRI) Crime and Justice Research Institute,
Centre for Artificial Intelligence and Robotics, and Innovation Centre of
the International Criminal Police Organization (INTERPOL).
Artificial Intelligence and Robotics for law Enforcement.
Technical report, UNICIR; Interpol, Lyon, France; Torino, Italy,
2019.
[ .pdf ]
|
[475]
|
Tobias Knobloch.
Vor die Lage kommen: Predictive Policing in Deutschland.
Chancen und Gefahren datenanalytischer Prognosetechnik und
Empfehlungen für den Einsatz in der Polizeiarbeit.
Technical report, Stiftung Neue Verantwortung; Bertelsmann Stiftung,
Berlin, August 2018.
[ .pdf ]
|
[476]
|
High-Level Expert Group on AI.
Ethics Guidelines for Trustworthy AI.
Technical report, European Commission, 2019.
[ http ]
|
[477]
|
Ben Buchanan and Taylor Miller.
Machine Learning for Policymakers. What It Is and Why
It Matters.
Technical report, Belfer Center for Science and International
Affiars; Harvard Kennedy School, Cambridge, Massachusetts, 2017.
[ .pdf ]
|
[478]
|
Nick Bostrom.
Brief initial thoughts on artificial intelligence policy.
Technical report, University of Oxford, Oxford, 2016.
[ http ]
|
[479]
|
Leonie Beining, Peter Bihr, and Stefan Heumann.
Towards a European AI & Society Ecosystem. Why we need it
and how to empower it to shape Europe’s way on AI.
Policy Brief, Stiftung Neue Verantwortung, Berlin, February 2020.
[ http ]
|
[480]
|
Sirika Chhem and Rethy Chhem.
Fighting the COVID-19 Pandemic with AI.
Policy Brief 07, Asian Vision Institute, Cambodia, March 2020.
[ http ]
|
[481]
|
Dillon Reisman, Kate Crawford, Jason Schultz, and Meredith Whittaker.
Algorithmic Impact Assesments: A Practical Framework for
Public Agency Accountability.
Technical report, AI Now Institute, New York, 2018.
[ .pdf ]
|
[482]
|
European Public Service Union.
Die Digitalisierung in den Griff bekommen.
Briefing 4, European Public Service Union, Brussels, 2019.
[ .pdf ]
|
[483]
|
Ailisto Heikki, Anssi Neuvonen, Timo Seppälä, Marco Halén, Henrik Nyman, and
Heli Helaakoski.
Finnish AI Competences and How to Make Them Stronger.
Policy Brief 3, Finnish Prime Minister’s Office, Helsinki, 2019.
[ http ]
|
[484]
|
Finnish Ministry of Finance.
Information and information policy at the core of digitalisation.
Technical report.
|
[485]
|
McKinsey Global Institute.
AI, Automation, and the Future of Work: Ten Things to
Solve for.
Briefing Note, McKinsey Global Institute, New York, NY, June 2018.
[ .pdf ]
|
[486]
|
Philippe Lorenz.
AI Governance through Political Fora and Standards
Developing Organizations. Mapping the actors relevant to AI
governance.
Policy Brief, Stiftung Neue Verantwortung, Berlin, September 2020.
[ http ]
|
[487]
|
Internet Society.
Artificial Intelligence and Machine Learning: Policy Paper.
Policy Paper, Internet Society, Geneva; Reston, Va, April 2017.
[ http ]
|
[488]
|
Dietmar Harhoff, Stefan Heumann, Nicola Jentsch, and Philippe Lorenz.
Eckpunkte einer nationalen Strategie für Künstliche
Intelligenz.
Policy Brief, Stiftung Neue Verantwortung, Berlin, May 2018.
[ http ]
|
[489]
|
Stefan Heumann and Nicolas Zahn.
Erfolgsmessung von KI-Strategien. Mit Indikatoren und
Benchmarks die Umsetzung der Strategie erfolgreich steuern.
Policy Brief, Stiftung Neue Verantwortung, Berlin, September 2018.
[ http ]
|
[490]
|
Franz Gatzweiler.
Advancing Urban Health and Wellbeing Through Collective and
Artificial Intelligence: A Systems Approach 3.0.
Policy Brief 6, Institute of Urban Environment, Chinese Academy of
Science, Fujian, China, September 2017.
[ http ]
|
[491]
|
United States Government Accountability Office.
Artificial Intelligence: Emerging Opportunities, Challenges,
and Implications.
Highlights of a Forum, United States Government Accountability
Office, Washington, D.C., March 2018.
|
[492]
|
Ulrike Frank and Paola Sartori.
Machine politics: Europe and the AI revolution.
Policy Brief, European Council on Foreign Relations, London, July
2019.
[ http ]
|
[493]
|
United Nations Interregional Crime and Justice Research Institute (UNICRI),
and The International Criminal Police Organization (INTERPOL).
Towards Responsibel AI Innovation. Second UNICRI-INTERPOL
report on Artificial Intelligence for Law Enforcement.
Technical Report 2, INTERPOL; UNICRI, Torino; Lyon, 2020.
|
[494]
|
Gabriela Zanfir-Fortuna.
Policy Brief: European Commission’s Strategy for AI,
explained.
Future of Privacy Forum, page 1, July 2018.
[ http ]
|
[495]
|
Kate Saslow and Philippe Lorenz.
Artificial Intelligence Needs Human Rights. How the focus
on ethical AI fails to address privacy, discrimination and other concerns.
Policy Brief, Stiftung Neue Verantwortung, Berlin, September 2019.
[ .pdf ]
|
[496]
|
Natasha McCarthy and Jessica Montgomery.
Explainable AI: the basics.
Policy Brief DES6051, The Royal Society, London, November 2019.
ISBN: 978-1-78252-433-5.
|
[497]
|
Osonde Osoba and William Welser.
The Risk of Artificial Intelligence to Security and the
Future of Work.
Policy Brief PE-237-RC, RAND Center for Global Risk and Security,
Santa Monica, CA, 2017.
|
[498]
|
Simon White.
Use of New Technologies in Regulatory Delivery.
Policy Brief, Donor Committee for Enterprise Development,
Cambridge, UK, April 2020.
|
[499]
|
Lisa Hegemann, Leonie Sontheimer, and Gregor Becker.
Palantir Technologies: Die geheimnisvollen Datensortierer.
Die Zeit, September 2020.
[ http ]
|
[500]
|
Tero Karppi.
“The Computer Said So”: On the Ethics,
Effectiveness, and Cultural Techniques of Predictive Policing.
Social Media + Society, 4(2):205630511876829, April 2018.
[ DOI |
http ]
|
[501]
|
Kate Robertson, Cynthia Khoo, and Yolanda Song.
To Surveil and Predict: A Human Rights Analysis of
Algorithmic Policing in Canada.
Technical report, Citizenlab Canada, 2020.
|
[502]
|
Simon Egbert and Matthias Leese.
Criminal Futures: Predictive Policing and Everyday
Police Work.
Taylor & Francis, 2020.
|
[503]
|
Marion Fourcade and Jeffrey Gordon.
Learning Like a State: Statecraft in the Digital Age.
Journal of Law and Political Economy, 1(1), 2020.
|
[504]
|
Sarah Brayne.
The Criminal Law and Law Enforcement Implications of Big
Data.
Annual Review of Law and Social Science, 14(1):293–308,
October 2018.
[ DOI |
http ]
|
[505]
|
Sarah Brayne.
Predict and Surveil: Data, Discretion, and the Future of
Policing.
Oxford University Press, 1 edition, December 2020.
[ DOI |
http ]
|
[506]
|
Enter the Dragnet.
[ http ]
|
[507]
|
The Mistrials of Algorithmic Sentencing.
[ http ]
|
[508]
|
Frank Pasquale.
A rule of persons, not machines: the limits of legal automation.
Geo. Wash. L. Rev., 87:1, 2019.
Publisher: HeinOnline.
|
[509]
|
Fernando A. Delgado.
Machine Learning in Legal Practice: Notes from Recent
History.
In Proceedings of the 2019 AAAI/ACM Conference on AI,
Ethics, and Society, pages 557–558, Honolulu HI USA, January 2019. ACM.
[ DOI |
http ]
|
[510]
|
Mireille Hildebrandt.
Learning as a Machine. Crossovers Between Humans and
Machines.
Journal of Learning Analytics, 4(1), March 2017.
[ DOI |
http ]
|
[511]
|
Mireille Hildebrandt.
Smart technologies and the end(s) of law: novel entanglements of
law and technology.
EE Edward Elgar Publishing, Cheltenham, UK Northampton, MA, USA,
paperback edition edition, 2016.
OCLC: 952326033.
|
[512]
|
Jude McCulloch and Dean Wilson.
Pre-crime: Pre-emption, precaution and the future.
Number 28 in Routledge Frontiers of Criminal Justice.
Routledge, London, July 2015.
[ DOI |
http ]
|
[513]
|
Dean Wilson.
Algorithmic patrol: the futures of predictive policing.
In Ales Zavrsnik, editor, Big Data, Crime and Social
Control, pages 108–127. Routledge, London, 2018.
Num Pages: 230.
[ http ]
|
[514]
|
Diane Coyle and Adrian Weller.
“Explaining” machine learning reveals policy challenges.
Science, 368(6498):1433–1434, June 2020.
Publisher: American Association for the Advancement of Science
Section: Policy Forum.
[ DOI |
http ]
|
[515]
|
Paul Dourish and Edgar Gómez Cruz.
Datafication and data fiction: Narrating data and narrating with
data.
Big Data & Society, 5(2):2053951718784083, July 2018.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[516]
|
Angelika Adensamer, Andreas Czák, Alina Hanel, Marlene Kreil, Reinhard
Kreissl, Christof Mackinger, Hanna Prykhodzka, Clara Schermer, Teresa
Schwaninger, Lisa Seidl, Erwin Ernst Steinhammer, Christoph Tschohl, Herbert
Waloschek, and Levin Wotke.
Handbuch Überwachung.
epicenterworks – Plattform Grundrechtspolitik, Wien, 2020.
|
[517]
|
Ruth Herberg and Alicia Lindhoff.
Automatisch verdächtig: Polizei setzt zunehmend auf umstrittene
US-Software, January 2020.
Section: Politik.
[ .html ]
|
[518]
|
Ali Winston.
Palantir has secretly been using New Orleans to test its
predictive policing technology, February 2018.
[ http ]
|
[519]
|
Helena Machado and Rafaela Granja.
Police epistemic culture and boundary work with judicial authorities
and forensic scientists: the case of transnational DNA data exchange in the
EU.
New Genetics and Society, 38(3):289–307, July 2019.
Publisher: Routledge _eprint:
https://doi.org/10.1080/14636778.2019.1609350.
[ DOI |
http ]
|
[520]
|
Der Standard.
2.000 Unbescholtene als Hooligans erkannt: Gesichtserkennung
floppte bei Champions League-Finale.
DER STANDARD, page 1, May 2018.
[ http ]
|
[521]
|
Lena Landström, Niklas Eklund, and Markus Naarttijärvi.
Legal limits to prioritisation in policing – challenging the impact
of centralisation.
Policing and Society, pages 1–20, July 2019.
Publisher: Routledge.
[ DOI |
http ]
|
[522]
|
Austerity Policing, Emotional Labour and the Boundaries of Police
Work: An Ethnography of a Police Force Control Room in
England The British Journal of Criminology
Oxford Academic.
[ http ]
|
[523]
|
Viktor Mayer-Schönberger and Kenneth Cukier.
Big data: a revolution that will transform how we live, work and
think.
Murray Houghton Mifflin Harcourt, London Boston, Mass. [u.a.], 1.
publ.. edition, 2013.
|
[524]
|
Josh Cowls and Ralph Schroeder.
Causation, Correlation, and Big Data in Social Science
Research.
Policy & Internet, 7(4):447–472, 2015.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/poi3.100.
[ DOI |
http ]
|
[525]
|
Carsten Momsen.
Digitale Beweismittel aus der Sicht der Strafverteidigung.
In Cybercrime und Cyberinvestigations, pages 67–92. Nomos
Verlagsgesellschaft mbH & Co. KG, 2015.
[ DOI ]
|
[526]
|
Donna Haraway.
Situated Knowledges: The Science Question in Feminism and
the Privilege of Partial Perspective.
Feminist Studies, 14(3):575–599, 1988.
Publisher: Feminist Studies, Inc.
[ DOI |
http ]
|
[527]
|
Abien Fred Agarap.
How can I trust you?, April 2020.
