Browse by UCL people
Group by: Type | Date
Number of items: 74.
2026
|
Veale, Michael;
Quintais, João Pedro;
(2026)
The Obligations of Providers of General-Purpose AI Models.
In: Malgieri, Gianclaudio and González Fuster, Gloria and Mantelero, Alessandro and Zanfir-Fortuna, Gabriela, (eds.)
The EU Artificial Intelligence Act: A Thematic Commentary.
Hart: London, UK.
(In press).
|
2025
Naudts, Laurens;
Helberger, Natali;
Veale, Michael;
Sax, Marijn;
(2025)
A Right to Constructive Optimization: A Public Interest Approach to Recommender Systems in the Digital Services Act.
Journal of Consumer Policy
10.1007/s10603-025-09586-1.
(In press).
|
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Veale, M;
(2025)
Rights for those who Unwillingly, Unknowingly and Unidentifiably Compute!
In: Micklitz, Hans-W. and Vettori, Giuseppe, (eds.)
The Future of the Person.
(pp. 231-253).
Bloomsbury Publishing: London, UK.
|
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Veale, Michael;
(2025)
Some commonly held but shaky assumptions about data, privacy and power.
In: Ioannidou, Maria and Mantzari, D, (eds.)
Research Handbook on Data, Privacy and Competition Law.
(pp. 17-34).
Edward Elgar Publishing
|
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Veale, Michael;
(2025)
Rights for Those Who Unwillingly, Unknowingly and Unidentifiably Compute!
In: Micklitz, Hans-Wolfgang and Vettori, Giussepe, (eds.)
The Person and the Future of Private Law.
Bloomsbury Publishing
(In press).
|
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Veale, Michael;
(2025)
Denied by Design? Data Access Rights in Encrypted Infrastructures.
In: Ausloos, Jef and De Souza, Siddharth P, (eds.)
Research Access to Digital Infrastructures.
Cambridge University Press: Cambridge, UK.
(In press).
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Veale, Michael;
Black, Isra;
Dsouza, Mark;
Fisher, Matt;
Ghaus, Mujtaba;
Gibbs, Thea;
Lynskey, Orla;
... Trapp, Kimberley; + view all
(2025)
Artificial Intelligence, Education and Assessment at UCL Laws: Current Thinking and Next Steps for the UK Legal Education Sector.
(UCL Legal Studies Research Paper Series
04/2025).
UCL Faculty of Laws: London, UK.
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2024
|
Gaumann, Noëlle;
Veale, Michael;
(2024)
AI providers as criminal essay mills? Large language models meet contract cheating law.
Information and Communications Technology Law
10.1080/13600834.2024.2352692.
(In press).
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Gorwa, Robert;
Veale, Michael;
(2024)
Moderating model marketplaces: platform governance puzzles for AI intermediaries.
Law, Innovation and Technology
, 16
(2)
10.1080/17579961.2024.2388914.
|
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Helberger, Natali;
Kas, Betül;
Micklitz, Hans-Wolfgang;
Namysłowska, Monika;
Naudts, Laurens;
Rott, Peter;
Sax, Marijn;
+ view all
(2024)
Digital Fairness for Consumers.
BEUC, the European Consumer Organisation: Brussels, Belgien.
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Könighofer, Bettina;
Kroll, Joshua A;
Piskac, Ruzica;
Veale, Michael;
Cano Córdoba, Filip;
(2024)
Accountable Software Systems (Dagstuhl Seminar 23411).
Dagstuhl Reports
, 13
(10)
pp. 24-49.
10.4230/DagRep.13.10.24.
|
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Micklitz, Hans-Wolfgang;
Helberger, Natali;
Kas, Betül;
Namysłowska, Monika;
Naudts, Laurens;
Rott, Peter;
Sax, Marijn;
(2024)
Towards Digital Fairness.
Journal of European Consumer and Market Law
, 13
(1)
pp. 24-30.
|
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Naudts, Laurens;
Helberger, Natali;
Sax, Marijn;
Veale, Michael;
(2024)
Toward Constructive Optimisation: A new perspective on the regulation of recommender systems and the rights of users and society.
In: Helberger, Natali and Kas, Betül and Micklitz, Hans-Wolfgang and Namysłowska, Monika and Naudts, Laurens and Rott, Peter and Veale, Michael, (eds.)
