Gaumann, N., & Veale, M. R. (2024). AI providers as criminal essay mills? Large language models meet contract cheating law. Information & Communications Technology Law. https://doi.org/10.1080/13600834.2024.2352692
Gorwa, R., & Veale, M. (2024). Moderating Model Marketplaces: Platform Governance Puzzles for AI Intermediaries. Law, Innovation and Technology, 16(2). https://doi.org/10.31235/osf.io/6dfk3
Terzis, P., Veale, M., & Gaumann, N. (2024). Law and the Emerging Political Economy of Algorithmic Audits. In Proceedings of the 2024 ACM Conference on Fairness, Accountability and Transparency (FAccT '24) ACM.
Veale, M. (2024). Denied by Design? Data Access Rights in Encrypted Infrastructures. In J. Ausloos, & S. P. de Souza (Eds.), Research Access to Digital Infrastructures Cambridge University Press. https://doi.org/10.31235/osf.io/94y6r
Veale, M. (2024). Privacy, Informational Infrastructures and Covid-19: Comparative Legal Responses. In J. King, & O. Luiz Motta Ferraz (Eds.), Comparing Covid Laws: A Critical Global Survey OUP. https://doi.org/10.31219/osf.io/ht7a4
Veale, M. (2024). Rights for Those Who Unwillingly, Unknowingly and Unidentifiably Compute! In H-W. Micklitz, & G. Vettori (Eds.), The Person and the Future of Private Law Hart. https://doi.org/10.31235/osf.io/4ugxd
Veale, M. (2024). Some Commonly-Held but Shaky Assumptions about Data, Privacy and Power. In M. Ioannidou, & D. Mantzari (Eds.), Research Handbook on Competition Law and Data Privacy Edward Elgar. https://doi.org/10.31235/osf.io/z8tw6
Veale, M. (2024). Verification Theatre at Borders and in Pockets. In C. M. Flood, Y. Y. B. Chen, R. Deonandan, S. Halabi, & S. Thériault (Eds.), Pandemics, Public Health, and the Regulation of Borders: Lessons from COVID-19 Routledge. https://doi.org/10.31235/osf.io/h24uv
Veale, M., Silberman, M. S., & Binns, R. (2023). Fortifying the Algorithmic Management Provisions in the Proposed Platform Work Directive. European Labour Law Journal, 14(2), 308-332. https://doi.org/10.1177/20319525231167983
2022
Matus, K., & Veale, M. (2022). Certification Systems for Machine Learning: Lessons from Sustainability. Regulation and Governance, 16(1), 177-196. https://doi.org/10.1111/rego.12417
Troncoso, C., Bogdanov, D., Bugnion, E., Chatel, S., Cremers, C., Gürses, S., Hubaux, J. P., Jackson, D., Larus, J. R., Lueks, W., Oliveira, R., Payer, M., Preneel, B., Pyrgelis, A., Salathé, M., Stadler, T., & Veale, M. (2022). Deploying Decentralized, Privacy-Preserving Proximity Tracing. Communications of the ACM, 65(9), 48-57. https://doi.org/10.1145/3524107
Veale, M., & Zuiderveen Borgesius, F. (2022). Adtech and Real-Time Bidding under European Data Protection Law. German law journal: review of developments in German, European and international jurisprudence, 23(2), 226-256. https://doi.org/10.1017/glj.2022.18
Veale, M., Binns, R., & Ausloos, J. (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.