[ http ]
|
[528]
|
ACM FAccT – 2021 Accepted CRAFT sessions.
[ http ]
|
[529]
|
Data Cards Playbook.
[ http ]
|
[530]
|
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman,
Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru.
Model Cards for Model Reporting.
Proceedings of the Conference on Fairness, Accountability, and
Transparency, pages 220–229, January 2019.
arXiv: 1810.03993.
[ DOI |
http ]
|
[531]
|
Praveen R.S. Gummadidala, Nanda Kumar Karippur, and Maddulety Koilakuntla.
Analysis of Factors Influencing the Adoption of Artificial
Intelligence for Crime Management.
In Sujeet K. Sharma, Yogesh K. Dwivedi, Bhimaraya Metri, and
Nripendra P. Rana, editors, Re-imagining Diffusion and Adoption of
Information Technology and Systems: A Continuing Conversation,
IFIP Advances in Information and Communication Technology, pages
3–9, Cham, 2020. Springer International Publishing.
[ DOI ]
|
[532]
|
Santosh K. Misra, Satyasiba Das, Sumeet Gupta, and Sujeet K. Sharma.
Public Policy and Regulatory Challenges of Artificial
Intelligence (AI).
In Sujeet K. Sharma, Yogesh K. Dwivedi, Bhimaraya Metri, and
Nripendra P. Rana, editors, Re-imagining Diffusion and Adoption of
Information Technology and Systems: A Continuing Conversation,
IFIP Advances in Information and Communication Technology, pages
100–111, Cham, 2020. Springer International Publishing.
[ DOI ]
|
[533]
|
Jayanthi Radhakrishnan and Sumeet Gupta.
Artificial Intelligence in Practice – Real-World Examples
and Emerging Business Models.
In Sujeet K. Sharma, Yogesh K. Dwivedi, Bhimaraya Metri, and
Nripendra P. Rana, editors, Re-imagining Diffusion and Adoption of
Information Technology and Systems: A Continuing Conversation,
IFIP Advances in Information and Communication Technology, pages
77–88, Cham, 2020. Springer International Publishing.
[ DOI ]
|
[534]
|
Raymond Lutui.
A multidisciplinary digital forensic investigation process model.
Business Horizons, 59(6):593–604, November 2016.
[ DOI |
http ]
|
[535]
|
Sebastian J. Golla.
Lernfähige KI erfordert lernfähiges Polizeirecht.
January 2020.
Publisher: Fachinformationsdienst für internationale und
interdisziplinäre Rechtsforschung.
[ DOI |
http |
Abstract ]
|
[536]
|
Lernfähige KI erfordert lernfähiges Polizeirecht.
[ http ]
|
[537]
|
Artificial Intelligence, Ethics, and Society — Home.
[ http ]
|
[538]
|
Alexander Babuta, Marion Oswald, and Christine Rinik.
Machine Learning Algorithms and Police Decision-Making:
Legal, Ethical and Regulatory Challenges.
Technical report, Royal United Services Institutefor Defence and
Security Studies, 2018.
|
[539]
|
Digital Forensics: Evidence Analysis via Intelligent Systems and
Practices – Sitio web de la Universidad de Cádiz.
[ http ]
|
[540]
|
Action CA17124.
[ http ]
|
[541]
|
EU Parliament and Committee on Budgetary Control.
USE OF BIG DATA AND AI IN FIGHTING CORRUPTION AND
MISUSE OF PUBLIC FUNDS Good practice, ways forward and how to
integrate new technology into contemporary control framework, 2021.
|
[542]
|
Patrick Perrot.
What about AI in Criminal Intelligence: From Predictive
Policing to AI Perspectives.
Eur. Police Sci. & Res. Bull., 16:65, 2017.
Publisher: HeinOnline.
|
[543]
|
Alicia Carriquiry, Heike Hofmann, Xiao Hui Tai, and Susan VanderPlas.
Machine learning in forensic applications.
Significance, 16(2):29–35, April 2019.
[ DOI |
http ]
|
[544]
|
What AI Can and Cannot Do for the Intelligence Community.
[ http ]
|
[545]
|
Marion Oswald and Jamie Grace.
Intelligence, policing and the use of algorithmic analysis: a freedom
of information-based study.
Journal of Information Rights, Policy and Practice, 1(1),
October 2016.
Number: 1 Publisher: Winchester University PRess.
[ DOI |
http ]
|
[546]
|
Marion Oswald, Jamie Grace, Sheena Urwin, and Geoffrey C. Barnes.
Algorithmic risk assessment policing models: lessons from the
Durham HART model and ‘Experimental’ proportionality.
Information & Communications Technology Law, 27(2):223–250,
May 2018.
Publisher: Routledge _eprint:
https://doi.org/10.1080/13600834.2018.1458455.
[ DOI |
http ]
|
[547]
|
Gunay Kazimzade and Milagros Miceli.
Biased Priorities, Biased Outcomes: Three Recommendations
for Ethics-oriented Data Annotation Practices.
In Proceedings of the AAAI/ACM Conference on AI,
Ethics, and Society, AIES ’20, page 71, New York, NY, USA, February
2020. Association for Computing Machinery.
[ DOI |
http ]
|
[548]
|
Judith Hauber.
Postfaktizität und Predictive Policing.
In Hans-Jürgen Lange and Michaela Wendekamm, editors,
Postfaktische Sicherheitspolitik: Gewährleistung von Sicherheit in
unübersichtlichen Zeiten, Studien zur Inneren Sicherheit, pages
191–209. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[549]
|
BKA – Homepage – Künstliche Intelligenz in der Polizeiarbeit.
[ .html ]
|
[550]
|
Künstliche Intelligenz – wir bringen Ihnen die Technologie näher.
[ http ]
|
[551]
|
Gloria GONZÁLEZ FUSTER.
Künstliche Intelligenz und Strafverfolgung – Auswirkungen
auf die Grundrechte.
Technical Report PE 656.295, Europäisches Parlament, July 2020.
|
[552]
|
First INTERPOL fully online training focused on digital evidence.
[ http ]
|
[553]
|
Artificial Intelligence and law enforcement: challenges and opportunities.
[ http ]
|
[554]
|
How AI will transform digital evidence management.
[ http ]
|
[555]
|
Timo Rademacher.
Artificial Intelligence and Law Enforcement.
In Thomas Wischmeyer and Timo Rademacher, editors, Regulating
Artificial Intelligence, pages 225–254. Springer International
Publishing, Cham, 2020.
[ DOI |
http ]
|
[556]
|
Nabile M. Safdar, John D. Banja, and Carolyn C. Meltzer.
Ethical considerations in artificial intelligence.
European Journal of Radiology, 122:108768, January 2020.
[ DOI |
http ]
|
[557]
|
Federico Liberatore, Lara Quijano-Sánchez, and Miguel Camacho-Collados.
Applications of data science in policing: VeriPol as an
investigation support tool.
European Law Enforcement Research Bulletin, pages 89–96, 2018.
Publisher: European Union Agency for Law Enforcement Training
(CEPOL).
|
[558]
|
Use of big data and AI in fighting corruption and misuse of public funds
Workshops Events CONT
Committees European Parliament.
[ http ]
|
[559]
|
Melanie Feinberg.
Material Vision.
In Proceedings of the 2017 ACM Conference on Computer
Supported Cooperative Work and Social Computing, CSCW ’17, pages
604–617, New York, NY, USA, February 2017. Association for Computing
Machinery.
[ DOI |
http ]
|
[560]
|
Artificial Intelligence and Law Enforcement – Impact on Fundamental
Rights – Think Tank.
[ http ]
|
[561]
|
Künstliche Intelligenz gegen das Verbrechen – BKA, LKA und DFKI
starten Forschungskooperation.
[ http ]
|
[562]
|
Global Data Law – Spring 2020.
[ http ]
|
[563]
|
Deutscher Bundestag – Enquete-Kommission „Künstliche
Intelligenz“.
[ http ]
|
[564]
|
Thomas Streinz.
The Evolution of European Data Law.
SSRN Scholarly Paper ID 3762971, Social Science Research
Network, Rochester, NY, January 2021.
[ http ]
|
[565]
|
Michael Veale, Reuben Binns, and Lilian Edwards.
Algorithms that remember: model inversion attacks and data protection
law.
Philosophical Transactions of the Royal Society A: Mathematical,
Physical and Engineering Sciences, 376(2133):20180083, November 2018.
Publisher: Royal Society.
[ DOI |
http ]
|
[566]
|
Leiser M.r and Dechesne F.
Governing machine-learning models: challenging the personal data
presumption.
International Data Privacy Law, 10(3):187–200, August 2020.
[ DOI |
http ]
|
[567]
|
Marco Gillies, Bongshin Lee, Nicolas d’Alessandro, Joëlle Tilmanne, Todd
Kulesza, Baptiste Caramiaux, Rebecca Fiebrink, Atau Tanaka, Jérémie Garcia,
Frédéric Bevilacqua, Alexis Héloir, Fabrizio Nunnari, Wendy Mackay, and
Saleema Amershi.
Human-Centred Machine Learning.
May 2016.
Pages: 3565.
[ DOI ]
|
[568]
|
Rafal Kocielnik, Saleema Amershi, and Paul N. Bennett.
Will You Accept an Imperfect AI? Exploring Designs for
Adjusting End-user Expectations of AI Systems.
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, CHI ’19, pages 1–14, New York, NY,
USA, May 2019. Association for Computing Machinery.
[ DOI |
http ]
|
[569]
|
Saleema Amershi, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, Eric Horvitz, Dan
Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina
Suh, Shamsi Iqbal, and Paul Bennett.
Guidelines for Human-AI Interaction.
April 2019.
Pages: 13.
[ DOI ]
|
[570]
|
Alex Taylor, Siân Lindley, Tim Regan, David Sweeney, Vasillis Vlachokyriakos,
Lillie Grainger, and Jessa Lingel.
Data-in-Place: Thinking through the Relations Between
Data and Community.
April 2015.
[ DOI ]
|
[571]
|
Qian Yang, Jina Suh, Nan-Chen Chen, and Gonzalo Ramos.
Grounding Interactive Machine Learning Tool Design in
How Non-Experts Actually Build Models.
June 2018.
[ DOI ]
|
[572]
|
R. Stuart Geiger, Kevin Yu, Yanlai Yang, Mindy Dai, Jie Qiu, Rebekah Tang, and
Jenny Huang.
Garbage in, garbage out? do machine learning application papers in
social computing report where human-labeled training data comes from?
In Proceedings of the 2020 Conference on Fairness,
Accountability, and Transparency, FAT* ’20, pages 325–336, New York,
NY, USA, January 2020. Association for Computing Machinery.
[ DOI |
http ]
|
[573]
|
Michael Muller, Christine Wolf, Josh Andres, Zahra Ashktorab, Narendra Nath,
Michael Desmond, Aabhas Sharma, Aabhas Sharma@ibm, Com, Kristina Brimijoin,
Qian Pan, Qian Pan@ibm, Evelyn Duesterwald, and Casey Dugan.
Designing Ground Truth and the Social Life of Labels
ACM Reference Format.
May 2021.
[ DOI ]
|
[574]
|
Alexander Gluba, Alexander Pett, Markus Pullen, and Maximilian Querbach.
Lagedaten, Datenlage, Prognoseansätze. Perspektiven des
„Predictive Policing“ in Niedersachsen. Teil 2.
SIAK-Journal – Zeitschrift für Polizeiwissenschaft und
polizeiliche Praxis, (3):20–27, 2020.
[ DOI |
http ]
|
[575]
|
Nicolas Raschauer.
„Staatlich geprüft“ (…).
Zeitschrift für Polizeiwissenschaft und polizeiliche Praxis,
17(3):75–85, 2020.
Publisher: Verlag Österreich.
[ DOI |
http ]
|
[576]
|
FAT* 2020 CRAFT session.
[ http ]
|
[577]
|
Five ways to make AI a greater force for good in 2021.
[ http ]
|
[578]
|
Mark Godsey and Marie Alou.
She Blinded Me with Science: Wrongful Convictions and the
“Reverse CSI-Effect”.
Faculty Articles and Other Publications, January 2011.
[ http ]
|
[579]
|
William C. Thompson and Edward L. Schumann.
Interpretation of statistical evidence in criminal trials.
Law and Human Behavior, 11(3):167–187, September 1987.
[ DOI |
http ]
|
[580]
|
Michael J. Saks.
Forensic identification: From a faith-based “Science” to a
scientific science.
Forensic Science International, 201(1):14–17, September 2010.
[ DOI |
http ]
|
[581]
|
Itiel E. Dror and Simon A. Cole.
