Day: July 1, 2022

Shope on NGO Engagement in the Age of Artificial Intelligence

Mark Shope (National Yang Ming Chiao Tung University; Indiana University Robert H. McKinney School of Law) has posted “NGO Engagement in the Age of Artificial Intelligence” (Buffalo Human Rights Law Review, Vol. 28, pp. 119-158, 2022) on SSRN. Here is the abstract:

From AI and human rights focused NGOs to thematic NGOs whose subjects are impacted by AI, the AI and human rights discourse within NGOs has moved from simply keeping an eye on AI to being an integral part of NGO work. At the same time, the issue of AI and human rights is being addressed by governments in their policymaking and rulemaking to, for example, protect human rights and remain compliant with their responsibilities under international human rights instruments. When governments are reporting to United Nations treaty bodies as required under international human rights instruments, and the reports and communications include topics of artificial intelligence, how and to what extent are NGOs engaging in this dialogue? This article explores how artificial intelligence can impact rights under the nine core human rights instruments and how NGOs should monitor States parties under these instruments, providing suggestions to guide NGO engagement in the reporting process.

Li on Affinity-Based Algorithmic Pricing: A Dilemma for EU Data Protection Law

Zihao Li (University of Glasgow) has posted “Affinity-Based Algorithmic Pricing: A Dilemma for EU Data Protection Law” (Computer Law & Security Review, Volume 46, 2022) on SSRN. Here is the abstract:

The emergence of big data and machine learning has allowed sellers and online platforms to tailor pricing for customers in real-time, but as many legal scholars have pointed out, personalised pricing poses a threat to the fundamental values of privacy and non-discrimination, raising legal and ethical concerns. However, most of those studies neglect affinity-based algorithmic pricing, which may bypass the General Data Protection Regulation (GDPR). This paper evaluates current data protection law in Europe against online algorithmic pricing. The first contribution of the paper is to introduce and clarify the term “online algorithmic pricing” in the context of data protection legal studies, as well as a new taxonomy of online algorithmic pricing by processing the data types. In doing so, the paper finds that the legal nature of affinity data is hard to classify as personal data. Therefore, affinity-based algorithmic pricing is highly likely to circumvent the GDPR. The second contribution of the paper is that it points out that even though some types of online algorithmic pricing can be covered by the GDPR, the data rights provided by the GDPR struggle to provide substantial help. The key finding of this paper is that the GDPR fails to apply to affinity-based algorithmic pricing, but the latter still can lead to privacy invasion. Therefore, four potential resolutions are raised, relating to group privacy, the remit of data protection law, the ex-ante measures in data protection, and a more comprehensive regulatory approach.

Schrepel & Goroza on The Adoption of Computational Antitrust by Agencies: 2021 Report

Thibault Schrepel (University Paris 1 Panthéon-Sorbonne; VU University Amsterdam; Stanford University’s Codex Center; Sciences Po) and Teodora Groza (Sciences Po Law School) have posted “The Adoption of Computational Antitrust by Agencies: 2021 Report” (2 Stanford Computational Antitrust, 78 (2022)) on SSRN. Here is the abstract:

In the first quarter of 2022, the Stanford Computational Antitrust project team invited the partnering antitrust agencies to share their advances in implementing computational tools. Here are the results of the survey.