Digital Fairness for Consumers.
(pp. 25-68).
European Consumer Organisation (BEUC): Brussels, Belgium.
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Terzis, Petros;
Veale, Michael;
Gaumann, Noëlle;
(2024)
Law and the Emerging Political Economy of Algorithmic Audits.
In:
Proceedings of the 2024 ACM Conference on Fairness, Accountability and Transparency.
ACM
(In press).
|
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Veale, Michael;
(2024)
Verification Theatre at Borders and in Pockets.
In: Flood, Colleen M and Chen, YY Brandon and Deonandan, Raywat and Halabi, Sam and Thériault, Sophie, (eds.)
Pandemics, Public Health, and the Regulation of Borders: Lessons from COVID-19.
(pp. 240-251).
Routledge: London, UK.
|
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Veale, Michael;
Matus, Kira;
Gorwa, Robert;
(2024)
人工智能与全球治理: 模式、理据和紧张关系.
俄罗斯学刊
, 2024
(3)
pp. 49-72.
|
 |
2023
|
Cobbe, Jennifer;
Veale, Michael;
Singh, Jatinder;
(2023)
Understanding accountability in algorithmic supply chains.
In:
Proceedings of FAccT '23: ACM Conference on Fairness, Accountability, and Transparency.
(pp. pp. 1186-1197).
ACM (Association for Computing Machinery): Chicago, IL, USA.
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Gaumann, Noëlle;
Veale, Michael;
(2023)
AI Providers as Criminal Essay Mills? Large Language Models meet Contract Cheating Law.
UCL Faculty of Laws: London, UK.
|
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Veale, Michael;
(2023)
Article 25: Logging.
In: Kosta, Eleni and Boehm, Franziska, (eds.)
The EU Law Enforcement Directive (LED): A Commentary.
Oxford University Press: Oxford, UK.
(In press).
|
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Veale, Michael;
(2023)
Privacy, Informational Infrastructures and Covid-19: Comparative Legal Responses.
Law Archive Papers: New Haven, CT, USA.
|
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Veale, Michael;
(2023)
Confidentiality Washing in Online Advertising.
In: Cath, Corinne, (ed.)
Eaten by the Internet.
(pp. 43-48).
Meatspace Press: Manchester, UK.
|
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Veale, Michael;
Matus, Kira;
Gorwa, Robert;
(2023)
AI and Global Governance: Modalities, Rationales, Tensions.
Annual Review of Law and Social Science
, 19
pp. 255-275.
10.1146/annurev-lawsocsci-020223-040749.
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Veale, Michael;
Silberman, M Six;
Binns, Reuben;
(2023)
Fortifying the Algorithmic Management Provisions in the Proposed Platform Work Directive.
European Labour Law Journal
, 14
(2)
pp. 308-332.
10.1177/20319525231167983.
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2022
|
Matus, Kira JM;
Veale, Michael;
(2022)
Certification Systems for Machine Learning: Lessons from Sustainability.
Regulation and Governance
, 16
(1)
pp. 177-196.
doi.org/10.1111/rego.12417.
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Pavel, Valentina;
Kind, Carly;
Strait, Andrew;
Reeve, Octavia;
Peppin, Aidan;
Szymielewicz, Katarzyna;
Veale, Michael;
+ view all
(2022)
Rethinking data and rebalancing digital power.
Ada Lovelace Institute: London, UK.
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Troncoso, Carmela;
Bogdanov, Dan;
Bugnion, Edouard;
Chatel, Sylvain;
Cremers, Cas;
Gürses, Seda;
Hubaux, Jean-Pierre;
... Veale, Michael; + view all
(2022)
Deploying decentralized, privacy-preserving proximity tracing.
Communications of the ACM
, 65
(9)
pp. 48-57.
10.1145/3524107.
|
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Veale, M;
Zuiderveen Borgesius, F;
(2022)
Adtech and Real-Time Bidding under European Data Protection Law.
German Law Journal
, 23
(2)
pp. 226-256.
10.1017/glj.2022.18.
|
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Veale, Michael;
(2022)
Schools must resist big EdTech – but it won’t be easy.
In: Livingstone, Sonia and Pothong, Krukae, (eds.)