Veale, M., Nouwens, M., & Santos, C. (2022). Impossible Asks: Can the Transparency and Consent Framework Ever Authorise Real-Time Bidding After the Belgian DPA Decision? Technology and Regulation, 2022, 12-22. https://doi.org/10.26116/techreg.2022.002
Yaghini, M., Kulynych, B., Cherubin, G., Veale, M., & Troncoso, C. (2022). Disparate Vulnerability to Membership Inference Attacks. Proceedings on Privacy Enhancing Technologies. https://doi.org/10.2478/popets-2022-0023
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, 11(4), 319-332. https://doi.org/10.1093/idpl/ipab020
King, J., Ferraz, O., Achiume, T., Bogg, A., Byrom, N., Costello, C., Countouris, N., Flood, C., Pils, E., Steytler, N., Suteu, S., Thomas, B., Veale, M., & Villarreal, P. A. (Eds.) (2021). Oxford Compendium of National Legal Responses to Covid-19. Oxford University Press. https://oxcon.ouplaw.com/home/occ19
Lueks, W., Gürses, S., Veale, M., Bugnion, E., Salathé, M., Paterson, K. G., & Troncoso, C. (2021). CrowdNotifier: Decentralized Privacy-Preserving Presence Tracing. Proceedings on Privacy Enhancing Technologies, 2021(4), 350-368. https://doi.org/10.2478/popets-2021-0074
Marsden, C. T., Brown, I., & Veale, M. (2021). Responding to Disinformation: Ten Recommendations for Regulatory Action and Forbearance. In M. Moore, & D. Tambini (Eds.), Regulating Big Tech: Policy Responses to Digital Dominance (pp. 195-220). Oxford University Press. https://doi.org/10.1093/oso/9780197616093.003.0012
Milan, S., Veale, M., Taylor, L., & Gürses, S. (2021). Promises Made to Be Broken: Performance and Performativity in Digital Vaccine and Immunity Certification. European Journal of Risk Regulation, 12(2), 382-392. https://doi.org/10.1017/err.2021.26[details]
Veale, M., & Zuiderveen Borgesius, F. (2021). Demystifying the Draft EU Artificial Intelligence Act. Computer Law Review International, 22(4), 97-112. https://doi.org/10.9785/cri-2021-220402
Delacroix, S., & Veale, M. (2020). Smart Technologies and Our Sense of Self: Going Beyond Epistemic Counter-Profiling. In M. Hildebrandt, & K. O'Hara (Eds.), Life and the Law in the Era of Data-Driven Agency (pp. 80-99). Edward Elgar. https://doi.org/10.4337/9781788972000
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 ACM. https://doi.org/10.1145/3313831.3376321
Troncoso, C., Payer, M., Hubaux, J-P., Salathé, M., Larus, J. R., Lueks, W., Stadler, T., Pyrgelis, A., Antonioli, D., Barman, L., Chatel, S., Paterson, K. G., Capkun, S., Basin, D. A., Beutel, J., Jackson, D., Roeschlin, M., Leu, P., Preneel, B., ... Pereira, J. (2020). Decentralized Privacy-Preserving Proximity Tracing. IEEE Data Engineering Bulletin, 43(2), 36-66. http://sites.computer.org/debull/A20june/p36.pdf
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). https://doi.org/10.1017/err.2019.65
Ausloos, J., Veale, M., & Mahieu, R. (2019). Getting Data Subject Rights Right: A submission to the European Data Protection Board from international data rights academics, to inform regulatory guidance. Journal of Intellectual Property, Information Technology and Electronic Commerce Law, 10(3), 283-309. https://www.jipitec.eu/issues/jipitec-10-3-2019/5031[details]
Gross, T., Inkpen, K., Lim, B. Y., & Veale, M. (2019). The Human(s) in the Loop—Bringing AI and HCI Together. In D. Lamas, F. Loizides, L. Nacke, H. Petrie, M. Winckler, & P. Zaphiris (Eds.), Human-Computer Interaction – INTERACT 2019 - 17th IFIP TC 13 International Conference, Proceedings (pp. 731-734). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11749 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-29390-1_71
Inkpen, K., Veale, M., Chancellor, S., De Choudhury, M., & Baumer, E. P. S. (2019). Where is the human? Bridging the gap between AI and HCI. In CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems Article 3299002 (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3290607.3299002
Veale, M., & Brass, I. (2019). Administration by Algorithm? Public Management meets Public Sector Machine Learning. In K. Yeung, & M. Lodge (Eds.), Algorithmic Regulation Oxford University Press. https://doi.org/10.1093/oso/9780198838494.001.0001