The vision in “blind” justice: Expert perception, judgment, and
visual cognition in forensic pattern recognition.
Psychonomic Bulletin & Review, 17(2):161–167, April 2010.
[ DOI |
http ]
|
[582]
|
Mike Redmayne, Paul Roberts, Colin Aitken, and Graham Jackson.
Forensic Science Evidence in Question.
Criminal Law Rev., 347, May 2011.
|
[583]
|
Tony Ward.
Explaining and trusting expert evidence: What is a ‘sufficiently
reliable scientific basis’?
The International Journal of Evidence & Proof, 24(3):233–254,
July 2020.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[584]
|
Gary Edmond, Richard Kemp, Glenn Porter, David Hamer, Mike Burton, Katherine
Biber, and Mehera San Roque.
Atkins v The Emperor: The ‘Cautious’ Use of
Unreliable ‘Expert’ Opinion.
The International Journal of Evidence & Proof, 14(2):146–166,
April 2010.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[585]
|
Michael Lynch.
Science, truth, and forensic cultures: The exceptional legal status
of DNA evidence.
Studies in History and Philosophy of Science Part C: Studies in
History and Philosophy of Biological and Biomedical Sciences, 44(1):60–70,
March 2013.
[ DOI |
http ]
|
[586]
|
Paul Roberts.
LTDNA Evidence on Trial.
Frontiers in Genetics, 7, 2016.
Publisher: Frontiers.
[ DOI |
http ]
|
[587]
|
Christopher Hamlin.
Forensic cultures in historical perspective: technologies of witness,
testimony, judgment (and justice?).
Studies in History and Philosophy of Biological and Biomedical
Sciences, 44(1):4–15, March 2013.
[ DOI ]
|
[588]
|
Paul Roberts.
Paradigms of forensic science and legal process: a critical
diagnosis.
Philosophical Transactions of the Royal Society of London.
Series B, Biological Sciences, 370(1674), August 2015.
[ DOI ]
|
[589]
|
Paul Roberts.
Renegotiating forensic cultures: between law, science and criminal
justice.
Studies in History and Philosophy of Biological and Biomedical
Sciences, 44(1):47–59, March 2013.
[ DOI ]
|
[590]
|
Danielle Keats Citron and Daniel J. Solove.
Privacy Harms.
SSRN Scholarly Paper ID 3782222, Social Science Research
Network, Rochester, NY, February 2021.
[ DOI |
http ]
|
[591]
|
Unfairness By Algorithm: Distilling the Harms of Automated
Decision-Making – Future of Privacy Forum.
[ http ]
|
[592]
|
ICO call for views: AI and data protection risk mitigation and management
toolkit, March 2021.
Publisher: ICO.
[ http ]
|
[593]
|
Ignacio Cofone and Katherine J. Strandburg.
Strategic Games and Algorithmic Secrecy.
SSRN Scholarly Paper ID 3440878, Social Science Research
Network, Rochester, NY, October 2019.
[ DOI |
http ]
|
[594]
|
Ethical AI Frameworks, Guidelines, Toolkits.
[ http ]
|
[595]
|
Min Kyung Lee.
Understanding perception of algorithmic decisions: Fairness, trust,
and emotion in response to algorithmic management.
Big Data & Society, 5(1):2053951718756684, January 2018.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[596]
|
Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler, Diana
Serbanescu, and Alex Hanna.
Documenting Computer Vision Datasets: An Invitation to
Reflexive Data Practices.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 161–172, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[597]
|
Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur
Kjartansson, Parker Barnes, and Margaret Mitchell.
Towards Accountability for Machine Learning Datasets:
Practices from Software Engineering and Infrastructure.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 560–575, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[598]
|
Lauren Thornton, Bran Knowles, and Gordon Blair.
Fifty Shades of Grey: In Praise of a Nuanced Approach
Towards Trustworthy Design.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 64–76, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[599]
|
Bran Knowles and John T. Richards.
The Sanction of Authority: Promoting Public Trust in AI.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 262–271, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[600]
|
Nil-Jana Akpinar, Maria De-Arteaga, and Alexandra Chouldechova.
The effect of differential victim crime reporting on predictive
policing systems.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 838–849, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[601]
|
P. M. Krafft, Meg Young, Michael Katell, Jennifer E. Lee, Shankar Narayan,
Micah Epstein, Dharma Dailey, Bernease Herman, Aaron Tam, Vivian Guetler,
Corinne Bintz, Daniella Raz, Pa Ousman Jobe, Franziska Putz, Brian Robick,
and Bissan Barghouti.
An Action-Oriented AI Policy Toolkit for Technology
Audits by Community Advocates and Activists.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 772–781, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[602]
|
An Action-Oriented AI Policy Toolkit for Technology Audits by
Community Advocates and Activists Proceedings of the 2021
ACM Conference on Fairness, Accountability, and Transparency.
[ http ]
|
[603]
|
Severin Kacianka and Alexander Pretschner.
Designing Accountable Systems.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 424–437, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[604]
|
Alon Jacovi, Ana Marasović, Tim Miller, and Yoav Goldberg.
Formalizing Trust in Artificial Intelligence: Prerequisites,
Causes and Goals of Human Trust in AI.
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 624–635, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[605]
|
OECD.
Why open science is critical to combatting COVID-19, 2020.
[ http ]
|
[606]
|
LEEd – EU Agency for Law Enforcement Training.
[ http ]
|
[607]
|
Arvind Narayanan.
Tutorial: 21 fairness definitions and their politics, March 2018.
[ http ]
|
[608]
|
Louise Bezuidenhout and Emanuele Ratti.
What does it mean to embed ethics in data science? An integrative
approach based on microethics and virtues.
AI & SOCIETY, December 2020.
[ DOI |
http ]
|
[609]
|
Thilo Hagendorff.
The Ethics of AI Ethics: An Evaluation of Guidelines.
Minds and Machines, 30(1):99–120, March 2020.
[ DOI |
http ]
|
[610]
|
Will Orr and Jenny L. Davis.
Attributions of ethical responsibility by Artificial Intelligence
practitioners.
Information, Communication & Society, 23(5):719–735, April
2020.
Publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2020.1713842.
[ DOI |
http ]
|
[611]
|
Catherine D’Ignazio and Lauren F. Klein.
Data feminism.
Strong ideas series. The MIT Press,
Cambridge, Massachusetts London, England, 2020.
|
[612]
|
Andrew Iliadis and Federica Russo.
Critical data studies: An introduction.
Big Data & Society, 3(2):2053951716674238, December 2016.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[613]
|
Craig M Dalton, Linnet Taylor, and Jim Thatcher (alphabetical).
Critical Data Studies: A dialog on data and space.
Big Data & Society, 3(1):2053951716648346, June 2016.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[614]
|
Paul Marks.
Can the biases in facial recognition be fixed; also, should they?
Communications of the ACM, 64(3):20–22, February 2021.
[ DOI |
http ]
|
[615]
|
Zoran Kanduc.
Machines, humans and the question of control.
In Ales Zavrsnik, editor, Big Data, Crime and Social
Control, pages 75 — 91. Routledge, London, 2018.
Num Pages: 230.
[ http ]
|
[616]
|
Laurence Diver.
Digisprudence: the design of legitimate code.
Technical report, LawArXiv, July 2020.
type: article.
[ DOI |
http ]
|
[617]
|
Lisa Gitelman.
“Raw data” is an oxymoron.
Infrastructures series. The MIT Press,, Cambridge, Massachusetts :,
2013.
[ http ]
|
[618]
|
Sheila Jasanoff.
Serviceable truths: science for action in law and policy.
Texas law review, 93(7):1723–, 2015.
Place: Austin Publisher: University of Texas at Austin.
|
[619]
|
Johanne Yttri Dahl and Ann Rudinow Sætnan.
“It all happened so slowly” – On controlling function creep
in forensic DNA databases.
International Journal of Law, Crime and Justice, 37(3):83–103,
September 2009.
[ DOI |
http ]
|
[620]
|
It all happened so slowly; On controlling function creep in forensic DNA
databases. – Universität Wien.
[ http ]
|
[621]
|
Deborah G. Mayo and Rachelle D. Hollander.
Acceptable evidence: : science and values in risk management.
Environmental ethics and science policy series. Oxford University
Press,, New York :, 1991.
[ http ]
|
[622]
|
Sheila Jasanoff.
Just Evidence: The Limits of Science in the Legal
Process.
The Journal of law, medicine & ethics, 34(2):328–341, 2006.
Place: Oxford, UK Publisher: Blackwell Publishing Ltd.
[ DOI ]
|
[623]
|
Ilke Turkmendag, Marie Fox, Charis Thompson, and Thérèse Murphy.
What’s Law got to do with Good Science?
Social & Legal Studies, 28(3):392–413, June 2019.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[624]
|
Milagros Miceli, Martin Schuessler, and Tianling Yang.
Between Subjectivity and Imposition: Power Dynamics in Data
Annotation for Computer Vision.
Proceedings of the ACM on Human-Computer Interaction,
4(CSCW2):115:1–115:25, October 2020.
[ DOI |
http ]
|
[625]
|
Florian Jaton.
Assessing biases, relaxing moralism: On ground-truthing practices
in machine learning design and application.
Big data & society, 8(1):205395172110135–, 2021.
Publisher: SAGE Publishing.
[ DOI ]
|
[626]
|
Florian Jaton and Geoffrey C. Bowker.
The Constitution of Algorithms: Ground-Truthing,
Programming, Formulating.
MIT Press, Cambridge, 2021.
|
[627]
|
Nick Seaver.
Knowing Algorithms, 2019.
ISBN: 9780691187075 Num Pages: 412-.
|
[628]
|
Knowing Algorithms, March 2019.
[ http ]
|
[629]
|
Lucy Suchman.
Making work visible.
Communications of the ACM, 38(9):56–64, September 1995.
[ DOI |
http ]
|
[630]
|
Robert Mitchell and Catherine Waldby.
Tissue Economies: Blood, Organs, and Cell Lines in
Late Capitalism.
Science and Cultural Theory. Duke University Press, 2006.
[ DOI ]
|
[631]
|
Uwe Ewald.
Digitale Beweismittel und neue Wege der Strafverteidigung.
Welche Herausforderungen stellt die Ausweitung
informationstechnologischer Überwachungs- und Ermittlungsmethoden an die
Strafverteidigung?
volume 42, pages 267 — 322, Münster, 2018.
Strafverteidigervereinigung.
[ .pdf ]
|
[632]
|
Madeleine Clare Elish and Danah Boyd.
Situating Methods in the Magic of Big Data and Artificial
Intelligence.
SSRN Scholarly Paper ID 3040201, Social Science Research
Network, Rochester, NY, September 2017.
[ http ]
|
[633]
|
Vidushi Marda and Shivangi Narayan.
On the importance of ethnographic methods in AI research.
Nature Machine Intelligence, 3(3):187–189, March 2021.
Number: 3 Publisher: Nature Publishing Group.
[ DOI |
http ]
|
[634]
|
Eoghan Casey.
The chequered past and risky future of digital forensics.
Australian Journal of Forensic Sciences, 51(6):649 — 664,
February 2019.
[ DOI ]
|
[635]
|
Paul Roberts.
Expert Evidence and Scientific Proof in Criminal
Trials.
Routledge, July 2017.
Google-Books-ID: zCcxDwAAQBAJ.
|
[636]
|
Sonja Bitzer, Laetitia Heudt, Aurélie Barret, Lore George, Karolien Van Dijk,
Fabrice Gason, and Bertrand Renard.
The introduction of forensic advisors in Belgium and their role in
the criminal justice system.
Science & Justice, 58(3):177–184, May 2018.
[ DOI |
http ]
|
[637]
|
Atsuro Morita.
Multispecies Infrastructure: Infrastructural Inversion and
Involutionary Entanglements in the Chao Phraya Delta, Thailand.
Ethnos.
[ http ]
|
[638]
|
Andrew Pickering.
The mangle of practice: time, agency, and science.
University of Chicago Press, Chicago, 1995.
|
[639]
|
Susan Leigh Star.
The Ethnography of Infrastructure.
American Behavioral Scientist, 43(3):377–391, November 1999.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[640]
|
Lucy Suchmann, Jeanette Blomberg, Julian E. Orr, and Randall Trigg.
Reconstructing Technologies as Social Practice.
American Behavioral Scientist, 43(3):392–408, November 1999.
Publisher: SAGE Publications Inc.