Education Data Futures: Critical, Regulatory and Practical Reflections.
(pp. 67-78).
5Rights Foundation: London, UK.
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Veale, Michael;
(2022)
Adtech’s new clothes might redefine privacy more than they reform profiling.
[Digital scholarly resource].
https://netzpolitik.org/2022/future-of-online-adve...
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Veale, Michael;
(2022)
Die neuen Kleider der Werbe-Giganten.
[Digital scholarly resource].
https://netzpolitik.org/2022/zukunft-der-online-we...
|
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Veale, Michael;
Binns, Reuben;
Ausloos, Jef;
(2022)
设计数据保护与数据主体权利之间的冲突.
In:
设计隐私权研究——新信息性隐私权（三）.
(pp. 651-684).
Sun Yat-Sen University Press: Guangzhou.
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Veale, Michael;
Nouwens, Midas;
Santos, Cristiana;
(2022)
Impossible Asks: Can the Transparency and Consent Framework Ever Authorise Real-Time Bidding After the Belgian DPA Decision?
Technology and Regulation
, 2022
pp. 12-22.
10.26116/techreg.2022.002.
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Yaghini, M;
Kulynych, B;
Cherubin, G;
Veale, M;
Troncoso, C;
(2022)
Disparate Vulnerability to Membership Inference Attacks.
Proceedings on Privacy Enhancing Technologies
, 2022
(1)
pp. 460-480.
10.2478/popets-2022-0023.
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2021
|
Binns, R;
Veale, M;
(2021)
Is That Your Final Decision? Multi-Stage Profiling, Selective Effects, and Article 22 of the GDPR.
International Data Privacy Law
10.1093/idpl/ipab020.
(In press).
|
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Lueks, W;
Gürses, S;
Veale, M;
Bugnion, E;
Salathé, M;
Paterson, KG;
Troncoso, C;
(2021)
CrowdNotifier: Decentralized Privacy-Preserving Presence Tracing.
Proceedings on Privacy Enhancing Technologies
, 2021
(4)
pp. 350-368.
10.2478/popets-2021-0074.
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Marsden, CT;
Brown, I;
Veale, M;
(2021)
Responding to Disinformation: Ten Recommendations for Regulatory Action and Forbearance.
In: Moore, M and Tambini, D, (eds.)
Regulating Big Tech: Policy Responses to Digital Dominance.
(pp. 195-230).
Oxford University Press: Oxford, UK.
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Taylor, L;
Milan, S;
Veale, M;
Gürses, S;
(2021)
Promises made to be broken: Performance and performativity in digital vaccine and immunity certification.
European Journal of Risk Regulation
, 12
(2)
pp. 382-392.
10.1017/err.2021.26.
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Veale, M;
Borgesius, FZ;
(2021)
Demystifying the Draft EU Artificial Intelligence Act.
Computer Law Review International
, 22
(4)
pp. 97-112.
10.9785/cri-2021-220402.
|
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Veale, M;
Ausloos, J;
(2021)
Researching with Data Rights.
Technology and Regulation
pp. 136-157.
10.26116/techreg.2020.010.
|
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2020
|
Brown, I;
Marsden, CT;
Lee, J;
Veale, M;
(2020)
Cybersecurity for Elections: A Commonwealth Guide on Best Practice.
Commonwealth Secretariat: London, UK.
|
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Delacroix, S;
Veale, M;
(2020)
Smart Technologies and Our Sense of Self: Going Beyond Epistemic Counter-Profiling.
In: Hildebrandt, M and O'Hara, K, (eds.)
Life and the Law in the Era of Data-Driven Agency.
(pp. 80-99).
Edward Elgar: Cheltenham, UK.
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Nouwens, M;
Liccardi, I;
Veale, M;
Karger, D;
Kagal, L;
(2020)
Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence.
In:
CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems.
(pp. p. 194).
ACM
|
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Troncoso, C;
Payer, M;
Hubaux, J-P;
Salathé, M;
Larus, J;
Bugnion, E;
Lueks, W;
... Pereira, J; + view all
(2020)
Decentralized Privacy-Preserving Proximity Tracing.
ArXiv: Ithaca, NY, USA.