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 CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems Article 377 ACM. https://doi.org/10.1145/3173574.3173951
Edwards, L., & Veale, M. (2018). Enslaving the Algorithm: From a "Right to an Explanation" to a "Right to Better Decisions"? IEEE Security & Privacy, 16(3), 46-54. https://doi.org/10.1109/MSP.2018.2701152
Mavroudis, V., & Veale, M. (2018). Eavesdropping Whilst You’re Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces. In Living in the Internet of Things: Cybersecurity of the IoT - 2018: 28-29 March 2018 IEEE. https://doi.org/10.1049/cp.2018.0018
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), 398-404. https://doi.org/10.1016/j.clsr.2017.12.002
Veale, M., Binns, R., & Ausloos, J. (2018). When data protection by design and data subject rights clash. International Data Privacy Law, 8(2), 105-123. https://doi.org/10.1093/idpl/ipy002
Veale, M., Binns, R., & Edwards, L. (2018). Algorithms that remember: model inversion attacks and data protection law. Philosophical Transactions of the Royal Society A - Mathematical, Physical and Engineering Sciences, 376(2133). https://doi.org/10.1098/rsta.2018.0083
Veale, M., Van Kleek, M., & Binns, R. (2018). Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making. In CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems Article 440 ACM. https://doi.org/10.1145/3173574.3174014
2017
Binns, R., Veale, M., Van Kleek, M., & Shadbolt, N. (2017). Like Trainer, Like Bot? Inheritance of Bias in Algorithmic Content Moderation. In G. L. Ciampaglia, A. Mashhadi, & T. Yasseri (Eds.), Social Informatics : 9th International Conference, SocInfo 2017, Oxford, UK, September 13-15, 2017 : proceedings (Vol. 2, pp. 405-415). (Lecture Notes in Computer Science; Vol. 10540). Springer. https://doi.org/10.48550/arXiv.1707.01477, https://doi.org/10.1007/978-3-319-67256-4_32
Veale, M., & Binns, R. (2017). Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data. Big Data & Society, 4(2). https://doi.org/10.1177/2053951717743530
2015
Veale, M., & Seixas, R. (2015). Moving to metrics: Opportunities and challenges of performance-based sustainability standards. SAPIENS, 8(1). https://journals.openedition.org/sapiens/1713
2023
Cobbe, J., Veale, M., & Singh, J. (2023). Understanding accountability in algorithmic supply chains. In FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency ACM. https://doi.org/10.1145/3593013.3594073
Naudts, L., Sax, M., Helberger, N., & Veale, M. (2024). Toward Constructive Optimisation: A new perspective on the regulation of recommender systems and the rights of users and society. In N. Helberger, B. Kas, H.-W. Micklitz, M. Namysłowska, L. Naudts, P. Rott, & M. Veale (Eds.), Digital Fairness for Consumers (pp. 25-68). BEUC (The European Consumer Organisation). https://www.beuc.eu/sites/default/files/publications/BEUC-X-2024-032_Digital_fairness_for_consumers_Report.pdf
Veale, M. (2022). Schools must resist big EdTech – but it won’t be easy. In S. Livingstone, & K. Pothong (Eds.), Education Data Futures: Critical, Regulatory and Practical Reflections (pp. 67-78). 5Rights Foundation.
Brown, I., Marsden, C. T., Lee, J., & Veale, M. (2020). Cybersecurity for Elections: A Commonwealth Guide on Best Practice. Commonwealth Secretariat. https://doi.org/10.31228/osf.io/tsdfb
Kilbertus, N., Gascon, A., Kusner, M., Veale, M., Gummadi, K., & Weller, A. (2018). Blind Justice: Fairness with Encrypted Sensitive Attributes: The 35th International Conference on Machine Learning (ICML 2018). 2635-2644. http://proceedings.mlr.press/v80/kilbertus18a.html
Spreker
Ausloos, J. (speaker), Toh, J. (speaker), Veale, M. (speaker), González Fuster, G. (speaker) & Ekker, A. (speaker) (9-6-2022). Fight the Power! Data Rights and Social Justice in the Platform Economy, Re:Publica, Berlin.
2019
Veale, M. (2019). Governing Machine Learning that Matters. [Thesis, fully external, UCL (University College London)].
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