[ DOI |
http ]
|
[641]
|
H. M. A. van Beek, E. J. van Eijk, R. B. van Baar, M. Ugen, J. N. C. Bodde, and
A. J. Siemelink.
Digital forensics as a service: Game on.
Digital Investigation, 15:20–38, December 2015.
[ DOI |
http ]
|
[642]
|
P. A. C. Duijn and P. M. A. Sloot.
From data to disruption.
Digital Investigation, 15:39–45, December 2015.
[ DOI |
http ]
|
[643]
|
Wilco Wisse and Cor Veenman.
Scripting DNA: Identifying the JavaScript programmer.
Digital Investigation, 15:61–71, December 2015.
[ DOI |
http ]
|
[644]
|
Editorial Board.
Digital Investigation, 15:i, December 2015.
[ DOI |
http ]
|
[645]
|
Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein, Peter H. Wrege,
and Carla P. Gomes.
Automatic Detection and Compression for Passive Acoustic
Monitoring of the African Forest Elephant.
Proceedings of the AAAI Conference on Artificial Intelligence,
33(01):476–484, July 2019.
Number: 01.
[ DOI |
http ]
|
[646]
|
Kimberly Houser and Anjanette Raymond.
It Is Time to Move Beyond the ‘AI Race’ Narrative:
Why Investment and International Cooperation Must Win the Day.
SSRN Scholarly Paper ID 3582641, Social Science Research
Network, Rochester, NY, April 2020.
[ http ]
|
[647]
|
Debra Benita Shaw.
The Aesthetics of Retrieval: Beautiful Data, Glitch Art
and Popular Culture.
Anthropocenes – Human, Inhuman, Posthuman, October 2020.
Publisher: University of Westminster Press.
[ DOI |
http ]
|
[648]
|
Zeno J. Geradts and Katrin Franke.
Editorial for big data issue.
Digital Investigation, 15:18–19, December 2015.
[ DOI |
http ]
|
[649]
|
Peter Sommer.
DI commentary: Big Data and privacy.
Digital Investigation, 15:101–103, December 2015.
[ DOI |
http ]
|
[650]
|
Javier Andreu-Perez, Carmen Poon, Robert Merrifield, Stephen Wong, and
Guang-Zhong Yang.
Big Data for Health.
IEEE journal of biomedical and health informatics, 19, July
2015.
[ DOI ]
|
[651]
|
Tom Simonite.
Behind the Paper That Led to a Google Researcher’s
Firing.
Wired, December 2020.
[ http ]
|
[652]
|
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret
Shmitchell.
On the Dangers of Stochastic Parrots: Can Language Models
Be Too Big?
In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, FAccT ’21, pages 610–623, New York,
NY, USA, March 2021. Association for Computing Machinery.
[ DOI |
http ]
|
[653]
|
Richmond Alake.
Machine Learning In The World Of Blockchain and
Cryptocurrency, May 2021.
[ http ]
|
[654]
|
Mitchell Clark.
Iran bans cryptocurrency mining for four months to stave off
blackouts.
The Verge, May 2021.
[ http ]
|
[655]
|
Sy Taffel.
Data and oil: Metaphor, materiality and metabolic rifts.
New Media & Society, page 14614448211017887, June 2021.
Publisher: SAGE Publications.
[ DOI |
http ]
|
[656]
|
Kristian Lum and Rumman Chowdhury.
What is an “algorithm”? It depends whom you ask.
MIT Technology Review, February 2021.
[ http ]
|
[657]
|
Taotao Wang, Soung Chang Liew, and Shengli Zhang.
When blockchain meets AI: Optimal mining strategy achieved by
machine learning.
International Journal of Intelligent Systems, 36(5):2183–2207,
2021.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.22375.
[ DOI |
http ]
|
[658]
|
Iran bans cryptocurrency mining for four months after blackouts.
BBC News, May 2021.
[ http ]
|
[659]
|
Richard V. Ericson and Kevin D. Haggerty.
Policing the Risk Society.
University of Toronto Press, December 2018.
Publication Title: Policing the Risk Society.
[ http ]
|
[660]
|
Melissa Hamilton.
The sexist algorithm.
Behavioral Sciences & the Law, 37(2):145–157, 2019.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/bsl.2406.
[ DOI |
http ]
|
[661]
|
Michelle Anna Vaccaro.
Algorithms in Human Decision-Making: A Case Study With
the COMPAS Risk Assessment Software.
August 2019.
Accepted: 2020-08-28T09:45:17Z.
[ http ]
|
[662]
|
Emilie Cloatre.
Law and ANT (and its Kin): Possibilities, Challenges, and
Ways Forward.
Journal of Law and Society, 45(4):646–663, 2018.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jols.12133.
[ DOI |
http ]
|
[663]
|
Jeffrey L Vagle.
Tightening the OODA loop: Police militarization, race, and
algorithmic surveillance.
Mich. J. Race & L., 22:101, 2016.
Publisher: HeinOnline.
|
[664]
|
Claudia Wagner, Markus Strohmaier, Alexandra Olteanu, Emre Kıcıman, Noshir
Contractor, and Tina Eliassi-Rad.
Measuring algorithmically infused societies.
Nature, pages 1–6, June 2021.
Bandiera_abtest: a Cg_type: Nature Research Journals
Primary_atype: Reviews Publisher: Nature Publishing Group Subject_term:
Social sciences;Society Subject_term_id: social-sciences;society.
[ DOI |
http ]
|
[665]
|
Divya Ramjee and Katelyn Ringrose.
The Challenges of Forensic Genealogy: Dirty Data,
Electronic Evidence, and Privacy Concerns.
Denver Law Review, 98:157, 2020.
[ http ]
|
[666]
|
Xandra E. Kramer.
Challenges of Electronic Taking of Evidence: Old Problems
in a New Guise and New Problems in Disguise.
SSRN Scholarly Paper ID 3282678, Social Science Research
Network, Rochester, NY, September 2018.
[ http ]
|
[667]
|
Brian Almquist.
Electronic evidence and technology-assisted review.
2019.
[ http ]
|
[668]
|
Michele C. S. Lange and Kristin M. Nimsger.
Electronic Evidence and Discovery: What Every Lawyer
Should Know.
American Bar Association, 2004.
Google-Books-ID: qtOoyoxn3W4C.
|
[669]
|
Nick Seaver.
Knowing Algorithms.
Princeton University Press, May 2019.
Pages: 412-422 Publication Title: digitalSTS Section: digitalSTS.
[ http ]
|
[670]
|
Artificial Intelligence and UK National Security: Policy
Considerations.
[ http ]
|
[671]
|
Stephen Mason and Daniel Seng.
Electronic Evidence.
University of London Press, 2017.
Accepted: 2020-05-27T16:45:21Z.
[ DOI |
http ]
|
[672]
|
Marco Gillies, Rebecca Fiebrink, Atau Tanaka, Jérémie Garcia, Frédéric
Bevilacqua, Alexis Heloir, Fabrizio Nunnari, Wendy Mackay, Saleema Amershi,
Bongshin Lee, Nicolas d’Alessandro, Joëlle Tilmanne, Todd Kulesza, and
Baptiste Caramiaux.
Human-Centred Machine Learning.
In Proceedings of the 2016 CHI Conference Extended
Abstracts on Human Factors in Computing Systems, CHI EA ’16,
pages 3558–3565, New York, NY, USA, May 2016. Association for Computing
Machinery.
[ DOI |
http ]
|
[673]
|
Rebecca Fiebrink and Marco Gillies.
Introduction to the Special Issue on Human-Centered Machine
Learning.
ACM Transactions on Interactive Intelligent Systems,
8(2):7:1–7:7, June 2018.
[ DOI |
http ]
|
[674]
|
Marcus Rogers.
Technology and digital forensics.
In The Routledge Handbook of Technology, Crime and
Justice. Routledge, 2017.
Num Pages: 11.
|
[675]
|
PredPol.
Predict Prevent Crime Predictive Policing
Software, 2021.
[ http ]
|
[676]
|
Truth Machine.
[ .html ]
|
[677]
|
Michael Lynch and Simon Cole.
Science and Technology Studies on Trial: Dilemmas of
Expertise.
Social studies of science, 35(2):269–311, 2005.
Place: Thousand Oaks, CA Publisher: Sage Publications.
[ DOI ]
|
[678]
|
James Curtis Fraser.
Forensic science: : a very short introduction.
Number 211 in Very short introductions ;. Oxford University Press,,
Oxford ; New York :, 2010.
[ http ]
|
[679]
|
Anika Ludwig and Jim Fraser.
Effective use of forensic science in volume crime investigations:
Identifying recurring themes in the literature.
Science & Justice, 54(1):81–88, January 2014.
[ DOI |
http ]
|
[680]
|
Simon A. Cole.
A surfeit of science: The “CSI effect” and the media
appropriation of the public understanding of science.
Public Understanding of Science, 24(2):130–146, February 2015.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[681]
|
Abdalbasit Mohammed Qadir and Asaf Varol.
The Role of Machine Learning in Digital Forensics.
In 2020 8th International Symposium on Digital Forensics
and Security (ISDFS), pages 1–5, June 2020.
[ DOI ]
|
[682]
|
Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold,
Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald,
Benjamin Bruno Meier, Katharina Rombach, and Lukas Tuggener.
Deep Learning in the Wild.
arXiv:1807.04950 [cs, stat], July 2018.
arXiv: 1807.04950.
[ http ]
|
[683]
|
Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, and
Michael S. Bernstein.
The Disagreement Deconvolution: Bringing Machine Learning
Performance Metrics In Line With Reality.
In Proceedings of the 2021 CHI Conference on Human
Factors in Computing Systems, number 388, pages 1–14. Association for
Computing Machinery, New York, NY, USA, May 2021.
[ http ]
|
[684]
|
Finale Doshi-Velez, Mason Kortz, Ryan Budish, Chris Bavitz, Sam Gershman, David
O’Brien, Kate Scott, Stuart Schieber, James Waldo, David Weinberger, Adrian
Weller, and Alexandra Wood.
Accountability of AI Under the Law: The Role of
Explanation.
arXiv:1711.01134 [cs, stat], December 2019.
arXiv: 1711.01134.
[ http ]
|
[685]
|
Adrien Bibal, Michael Lognoul, Alexandre de Streel, and Benoît Frénay.
Legal requirements on explainability in machine learning.
Artificial Intelligence and Law, 29(2):149–169, June 2021.
[ DOI |
http ]
|
[686]
|
M. C. Elish and danah boyd.
Situating methods in the magic of Big Data and AI.
Communication Monographs, 85(1):57–80, January 2018.
Publisher: Routledge _eprint:
https://doi.org/10.1080/03637751.2017.1375130.
[ DOI |
http ]
|
[687]
|
Viktor Shestak and Victoria Goncharova.
Artificial Intelligence as a Means of Combatting Crime: A
Leap Forward in Digital Forensic Science.
SSRN Scholarly Paper ID 3613796, Social Science Research
Network, Rochester, NY, May 2020.
[ http ]
|
[688]
|
Zeno Geradts.
Digital, big data and computational forensics.
Forensic Sciences Research, 3(3):179–182, July 2018.
Publisher: Taylor & Francis _eprint:
https://doi.org/10.1080/20961790.2018.1500078.
[ DOI |
http ]
|
[689]
|
Z. J. Geradts.
The Application of Artificial Intelligence (AI) in Digital
Forensic Science.
In Proceedings of the American Academy of Forensic
Sciences, volume 26, page 463, 2020.
[ http ]
|
[690]
|
Horst Clages and Rolf Ackermann.
Der rote Faden: Grundsätze der Kriminalpraxis.
Number 32 in Grundlagen der Kriminalistik. Kriminalistik-Verl,
Heidelberg, 12. edition, 2012.
|
[691]
|
Ibrahim Baggili and Vahid Behzadan.
Founding The Domain of AI Forensics.
SafeAI2020, Proceedings of the Workshop on Artificial
Intelligence Safety(34th AAAI Conference on Artificial Intelligence):1–5,
December 2019.
arXiv: 1912.06497.
[ DOI |
http ]
|
[692]
|
Janet Vertesi.
Introduction: Infrastructure.
In DigitalSTS: a field guide for science & technology
studies, pages 263 — 266. Princeton University Press, Princeton, 2019.
|
[693]
|
D. Lewis, G. Agam, S. Argamon, O. Frieder, D. Grossman, and J. Heard.
Building a test collection for complex document information
processing.
In Proceedings of the 29th annual international ACM SIGIR
conference on Research and development in information retrieval, SIGIR
’06, pages 665–666, New York, NY, USA, August 2006. Association for
Computing Machinery.