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Troncoso, C;
Payer, M;
Hubaux, J-P;
Salathé, M;
Larus, J;
Bugnion, E;
Lueks, W;
+ view all
(2020)
Decentralized Privacy-Preserving Proximity Tracing: Overview of Data Protection and Security.
(DP-3T Project
).
DP-3T Project: London, UK.
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Troncoso, C;
Payer, M;
Hubaux, J-P;
Salathé, M;
Larus, JR;
Lueks, W;
Stadler, T;
... Pereira, J; + view all
(2020)
Decentralized Privacy-Preserving Proximity Tracing.
IEEE Data Engineering Bulletin
, 43
(2)
pp. 36-66.
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Veale, M;
(2020)
Sovereignty, Privacy, and Contact Tracing Protocols.
In: Taylor, L and Sharma, G and Martin, AK and Jameson, SM, (eds.)
Data Justice and COVID-19: Global Perspectives.
(pp. 34-39).
Meatspace Press: London, UK.
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Veale, M;
(2020)
Privacy is not the problem with the Apple-Google contact-tracing toolkit.
The Guardian
|
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Veale, M;
(2020)
A Critical Take on the Policy Recommendations of the EU High-Level Expert Group on Artificial Intelligence.
European Journal of Risk Regulation
, 11
(1)
, Article e1. 10.1017/err.2019.65.
|
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Veale, M;
Brown, I;
(2020)
Cybersecurity.
Internet Policy Review
, 9
(4)
pp. 1-22.
10.14763/2020.4.1533.
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2019
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Ausloos, J;
Mahieu, R;
Veale, M;
(2019)
Getting Data Subject Rights Right: A submission to the European Data Protection Board from international data rights academics, to inform regulatory guidance.
JIPITEC – Journal of Intellectual Property, Information Technology and E-Commerce Law
, 10
(3)
pp. 283-309.
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Edwards, L;
Finck, M;
Veale, M;
Zingales, N;
(2019)
Data subjects as data controllers: a Fashion(able) concept?
[Digital scholarly resource].
https://policyreview.info/articles/news/data-subje...
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Gross, T;
Inkpen, K;
Lim, BY;
Veale, M;
(2019)
The Human(s) in the Loop—Bringing AI and HCI Together.
In: Panayiotis, Zaphiris and David, Lamas, (eds.)
Human-Computer Interaction – INTERACT 2019: 17th IFIP TC 13 International Conference, Paphos, Cyprus, September 2–6, 2019, Proceedings, Part IV.
Springer: Cham, Switzerland.
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Inkpen, K;
Veale, M;
Chancellor, S;
De Choudhury, M;
Baumer, EPS;
(2019)
Where is the human? Bridging the gap between AI and HCI.
In: Brewster, S and Fitzpatrick, G and Cox, A and Kostakos, V, (eds.)
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems.
Association for Computing Machinery (ACM): New York, NY, USA.
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Veale, M;
Brass, I;
(2019)
Administration by Algorithm? Public Management meets Public Sector Machine Learning.
In: Yeung, K and Lodge, M, (eds.)
Algorithmic Regulation.
(pp. 121-149).
Oxford University Press: Oxford, UK.
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Veale, M;
Delacroix, S;
Olhede, S;
Blacklaws, C;
Adams Bhatti, S;
(2019)
Algorithms in the Criminal Justice System.
(Technology and Law Public Policy Commission
).
The Law Society of England and Wales: London, UK.
|
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Veale, Michael;
(2019)
Governing Machine Learning that Matters.
Doctoral thesis (Ph.D), UCL (University College London).
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2018
|
Binns, R;
Van Kleek, M;
Veale, M;
Lyngs, U;
Zhao, J;
Shadbolt, N;
(2018)
'It's Reducing a Human Being to a Percentage'; Perceptions of Procedural Justice in Algorithmic Decisions.
In:
Proceedings of the CHI'18: ACM Conference on Human Factors in Computing Systems.
(pp. Paper No. 377).
Association for Computing Machinery (ACM): ACM New York, NY, USA.
|
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Edwards, L;
Veale, M;
(2018)
Enslaving the Algorithm: From a 'Right to an Explanation' to a 'Right to Better Decisions'?
IEEE Security and Privacy Magazine
, 16
(3)
pp. 46-54.
10.1109/MSP.2018.2701152.