[ DOI |
http ]
|
[694]
|
Zotero Downloads.
[ http ]
|
[695]
|
Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, and
Michael S. Bernstein.
The Disagreement Deconvolution: Bringing Machine Learning
Performance Metrics In Line With Reality.
In Proceedings of the 2021 CHI Conference on Human
Factors in Computing Systems, number 388, pages 1–14. Association for
Computing Machinery, New York, NY, USA, May 2021.
[ http ]
|
[696]
|
Nithya Sambasivan, Shivani Kapania, Hannah Highfill, Diana Akrong, Praveen
Paritosh, and Lora M Aroyo.
Everyone wants to do the model work, not the data work. Data
Cascades in High-Stakes AI.
In Proceedings of the 2021 CHI Conference on Human
Factors in Computing Systems, number 39, pages 1–15. Association for
Computing Machinery, New York, NY, USA, May 2021.
[ http ]
|
[697]
|
European Commission.
Proposal for a Regulation of the European Parliament and of the
Council laying down harmoniesd rules on artificial intelligence
(Artificial Intelligence Act) and amending certain union legislative
acts, April 2021.
|
[698]
|
Jo Reichertz and Sylvia Marlene Wilz.
Polizeiliche Aufklärungsarbeit 2.0.
SIAK-Journal − Zeitschrift für Polizeiwissenschaft und
polizeiliche Praxis, (1):31–39, 2016.
[ DOI |
http ]
|
[699]
|
Dana Wilson-Kovacs.
Digital media investigators: challenges and opportunities in the use
of digital forensics in police investigations in England and Wales.
Policing: An International Journal, 44(4):669–682, January
2021.
Publisher: Emerald Publishing Limited.
[ DOI |
http ]
|
[700]
|
Dana Wilson-Kovacs.
Digital media investigators: challenges and opportunities in the use
of digital forensics in police investigations in England and Wales.
Policing: An International Journal, 44(4):669–682, January
2021.
Publisher: Emerald Publishing Limited.
[ DOI |
http ]
|
[701]
|
Anita Lavorgna and Pamela Ugwudike.
The datafication revolution in criminal justice: An empirical
exploration of frames portraying data-driven technologies for crime
prevention and control.
Big Data & Society, 8(2):20539517211049670, July 2021.
Publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[702]
|
Europäisches Parlament.
Angenommene Texte – Künstliche Intelligenz im Strafrecht und
ihre Verwendung durch die Polizei und Justizbehörden in Strafsachen
– Mittwoch, 6. Oktober 2021, 2021.
[ .html ]
|
[703]
|
Europäisches Parlament.
Einsatz von KI durch die Polizei: Abgeordnete lehnen
Massenüberwachung ab, June 2021.
[ http ]
|
[704]
|
Vorschlag für eine VERORDNUNG DES EUROPÄISCHEN PARLAMENTS UND DES
RATES ZUR FESTLEGUNG HARMONISIERTER VORSCHRIFTEN FÜR
KÜNSTLICHE INTELLIGENZ (GESETZ ÜBER KÜNSTLICHE INTELLIGENZ)
UND ZUR ÄNDERUNG BESTIMMTER RECHTSAKTE DER UNION, 2021.
[ http ]
|
[705]
|
Vegard Kolbjørnsrud, Richard Amico, and Robert J Thomas.
How Artificial Intelligence Will Redefine Management.
page 6, 2016.
|
[706]
|
Alexander Campolo and Kate Crawford.
Enchanted Determinism: Power without Responsibility in
Artificial Intelligence.
Engaging Science, Technology, and Society, 6:1–19, January
2020.
[ DOI |
http ]
|
[707]
|
Jędrzej Niklas and Lina Dencik.
What rights matter? Examining the place of social rights in the
EU’s artificial intelligence policy debate.
Internet Policy Review, 10(3), September 2021.
[ http ]
|
[708]
|
Heike Felzmann, Eduard Fosch Villaronga, Christoph Lutz, and Aurelia
Tamò-Larrieux.
Transparency you can trust: Transparency requirements for
artificial intelligence between legal norms and contextual concerns.
Big Data & Society, 6(1):2053951719860542, 2019.
Publisher: SAGE Publications Sage UK: London, England.
|
[709]
|
Shea Brown, Jovana Davidovic, and Ali Hasan.
The algorithm audit: Scoring the algorithms that score us.
Big Data & Society, 8(1):2053951720983865, 2021.
Publisher: SAGE Publications Sage UK: London, England.
|
[710]
|
Bogdana Rakova, Jingying Yang, Henriette Cramer, and Rumman Chowdhury.
Where responsible AI meets reality: Practitioner perspectives on
enablers for shifting organizational practices.
Proceedings of the ACM on Human-Computer Interaction,
5(CSCW1):1–23, 2021.
Publisher: ACM New York, NY, USA.
|
[711]
|
Mark Findlay and Josephine Seah.
An Ecosystem Approach to Ethical AI and Data Use:
Experimental Reflections.
In 2020 IEEE/ITU International Conference on
Artificial Intelligence for Good (AI4G), pages 192–197. IEEE, 2020.
|
[712]
|
UNICRI Interpol.
Artificial intelligence and robotics for law enforcement, 2019.
|
[713]
|
Tatiana Tommasi, Silvia Bucci, Barbara Caputo, and Pietro Asinari.
Towards Fairness Certification in Artificial Intelligence,
2021.
_eprint: 2106.02498.
|
[714]
|
Serena Quattrocolo, Cosimo Anglano, Massimo Canonico, and Marco Guazzone.
Technical Solutions for Legal Challenges: Equality of Arms
in Criminal Proceedings.
Global Jurist, 20(1), January 2020.
[ DOI |
http ]
|
[715]
|
Ram Shankar Siva Kumar, David R O’Brien, Kendra Albert, and Salome Vilojen.
Law and Adversarial Machine Learning.
arXiv preprint arXiv:1810.10731, 2018.
|
[716]
|
Tyler J. Loftus, Gilbert R. Upchurch, Daniel Delitto, Parisa Rashidi, and Azra
Bihorac.
Mysteries, Epistemological Modesty, and Artificial
Intelligence in Surgery.
Frontiers in Artificial Intelligence, 2:32, January 2020.
[ DOI |
http ]
|
[717]
|
Sally A. Applin and Michael D. Fischer.
New technologies and mixed-use convergence: How humans and
algorithms are adapting to each other.
In 2015 IEEE International Symposium on Technology and
Society (ISTAS), pages 1–6, Dublin, Ireland, November 2015. IEEE.
[ DOI |
http ]
|
[718]
|
Sheila Jasanoff and Sang-Hyun Kim.
Containing the atom: Sociotechnical imaginaries and nuclear power
in the United States and South Korea.
Minerva, 47(2):119, 2009.
|
[719]
|
Susan Leigh Star and James R Griesemer.
Institutional Ecology, ‘Translations’ and Boundary Objects:
Amateurs and Professionals in Berkeley’s Museum of Vertebrate
Zoology, 1907-39.
Social Studies of Science, 19(3):387–420, 1989.
[ http ]
|
[720]
|
Madeleine Akrich.
The de-scription of technical objects, 1992.
|
[721]
|
Bruno Latour.
Eine neue Soziologie für eine neue Gesellschaft.
suhrkamp, Frankfurt am Main, 2007.
|
[722]
|
John Law and Michel Callon.
Aircraft Project: A Network Analysis of Technological
Change.
35(3):284–297, 2014.
|
[723]
|
John Law.
Notes on the Theory of the Actor-Network: Ordering,
Strategy and Heterogeneity.
Systems Practice, 5:379–393, 1992.
|
[724]
|
Danah Boyd and Kate Crawford.
Critical questions for big data: Provocations for a cultural,
technological, and scholarly phenomenon.
Information, communication & society, 15(5):662–679, 2012.
|
[725]
|
Rob Kitchin.
Big Data, new epistemologies and paradigm shifts.
Big Data & Society, 1(1):205395171452848, July 2014.
[ DOI |
http ]
|
[726]
|
Louise Amoore.
The Politics of Possibility.
2013.
|
[727]
|
Philipp Mayring.
Qualitative Content Analysis.
Forum Qualitative Sozialforschung / Forum: Qualitative Social
Research, 1(2), 2000.
[ DOI |
http ]
|
[728]
|
George E Marcus.
Ethnography in/of the world system: The emergence of multi-sited
ethnography.
Annual review of anthropology, 24(1):95–117, 1995.
Publisher: Annual Reviews 4139 El Camino Way, PO Box 10139, Palo
Alto, CA 94303-0139, USA.
|
[729]
|
Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini,
Joonseok Lee, and Emily Denton.
Saving face: Investigating the ethical concerns of facial
recognition auditing.
In Proceedings of the AAAI/ACM Conference on AI,
Ethics, and Society, pages 145–151, 2020.
|
[730]
|
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner.
Machine bias.
ProPublica, May, 23(2016):139–159, 2016.
|
[731]
|
European Commission. Directorate General for Communications Networks, Content
and Technology. and Hochrangige Expertengruppe für künstliche
Intelligenz.
Ethik-leitlinien für eine vertrauenswürdige KI.
Publications Office, LU, 2019.
[ http ]
|
[732]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act —
Analysing the good, the bad, and the unclear elements of the proposed
approach.
Computer Law Review International, 22(4):97–112, August 2021.
Publisher: Verlag Dr. Otto Schmidt.
[ DOI |
http ]
|
[733]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act —
Analysing the good, the bad, and the unclear elements of the proposed
approach.
Computer Law Review International, 22(4):97–112, August 2021.
Publisher: Verlag Dr. Otto Schmidt.
[ DOI |
http ]
|
[734]
|
Simon Egbert.
Predictive Policing and the Platformization of Police Work.
Surveillance & Society, 17:83–88, March 2019.
[ DOI ]
|
[735]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act.
SSRN Scholarly Paper ID 3896852, Social Science Research
Network, Rochester, NY, July 2021.
[ http ]
|
[736]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act.
SSRN Scholarly Paper ID 3896852, Social Science Research
Network, Rochester, NY, July 2021.
[ http ]
|
[737]
|
Thomas Burri and Fredrik von Bothmer.
The New EU Legislation on Artificial Intelligence: A
Primer.
SSRN Scholarly Paper ID 3831424, Social Science Research
Network, Rochester, NY, April 2021.
[ DOI |
http ]
|
[738]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act —
Analysing the good, the bad, and the unclear elements of the proposed
approach.
Computer Law Review International, 22(4):97–112, August 2021.
Publisher: Verlag Dr. Otto Schmidt.
[ DOI |
http ]
|
[739]
|
Michael Veale and Frederik Zuiderveen Borgesius.
Demystifying the Draft EU Artificial Intelligence Act —
Analysing the good, the bad, and the unclear elements of the proposed
approach.
Computer Law Review International, 22(4):97–112, August 2021.
Publisher: Verlag Dr. Otto Schmidt.
[ DOI |
http ]
|
[740]
|
Martin Ebers, Veronica R. S. Hoch, Frank Rosenkranz, Hannah Ruschemeier, and
Björn Steinrötter.
The European Commission’s Proposal for an Artificial
Intelligence Act—A Critical Assessment by Members of the
Robotics and AI Law Society (RAILS).
J, 4(4):589–603, December 2021.
Number: 4 Publisher: Multidisciplinary Digital Publishing Institute.
[ DOI |
http ]
|
[741]
|
Michael Wiesmüller, Ingo Hegny, Alexander Banfield-Mumb-Mühlhaim, Markus
Triska, Erich Prem, and Bernhard Dachs.
Artificial Intelligence Mission Austria 2030 – Die Zukunft
der Künstlichen Intelligenz in Österreich gestalten.
Technical report, Bundesministerium für Verkehr, Innovatoin,
Technologie; Bundesministerium für Digitalisierung und Wirtschaftsstandort,
Wien, 2019.
[ .pdf ]
|
[742]
|
European Commission.
On Artificial Intelligence. A European approach to excellence
and trust.
White Paper COM(2020) 65, European Commission, Unit A1 Robots and
Artificial Intelligence, Brüssel, 2020.
[ http ]
|
[743]
|
Anna Lauren Hoffmann.
Data Violence and How Bad Engineering Choices Can
Damage Society, April 2018.
source: medium.com.
[ http ]
|
[744]
|
Min Kyung Lee, Daniel Kusbit, Evan Metsky, and Laura Dabbish.
Working with Machines: The Impact of Algorithmic and
Data-Driven Management on Human Workers.
In Proceedings of the 33rd Annual ACM Conference on
Human Factors in Computing Systems, CHI ’15, pages 1603–1612,
Seoul, April 2015. Association for Computing Machinery.
[ DOI |
http ]
|
[745]
|
Lilian Edwards and Michael Veale.
Slave to the Algorithm? Why a ‘right to an explanation’ is
probably not the remedy you are looking for.
Duke Law and Technology Review, pages 18–84, November 2017.
[ DOI |
http ]
|
[746]
|
Simon Egbert and Susanne Krasmann.
Predictive Policing. Eine ethnographische Studie neuer
Technologien zur Vorhersage von Straftaten und ihre Folgen für die
polizeiliche Praxis. Abschlussbericht.
Abschlussbericht, Universität Hamburg, Hamburg, April 2019.
[ .pdf ]
|
[747]
|
Bundespolizeipräsidium Potsdam.
Abschlussbericht des Bundespolizeipräsidiums zum Teilprojekt 1
“Biometrische Gesichtserkennung” am Bahnhof Berlin Südkreuz.
Teilprojekt 1, Bundespolizeipräsidium Potsdam, Potsdam, September
2018.
[ http ]
|
[748]
|
Anja Bechmann and Geoffrey C Bowker.
Unsupervised by any other name: Hidden layers of knowledge
production in artificial intelligence on social media.
Big Data & Society, 6(1):1–11, January 2019.
publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[749]
|
European Commission.
Amended proposal for a Council Directive on the protection of
individuals with regard to the processing of personal data and on the free
movement of such data.
COM COM (92) 422, European Commission, Brussels, 1992.
[ http ]
|
[750]
|
Alexandra Chouldechova.
Fair prediction with disparate impact: A study of bias in
recidivism prediction instruments.
Big Data, 5(2):153–163, October 2016.
arXiv: 1610.07524.
[ DOI |
http ]
|
[751]
|
Österreichisches Bundeskriminalamt and Österreichisches Bundesministerium
für Inneres.
Österreichisches Bundeskriminalamt: Abteilungem im BK, 2020.
[ http ]
|
[752]
|
CriPA.
Crime Predictive Analytics (CriPA), February 2020.
source: www.kiras.at.
[ http ]
|
[753]
|
Niedersaechsisches Ministerium fuer Inneres und Sport.
Polizei Niedersachsen geht neue Wege: Mit PreMAP gegen
Einbrecher, December 2016.
[ .html ]
|
[754]
|
Hessisches Ministerium für Inneres und Sport.
Hessen Data, 2020.
|
[755]
|
Åsa Mäkitalo and Roger Säljö.
Invisible People: Institutional Reasoning and Reflexivity in
the Production of Services and”Social Facts” in Public Employment
Agencies.
Mind, Culture, and Activity, 9(3):160–178, August 2002.
publisher: Routledge _eprint:
https://doi.org/10.1207/S15327884MCA0903_02.
[ DOI |
http ]
|
[756]
|
Danyal Bayaz.
Finanzmarktaufsicht: Innovation braucht Kontrolle.
Wiwo.de, pages 1–2, November 2018.
[ .html ]
|
[757]
|
Roland Atzmüller and Christoph Hermann.
Veränderung öffentlicher Beschäftigung im Prozess der
Liberalisierung und Privatisierung. Rekommodifizierung von Arbeit und
Herausbildung eines neoliberalen Arbeitsregimes.
Österreichische Zeitschrift für Soziologie, 29(4):30–48,
December 2004.
publisher-place: Wiesbaden publisher: VS Verlag für
Sozialwissenschaften.
[ DOI ]
|
[758]
|
Michael Spranger and Dirk Labudde.
Textforensik.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 167–198. Springer,
Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[759]
|
Dirk Labudde and Michael Spranger, editors.
Forensik in der digitalen Welt: Moderne Methoden der
forensischen Fallarbeit in der digitalen und digitalisierten realen
Welt.
Springer, Berlin, Heidelberg, 2017.
[ DOI |
http ]
|
[760]
|
Laura Mahrenbach and Katja Mayer.
Framing Policy Visions of Big Data in Emerging States.
Canadian Journal of Communication, 45(1), February 2020.
[ DOI |
http ]
|
[761]
|
Rob Kitchin.
The data revolution: big data, open data, data infrastructures
& their consequences.
Sage, Los Angeles, Calif. [u.a.], 1. publ.. edition, June 2014.
|
[762]
|
Richard Herschel and Virginia M. Miori.
Ethics & Big Data.
Technology in Society, 49:31–36, May 2017.
[ DOI |
http ]
|
[763]
|
David Beer.
Metric power.
Palgrave Macmillan, London, 2016.
[ http ]
|
[764]
|
Doug Laney.
3D Data Management: Controlling Data Volume, Velocity
and Variety. Stanford, application delivery strategies.
Meta Group, (File 949), February 2001.
|
[765]
|
Constantin Houy, Oliver Gutermuth, Sharam Dadashnia, and Peter Loos.
Digitale Polizeiarbeit.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–10.
Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[766]
|
Patrick Vos de Haan and Andreas Kämpfer.
Künstliche Intelligenz und ihre Bedeutung für die Polizei.
Zusammenfassung des Vortrags, Bundeskriminalamt, Wiesbaden, June
2019.
[ .html ]
|
[767]
|
Shira Ovide.
When the Police Treat Software Like Magic.
The New York Times, page 0, June 2020.
[ .html ]
|
[768]
|
Mitali Nitish Thakor.
Algorithmic Detectives Against Child Trafficking:
Data, Entrapment, and the New Global Policing Network.
Doctor of Philosophy in History, Anthropology, and Science,
Technology and Society, Massachusetts Institute of Technology, Cambridge,
Massachusetts, August 2016.
[ http ]
|
[769]
|
Wolf J. Schünemann.
Cybersicherheit.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–11.
Springer, Wiesbaden, 2020.
[ DOI |
http ]
|
[770]
|
Europol.
Do criminals dream of electric sheep? How technology shapes the
future of crime and law enforcement.
Technical report, Europol, Den Haag, 2019.
[ .pdf ]
|
[771]
|
Stefania Milan and Lonneke Van der Velden.
The alternative epistemologies of data activism.
Digital Culture & Society, 2(2):57–74, January 2015.
publisher: transcript.
[ DOI ]
|
[772]
|
Sarah Brayne.
Big Data Surveillance: The Case of Policing.
American Sociological Review, 82(5):977–1008, August 2017.
[ DOI |
http ]
|
[773]
|
Lukas Staffler and Oliver Jany.
Künstliche Intelligenz und Strafrechtspflege – eine
Orientierung.
Zeitschrift für Internationale Strafrechtsdogmatik,
15(4):164–177, 2020.
publisher: Editors of ZIS.
[ .pdf ]
|
[774]
|
Chelsea Barabas, Colin Doyle, JB Rubinovitz, and Karthik Dinakar.
Studying up: reorienting the study of algorithmic fairness around
issues of power.
In Proceedings of the 2020 Conference on Fairness,
Accountability, and Transparency, FAT* ’20, pages 167–176, Barcelona,
Spain, January 2020. Association for Computing Machinery.
[ DOI |
http ]
|
[775]
|
Florian Jaton.
We get the algorithms of our ground truths: Designing referential
databases in digital image processing.
Social Studies of Science, 47(6):811–840, 2017.
SAGE Publications.
[ DOI |
http ]
|
[776]
|
Ian Bogost.
The Cathedral of Computation.
The Atlantic, page 1, January 2015.
[ http ]
|
[777]
|
Nick Seaver.
Algorithms as culture: Some tactics for the ethnography of
algorithmic systems.
Big Data & Society, 4(2):1–12, December 2017.
[ DOI |
http ]
|
[778]
|
Malte Ziewitz.
Governing Algorithms: Myth, Mess, and Methods.
Science, Technology, & Human Values, 41(1):3–16, January
2016.
https://journals-sagepub-com.uaccess.univie.ac.at/doi/full/10.1177/0162243915608948.
[ DOI |
http ]
|
[779]
|
Chris Anderson.
The End of Theory: The Data Deluge Makes the Scientific
Method Obsolete.
Wired, 15(06), June 2008.
[ http ]
|
[780]
|
Jackie Snow.
Algorithms are making American inequality worse.
MIT Technology Review, page 1, January 2018.
[ http ]
|
[781]
|
Solon Barocas, Sophie Hood, and Malte Ziewitz.
Governing Algorithms: A Provocation Piece.
Rochester, NY, March 2013. Social Science Research Network.
[ DOI |
http ]
|
[782]
|
Christen Mader, C. Cas, T. Abou-Chadi, A. Bernstein, N. Braun Binder,
D. Dell’Aglio, L Fábián, D. George, A. Gohdes, L. Hilty, M. Kneer,
J. Krieger-Lamina, H. Licht, A. Scherer, C. Som, P. Sutter, and F. Thouvenin.
Wenn Algorithmen für uns entscheiden: Chancen und Risiken
der künstlichen Intelligenz, volume 72 of TA-Swiss
Publikationsreihe.
TA-Swiss, Zürich, 2020.
|
[783]
|
Jessica Fjeld, Nele Achten, Hannah Hilligoss, Adam Nagy, and Madhulika
Srikumar.
Principled Artificial Intelligence: Mapping Consensus in
Ethical and Rights-Based Approaches to Principles for AI.
SSRN Scholarly Paper ID 3518482, Social Science Research
Network, Rochester, NY, January 2020.
[ DOI |
http ]
|
[784]
|
Joel Ross, Lilly Irani, M. Six Silberman, Andrew Zaldivar, and Bill Tomlinson.
Who are the crowdworkers? Shifting demographics in mechanical turk.
In CHI ’10 Extended Abstracts on Human Factors in
Computing Systems, CHI EA ’10, pages 2863–2872, Atlanta, Georgia,
USA, April 2010. Association for Computing Machinery.
[ DOI |
http ]
|
[785]
|
Linzi Wilson-Wilde.
The international development of forensic science standards—a
review.
Forensic science international, 288:1–9, 2018.
publisher: Elsevier.
[ DOI ]
|
[786]
|
Matthias Monroy.
„Vom Tatort bis zum Gerichtssaal“: EU will mehr
Qualität in der digitalen Kriminaltechnik, 2016.
[ http ]
|
[787]
|
European Commission.
The European Agenda on Security.
COM COM(2015)185, European Commission, Strasbourg, April 2015.
[ http ]
|
[788]
|
Dean Wilson.
Platform Policing and the Real-Time Cop.
Surveillance & Society, 17(1/2):69–75, 2019.
publisher-place: Kingston publisher: Surveillance Studies Network.
[ DOI |
http ]
|
[789]
|
P. Jeffrey Brantingham.
The Logic of Data Bias and Its Impact on Place- Based
Predictive Policing.
Ohio State Journal of Criminal Law, 15(2):473–486, 2018.
Accepted: 2018-06-08T19:11:09Z publisher: Ohio State University.
Moritz College of Law.
[ DOI |
http ]
|
[790]
|
Won Kim, Byoung-Ju Choi, Eui-Kyeong Hong, Soo-Kyung Kim, and Doheon Lee.
A Taxonomy of Dirty Data.
Data Mining and Knowledge Discovery, 7(1):81–99, January 2003.
[ DOI |
http ]
|
[791]
|
Algorithm Watch.
Gesichtserkennung. Atlas der Automatisierung., 2020.
source: atlas.algorithmwatch.org.
[ http ]
|
[792]
|
Lora Aroyo and Chris Welty.
Truth Is a Lie: Crowd Truth and the Seven Myths of
Human Annotation.
AI Magazine, 36(1):15–24, March 2015.
number: 1.
[ DOI |
http ]
|
[793]
|
Saleema Amershi, Maya Cakmak, William Bradley Knox, and Todd Kulesza.
Power to the People: The Role of Humans in Interactive
Machine Learning.
AI Magazine, 35(4):105–120, December 2014.
number: 4.
[ DOI |
http ]
|
[794]
|
Rashida Richardson, Jason Schultz, and Kate Crawford.
Dirty Data, Bad Predictions: How Civil Rights
Violations Impact Police Data, Predictive Policing Systems, and
Justice.
SSRN Scholarly Paper ID 3333423, Social Science Research
Network, Rochester, NY, March 2019.
[ http ]
|
[795]
|
Maia Apelt and Norma Möllers.
BMBF-Projekt MuViT-Soz. Soziologische Perspektiven auf
Musterkennung und Video Tracking. Schlussbericht.
BMBF-Projekt MuViT-Soz BMBF 13N10959, Univ. Potsdam, Potsdam,
2013.
dimensions: Online-Ressource (67 S., 872 KB) medium: application/pdf.