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Kilbertus, N;
Gascon, A;
Kusner, M;
Veale, M;
Gummadi, K;
Weller, A;
(2018)
Blind Justice: Fairness with Encrypted Sensitive Attributes.
In: Dy, J and Krause, A, (eds.)
Proceedings of the 35th International Conference on Machine Learning.
(pp. pp. 2635-2644).
International Machine Learning Society (IMLS).: Stockholm, Sweden.
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Mavroudis, V;
Veale, M;
(2018)
Eavesdropping whilst you're shopping: Balancing personalisation and privacy in connected retail spaces.
In:
Proceedings of Living in the Internet of Things: Cybersecurity of the IoT - 2018.
IET: London, UK.
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Van Kleek, M;
Seymour, W;
Veale, M;
Binns, R;
Shadbolt, N;
(2018)
The Need for Sensemaking in Networked Privacy and Algorithmic Responsibility.
In:
Sensemaking in a Senseless World: Workshop at ACM CHI’18, 22 April 2018, Montréal, Canada.
Association for Computing Machinery (ACM)
(In press).
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Veale, M;
(2018)
Ignore Mark Zuckerberg: His promise that new EU data privacy guidelines will be “rolled out” to American users is misleading.
Slate
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Veale, M;
Binns, R;
Ausloos, J;
(2018)
When Data Protection by Design and Data Subject Rights Clash.
International Data Privacy Law
, 8
(2)
pp. 105-123.
10.1093/idpl/ipy002.
|
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Veale, M;
Binns, R;
Edwards, L;
(2018)
Algorithms that remember: model inversion attacks and data protection law.
Philosophical Transactions A: Mathematical, Physical and Engineering Sciences
, 376
(2133)
, Article 20180083. 10.1098/rsta.2018.0083.
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Veale, M;
Binns, R;
Van Kleek, M;
(2018)
Some HCI Priorities for GDPR-Compliant Machine Learning.
In:
The General Data Protection Regulation: An Opportunity for the CHI Community? (CHI-GDPR 2018), Workshop at ACM CHI’18, 22 April 2018, Montréal, Canada.
Association for Computing Machinery (ACM)
(In press).
|
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Veale, M;
Edwards, L;
(2018)
Clarity, Surprises, and Further Questions in the Article 29 Working Party Draft Guidance on Automated Decision-Making and Profiling.
Computer Law and Security Review
, 34
(2)
pp. 398-404.
10.1016/j.clsr.2017.12.002.
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Veale, M;
Edwards, L;
Eyers, D;
Henderson, T;
Millard, C;
Staudt Lerner, B;
(2018)
Automating Data Rights.
Dagstuhl Reports
, 8
(4)
pp. 126-163.
10.4230/DagRep.8.4.126.
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Veale, M;
Van Kleek, M;
Binns, R;
(2018)
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making.
In:
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems.
(pp. paper no. 440).
ACM: Montréal, QC, Canada.
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2017
|
Binns, R;
Veale, M;
Van Kleek, M;
Shadbolt, N;
(2017)
Like Trainer, Like Bot? Inheritance of Bias in Algorithmic Content Moderation.
In: Ciampaglia, GL and Mashhadi, A and Yasseri, T, (eds.)
Social Informatics. SocInfo 2017. Lecture Notes in Computer Science, Vol. 10540.
(pp. pp. 405-415).
Springer: Cham, Switzerland.
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Edwards, L;
Veale, M;
(2017)
Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for.
Duke Law & Technology Review
, 16
(1)
pp. 18-84.
|
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Veale, M;
(2017)
Data management and use: case studies of technologies and governance.
The British Academy; The Royal Society: London, UK.
|
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Veale, M;
(2017)
Logics and practices of transparency and opacity in real-world applications of public sector machine learning.
In:
Proceedings of the 4th Workshop on Fairness, Accountability and Transparency in Machine Learning, (FAT/ML 2017).
: Halifax, Canada.
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Veale, M;
Binns, R;
(2017)
Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data.
Big Data & Society
, 4
(2)
pp. 1-17.
10.1177/2053951717743530.
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2015
|
Veale, M;
Seixas, R;
(2015)
Moving to metrics: Opportunities and challenges of performance-based sustainability standards.
Sapiens
, 8
(1)
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