[ DOI |
http ]
|
[796]
|
Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos, and Elena L. Glassman.
Proxy Tasks and Subjective Measures Can Be Misleading in
Evaluating Explainable AI Systems.
In IUI ’20, pages 454 — 464, New York, January 2020.
Association for Computing Machinery.
[ DOI |
http ]
|
[797]
|
Michael Muller, Ingrid Lange, Dakuo Wang, David Piorkowski, Jason Tsay, Vera
Liao, Casey Dugan, and Thomas Erickson.
How Data Science Workers Work with Data.
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, page 14, Glasgow, 2019. ACM.
[ DOI |
http ]
|
[798]
|
Jason Radford and Kenneth Joseph.
Theory In, Theory Out: The Uses of Social Theory in
Machine Learning for Social Science.
Frontiers in Big Data, 3, 2020.
publisher: Frontiers.
[ DOI |
http ]
|
[799]
|
Cinthya Grajeda, Frank Breitinger, and Ibrahim Baggili.
Availability of datasets for digital forensics – And what is
missing.
Digital Investigation, 22:94–105, August 2017.
[ DOI |
http ]
|
[800]
|
Fondazione Prada.
Kate Crawford, Trevor Paglen: Training Humans. Fondazione
Prada, 2020.
[ http ]
|
[801]
|
Kari Paul.
Facebook to pay $52m for failing to protect moderators from
‘horrors’ of graphic content.
The Guardian, page 1, May 2020.
section: Technology.
[ http ]
|
[802]
|
Wolf Zimmer.
Die Legende von der Sharing Economy.
In Wolf Zimmer, editor, Ansturm der Algorithmen: Die
Verwechslung von Urteilskraft mit Berechenbarkeit, Die blaue Stunde
der Informatik, pages 77–82. Springer, Berlin, Heidelberg, 2019.
[ DOI |
http ]
|
[803]
|
Kelley Cotter.
Playing the visibility game: How digital influencers and algorithms
negotiate influence on Instagram.
New Media & Society, 21(4):895–913, 2019.
publisher-place: London, England publisher: SAGE Publications.
[ DOI ]
|
[804]
|
Ted Striphas.
Algorithmic culture.
European Journal of Cultural Studies, 18(4-5):395–412, 2015.
publisher-place: London, England publisher: SAGE Publications.
[ DOI |
http ]
|
[805]
|
Olivia Solon.
Artist reveals disembodied workers scanning books for Google.
Wired UK, January 2014.
section: Art.
[ http ]
|
[806]
|
Andrew Norman Wilson.
ScanOps, 2012.
[ .html ]
|
[807]
|
Mary South.
You Will Never Be Forgotten.
The New Yorker, January 2020.
[ http ]
|
[808]
|
Sarah Brayne.
Predict and Surveil: Data, Discretion, and the Future of
Policing.
Oxford University Press, 1 edition, December 2020.
[ DOI |
http ]
|
[809]
|
Dean Wilson.
Platform Policing and the Real-Time Cop.
Surveillance & Society, 17(1/2):69–75, 2019.
publisher-place: Kingston publisher: Surveillance Studies Network.
[ DOI |
http ]
|
[810]
|
Simon Egbert.
Predictive Policing and the Platformization of Police Work.
Surveillance & Society, 17:83–88, March 2019.
[ DOI ]
|
[811]
|
Uwe Ewald.
Digitale Beweismittel und neue Wege der Strafverteidigung.
In Strafverteidigervereinigung, volume 42 of Räume der
Unfreiheit, pages 267 — 321, Münster, 2018. Organisationsbüro
Strafverteidigervereinigung.
|
[812]
|
Norman P. Lewis and Stephenson Waters.
Data Journalism and the Challenge of Shoe-Leather
Epistemologies.
Digital Journalism, 6(6):719–736, June 2018.
publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2017.1377093.
[ DOI |
http ]
|
[813]
|
Timo Rademacher.
Artificial Intelligence and Law Enforcement.
In Thomas Wischmeyer and Timo Rademacher, editors, Regulating
Artificial Intelligence, pages 225–254. Springer International
Publishing, Cham, 2020.
[ DOI |
http ]
|
[814]
|
Simon Egbert and Matthias Leese.
Criminal Futures: Predictive Policing and Everyday
Police Work.
Taylor & Francis, 2020.
|
[815]
|
Matt Carlson.
News Algorithms, Photojournalism and the Assumption of
Mechanical Objectivity in Journalism.
Digital Journalism, 7(8):1117–1133, September 2019.
publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2019.1601577.
[ DOI |
http ]
|
[816]
|
Sarah Inman and David Ribes.
” Beautiful Seams” Strategic Revelations and Concealments.
In Proceedings of the 2019 CHI Conference on Human
Factors in Computing Systems, pages 1–14, Glasgow, Scotland Uk, 2019.
Association for Computing Machinery.
[ DOI ]
|
[817]
|
Kevin Hamilton, Karrie Karahalios, Christian Sandvig, and Motahhare Eslami.
A path to understanding the effects of algorithm awareness.
In Proceedings of the extended abstracts of the 32nd annual
ACM conference on Human factors in computing systems – CHI EA ’14,
pages 631–642, Toronto, Ontario, Canada, 2014. ACM Press.
[ DOI ]
|
[818]
|
T. Franklin Waddell.
Attribution Practices for the Man-Machine Marriage: How
Perceived Human Intervention, Automation Metaphors, and Byline
Location Affect the Perceived Bias and Credibility of Purportedly
Automated Content.
Journalism Practice, 13(10):1255–1272, November 2019.
publisher: Routledge _eprint:
https://doi.org/10.1080/17512786.2019.1585197.
[ DOI |
http ]
|
[819]
|
Samir Passi and Steven J. Jackson.
Data Vision: Learning to See Through Algorithmic
Abstraction.
In Proceedings of the 2017 ACM Conference on Computer
Supported Cooperative Work and Social Computing, pages 2436
–2447, Portland, February 2020. Association for Computing Machinery.
arXiv: 2002.03387 version: 1.
[ DOI |
http ]
|
[820]
|
Marcus Rogers.
Technology and digital forensics.
In The Routledge Handbook of Technology, Crime and
Justice. Routledge, 2017.
number-of-pages: 11.
|
[821]
|
Cindy Greenman.
Exploring the Impact of Artificial Intelligence on the
Accounting Profession.
Journal of Research in Business, Economics and Management,
8(3):1451–1454, March 2017.
[ http ]
|
[822]
|
Stefan Strohmeier and Franca Piazza.
Artificial Intelligence Techniques in Human Resource
Management — A Conceptual Exploration.
In Cengiz Kahraman and Sezi Çevik Onar, editors, Intelligent
Techniques in Engineering Management: Theory and Applications,
Intelligent Systems Reference Library, pages 149–172. Springer
International Publishing, Cham, 2015.
[ DOI |
http ]
|
[823]
|
Vinícius Fagundes, Raul Fernandes, Carlos Santos, and Tatiana Tavares.
Visualization of Climate Data from User Perspective:
Evaluating User Experience in Graphical User Interfaces and
Immersive Interfaces.
In Sakae Yamamoto, editor, Human Interface and the
Management of Information: Information, Knowledge and Interaction
Design, Lecture Notes in Computer Science, pages 55–70, Cham, 2017.
Springer International Publishing.
[ DOI ]
|
[824]
|
Alexander Babuta, Marion Oswald, and Christine Rinik.
Machine Learning Algorithms and Police Decision-Making:
Legal, Ethical and Regulatory Challenges.
Technical report, Royal United Services Institutefor Defence and
Security Studies, 2018.
|
[825]
|
Elizabeth E. Joh.
The Consequences of Automating and Deskilling the Police.
UCLA Law Review, 134(1):135 — 164, September 2019.
[ http ]
|
[826]
|
Michele Willson.
Algorithms (and the) everyday.
Information, Communication & Society, 20(1):137–150, 2017.
publisher: Routledge _eprint:
https://doi.org/10.1080/1369118X.2016.1200645.
[ DOI |
http ]
|
[827]
|
Geoffrey C. Bowker and Susan Leigh Star.
Sorting things out: classification and its consequences.
Inside technology. MIT Press, Cambridge, Mass, 2000.
[ http ]
|
[828]
|
Institut für musterbasierte Prognosetechnik.
PRECOBS im Einsatz, 2020.
[ .html ]
|
[829]
|
Matt Carlson.
The Robotic Reporter.
Digital Journalism, 3(3):416–431, May 2015.
publisher: Routledge _eprint:
https://doi.org/10.1080/21670811.2014.976412.
[ DOI |
http ]
|
[830]
|
Paola Tubaro, Antonio A Casilli, and Marion Coville.
The trainer, the verifier, the imitator: Three ways in which human
platform workers support artificial intelligence.
Big Data & Society, 7(1):2053951720919776, January 2020.
publisher: SAGE Publications Ltd.
[ DOI ]
|
[831]
|
Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, and
Eric Horvitz.
Updates in Human-AI Teams: Understanding and Addressing the
Performance/Compatibility Tradeoff.
Proceedings of the AAAI Conference on Artificial Intelligence,
33(01):2429–2437, July 2019.
number: 01.
[ DOI |
http ]
|
[832]
|
Marina Walker Guevara.
How Artificial Intelligence Can Help Us Crack More
Panama Papers Stories, March 2019.
source: www.icij.org section: Blog.
[ http ]
|
[833]
|
Neil Thurman, Konstantin Dörr, and Jessica Kunert.
When Reporters Get Hands-on with Robo-Writing.
Digital Journalism, 5(10):1240–1259, January 2017.
publisher: Routledge.
[ DOI |
http ]
|
[834]
|
Arjen Dalen.
The Algorihtms behind the Headlines. How machine-written news
redefines the core skills of human journalists.
Journalism Practice: The Future of Journalism 2011: Developments
and Debates, 6(5-6):648–658, 2012.
publisher: Taylor & Francis Group.
[ DOI |
http ]
|
[835]
|
Christian Borch and Ann-Christina Lange.
High-frequency Trader Subjectivity: Emotional Attachment and
Discipline in an Era of Algorithms.
Socio-Economic Review, 15(2):283–306, 2017.
publisher: Oxford University Press.
[ DOI |
http ]
|
[836]
|
Eduardo Porter.
Don’t Fight the Robots. Tax Them.
The New York Times, February 2019.
[ .html ]
|
[837]
|
Carl Benedikt Frey and Michael A. Osborne.
The future of employment: How susceptible are jobs to
computerisation?
Technological Forecasting and Social Change, 114:254–280,
January 2017.
[ DOI |
http ]
|
[838]
|
Aleš Završnik.
Algorithmic justice: Algorithms and big data in criminal justice
settings.
European Journal of Criminology, pages 1–20, September 2019.
publisher: SAGE Publications.
[ DOI |
http ]
|
[839]
|
Viola Schmid and Hanno Bauer.
Zur „Beweiskraft informationstechnologischer Expertise”.
In Helmut Redekker and Peter Hoppen, editors, DGRI Jahrbuch
2011, pages 259 — 266. Verlag Dr. Otto Schmidt, Köln, 2012.
[ http ]
|
[840]
|
Virginia Eubanks.
Automating inequality: How high-tech tools profile, police,
and punish the poor.
St. Martin’s Press, New York, first edition edition, 2018.
|
[841]
|
Mary L. Gray and Siddharth Suri.
Ghost Work (International Edition): How to Stop
Silicon Valley from Building a New Global Underclass.
First Edition. Mariner Books, Boston, 2019.
|
[842]
|
Institut für Arbeitsmarkt- und Berufsforschung.
Könnte ein Roboter meinen Job machen? Jetzt online testen!,
2020.
source: job-futuromat.iab.de.
[ http ]
|
[843]
|
Richard Baldwin.
White-Collar Robots Are Coming for Jobs.
Wall Street Journal, January 2019.
[ http ]
|
[844]
|
Melanie Arntz, Terry Gregory, and Ulrich Zierahn.
The Risk of Automation for Jobs in OECD Countries: A
Comparative Analysis.
Organisation for Economic Co-operation and Developmen,
01(189):1 — 34, May 2016.
publisher: OECD.
[ DOI |
http ]
|
[845]
|
Eckhard Fuchs.
Bildung im Zeichen der Globalisierung.
Handbuch der Erziehungswissenschaft, pages 857–868, August
2008.
publisher: Ferdinand Schöningh section: Handbuch der
Erziehungswissenschaft.
[ DOI |
http ]
|
[846]
|
David Watson.
Digital Forensics Processing and Procedures: Meeting the
Requirements of ISO 17020, ISO 17025, ISO 27001 and Best Practice
Requirements.
Syngress, Amsterdam, 2013.
[ http ]
|
[847]
|
Dirk Pawlaszczyk.
Digitaler Tatort, Sicherung und Verfolgung digitaler Spuren.
In Dirk Labudde and Michael Spranger, editors, Forensik in der
digitalen Welt: Moderne Methoden der forensischen Fallarbeit in der
digitalen und digitalisierten realen Welt, pages 113–166. Springer,
Berlin, Heidelberg, March 2017.
[ DOI |
http ]
|
[848]
|
Bundesamt für Sicherheit in der Informationstechnik.
Leitfaden IT-Forensik.
Government 1.01, Bundesamt für Sicherheit in der
Informationstechnik, March 2011.
[ http ]
|
[849]
|
Black in AI.
Black in AI, 2020.
source: blackinai.github.io.
[ http ]
|
[850]
|
Sarah Myers West, Meredith Whittaker, and Kate Crawford.
Discriminating Systems: Gender, Race and Power in
Artificial Intelligence.
Technical report, AI Now Institute, New York, February 2020.
Accepted: 2020-03-05T20:42:23Z publisher: Georgia Institute of
Technology.
[ http ]
|
[851]
|
Girls Who Code.
Girls Who Code, 2020.
source: girlswhocode.com.
[ http ]
|
[852]
|
ACM FAccT.
ACM Conference on Fairness, Accountability, and
Transparency (ACM FAccT), May 2020.
[ http ]
|
[853]
|
Europol.
Trustworthy AI Requires Solid Cybersecurity, October 2019.
source: www.europol.europa.eu.
[ http ]
|
[854]
|
Diogo Carvalho, Eduardo Pereira, and Jaime Cardoso.
Machine Learning Interpretability: A Survey on Methods and
Metrics.
Electronics, 8(8):832–864, 2019.
publisher: Multidisciplinary Digital Publishing Institute.
[ DOI |
http ]
|
[855]
|
Michael Lent, William Fisher, and Michael Mancuso.
An explainable artificial intelligence system for small-unit tactical
behavior.
In Proceedings of the 16th conference on Innovative
applications of artifical intelligence, IAAI’04, pages 900–907, San Jose,
California, June 2004. AAAI Press.
|
[856]
|
Bundesanstalt für Finanzdienstleistungsaufsicht.
Big Data trifft auf künstliche Intelligenz. Herausforderungen
und Implikationen für Aufsicht und Regulierung von
Finanzdienstleistungen.
Technical report, Bundesanstalt für Finanzdienstleistungsaufsicht,
Bonn, June 2018.
[ .html ]
|
[857]
|
Matthias Leese.
The new profiling: Algorithms, black boxes, and the failure of
anti-discriminatory safeguards in the European Union.
Security Dialogue, 45(5):494–511, October 2014.
publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[858]
|
Annette Vestby and Jonas Vestby.
Machine Learning and the Police: Asking the Right
Questions.
Policing: A Journal of Policy and Practice, September 2019.
[ DOI |
http ]
|
[859]
|
David Alvarez-Melis and Tommi Jaakkola.
A causal framework for explaining the predictions of black-box
sequence-to-sequence models.
arXiv.org, November 2017.
publisher-place: Ithaca publisher: Cornell University Library,
arXivorg.
[ http ]
|
[860]
|
Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, and
Wojciech Samek.
Layer-wise Relevance Propagation for Neural Networks with
Local Renormalization Layers.
In Artificial Neural Networks and Machine Learning –
ICANN 2016, volume 9887 of Lecture Notes in Computer Science,
pages 1–8, Cham, April 2016. Springer.
arXiv: 1604.00825.
[ DOI |
http ]
|
[861]
|
Council of Europe and Committee of experts on internet intermediaries.
Algorithms and human rights – Study on the human rights dimensions
of automated data processing techniques and possible regulatory implications.
Council of Europe Study (2017) 12, Council of Europe, Brussels,
March 2018.
[ .html ]
|
[862]
|
Mike Ananny and Kate Crawford.
Seeing without knowing: Limitations of the transparency ideal and
its application to algorithmic accountability.
New Media & Society, 20(3):973–989, March 2018.
publisher: SAGE Publications.
[ DOI ]
|
[863]
|
Fabian Muniesa.
Is a Stock Exchange a Computer Solution?: Explicitness,
Algorithms and the Arizona Stock Exchange.
International Journal of Actor Network Theory and Technological
Innovation, 3(1):1 — 15, 2011.
[ DOI ]
|
[864]
|
Frederik Zuiderveen Borgesius.
Discrimination, artificial intelligence, and algorithmic
decision-making.
Study, Council of Europe, Directorate General of Democracy,
Strasbourg, 2018.
[ http ]
|
[865]
|
Kevin Marschall.
Chancen und Risiken IT-forensischer Systeme.
In Kevin Marschall, editor, Rechtsverträgliche Gestaltung
IT-forensischer Systeme: Eine Untersuchung am Beispiel der
Aufdeckung und Beweisbarkeit von Versicherungsbetrug,
DuD-Fachbeiträge, pages 141–182. Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[866]
|
M. Hildebrandt and L. Janssens.
The New Imbroglio. Living with machine algorithms, 2016.
page: 55–60.
[ http ]
|
[867]
|
Christian Djeffal.
Künstliche Intelligenz.
In Tanja Klenk, Frank Nullmeier, and Göttrik Wewer, editors,
Handbuch Digitalisierung in Staat und Verwaltung, pages 1–12.
Springer Fachmedien, Wiesbaden, 2019.
[ DOI |
http ]
|
[868]
|
Danah boyd and Kate Crawford.
Critical Questions for Big Data: Provocations for a cultural,
technological, and scholarly phenomenon.
Information, Communication & Society: A decade in Internet
time: the dynamics of the Internet and society, 15(5):662–679, 2012.
publisher: Routledge.
[ DOI ]
|
[869]
|
Hannah Kuchler.
Max Schrems: the man who took on Facebook — and won, April
2018.
source: www.ft.com.
[ http ]
|
[870]
|
Thomas Burri and Fredrik Bothmer.
The New EU Legislation on Artificial Intelligence: A
Primer.
SSRN Scholarly Paper ID 3831424, Social Science Research
Network, Rochester, NY, April 2021.
[ DOI |
http ]
|
[871]
|
Max Schrems.
Kämpf um deine Daten.
edition a, Wien, 2014.
|
[872]
|
Rashida Richardson.
Confronting Black Boxes: A Shadow Report of the New
York City Automated Decision System Task Force.
Technical report, AI Now Institute, New York, December 2019.
|
[873]
|
Bilel Benbouzid.
To predict and to manage. Predictive policing in the United
States.
Big Data & Society, 6(1):1–13, January 2019.
publisher: SAGE Publications Ltd.
[ DOI |
http ]
|
[874]
|
Isabella Grabski.
Fairness in Machine Learning, January 2020.
source: sitn.hms.harvard.edu.
[ http ]
|
[875]
|
Peter Müller and Nikolaus Pöchhacker.
Algorithmic Risk Assessment als Medium des Rechts.
Österreichische Zeitschrift für Soziologie, 44(1):157–179,
June 2019.
[ DOI |
http ]
|
[876]
|
Fabia Schäufele.
Profiling zwischen sozialer Praxis und technischer Prägung:
Ein Vergleich von Flughafensicherheit und Credit-Scoring.
Springer VS Research. Springer VS, Wiesbaden, 2017.
|
[877]
|
Kashmir Hill.
Wrongfully Accused by an Algorithm.
The New York Times, June 2020.
[ .html ]
|
[878]
|
European Commission.
General Data Protection Regulation, May 2018.
|
[879]
|
Shaoqing Ren, Kaiming He, Ross B. Girshick, and Jian Sun.
Faster R-CNN: towards real-time object detection with region
proposal networks.
CoRR, abs/1506.01497, 2015.
[ arXiv |
http ]
|
[880]
|
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun.
Deep residual learning for image recognition.
CoRR, abs/1512.03385, 2015.
[ arXiv |
http ]
|
[881]
|
Justin Johnson and Taghi Khoshgoftaar.
Survey on deep learning with class imbalance.
Journal of Big Data, 6:27, 03 2019.
[ DOI ]
|
[882]
|
Dário Oliveira and Matheus Viana.
Fast cnn-based document layout analysis.
pages 1173–1180, 10 2017.
[ DOI ]
|
[883]
|
Xu Zhong, Jianbin Tang, and Antonio Jimeno-Yepes.
Publaynet: largest dataset ever for document layout analysis.
CoRR, abs/1908.07836, 2019.
[ arXiv |
http ]
|
[884]
|
Carlos Soto and Shinjae Yoo.
Visual detection with context for document layout analysis.
In Proceedings of the 2019 Conference on Empirical Methods in
Natural Language Processing and the 9th International Joint Conference on
Natural Language Processing (EMNLP-IJCNLP), pages 3464–3470, Hong Kong,
China, November 2019. Association for Computational Linguistics.
[ DOI |
http ]
|
[885]
|
Elhassan Mohamed, Konstantinos Sirlantzis, and Gareth Howells.
Application of Transfer Learning for Object Detection on
Manually Collected Data, pages 919–931.
01 2020.
[ DOI ]
|
[886]
|
Chuanqi Tan, Fuchun Sun, Tao Kong, Wenchang Zhang, Chao Yang, and Chunfang Liu.
A survey on deep transfer learning.
CoRR, abs/1808.01974, 2018.
[ arXiv |
http ]
|
[887]
|
X. Yi, L. Gao, Y. Liao, X. Zhang, R. Liu, and Z. Jiang.
Cnn based page object detection in document images.
In 2017 14th IAPR International Conference on Document Analysis
and Recognition (ICDAR), volume 01, pages 230–235, 2017.
|
[888]
|
K. Li, C. Wigington, C. Tensmeyer, H. Zhao, N. Barmpalios, V. I.
Morariu, V. Manjunatha, T. Sun, and Y. Fu.
Cross-domain document object detection: Benchmark suite and method.
In 2020 IEEE/CVF Conference on Computer Vision and Pattern
Recognition (CVPR), pages 12912–12921, 2020.
|
[889]
|
T. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár.
Focal loss for dense object detection.
In 2017 IEEE International Conference on Computer Vision
(ICCV), pages 2999–3007, 2017.
|
[890]
|
L. Gao, X. Yi, Z. Jiang, L. Hao, and Z. Tang.
Icdar2017 competition on page object detection.
In 2017 14th IAPR International Conference on Document Analysis
and Recognition (ICDAR), volume 01, pages 1417–1422, 2017.
|
[891]
|
Pawel Forczmański, Anton Smolinski, Adam Nowosielski, and Krzysztof
Malecki.
Segmentation of Scanned Documents Using Deep-Learning Approach,
pages 141–152.
Jan 2020.
[ DOI |
http ]
|
[892]
|
Adam W. Harley, Alex Ufkes, and Konstantinos G. Derpanis.
Evaluation of deep convolutional nets for document image
classification and retrieval, 2015.
[ arXiv ]
|
[893]
|
V. P. Le, N. Nayef, M. Visani, J. Ogier, and C. D. Tran.
Text and non-text segmentation based on connected component features.
In 2015 13th International Conference on Document Analysis and
Recognition (ICDAR), pages 1096–1100, 2015.
|
[894]
|
Arindam Das, Saikat Roy, Ujjwal Bhattacharya, and Swapan K Parui.
Document image classification with intra-domain transfer learning and
stacked generalization of deep convolutional neural networks.
In 2018 24th International Conference on Pattern Recognition
(ICPR), pages 3180–3185. IEEE, 2018.
|
[895]
|
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, and C. Lee
Giles.
Learning to extract semantic structure from documents using
multimodal fully convolutional neural network, 2017.
[ arXiv ]
|
[896]
|
Muhammad Zeshan Afzal, Andreas Kolsch, Sheraz Ahmed, and Marcus Liwicki.
Cutting the error by half: Investigation of very deep cnn and
advanced training strategies for document image classification.
2017 14th IAPR International Conference on Document Analysis and
Recognition (ICDAR), Nov 2017.
[ DOI |
http ]
|
[897]
|
Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, and Ming Zhou.
Layoutlm: Pre-training of text and layout for document image
understanding.
Proceedings of the 26th ACM SIGKDD International Conference on
Knowledge Discovery & Data Mining, Aug 2020.
[ DOI |
http ]
|