Three Laws

Carroll on Rules of Engagement: Copyright and Automated Gatekeepers @SHULawReview @AUWCL @MikeCarroll_US

Michael W. Carroll, American University College of Law, has published Rules of Engagement: Copyright and Automated Gatekeepers’ Influence on Creative Expression at 52 Seton Hall Law Review 1137 (2022). Here is the abstract.

This Essay turns questions about artificial intelligence and copyright law around. Rather than focus on algorithms as potential authors, this Essay argues for more attention to the role of algorithms as gatekeepers on social media and how creators adapt their creative choices to meet the demands of these automated tastemakers. Using TikTok’s “For You” algorithm and its role in breaking Lil Nas X’s hit song “Old Town Road” as a case study, this Essay poses the question whether algorithmic gatekeeping is simply a difference in degree or a difference in kind from an artist’s perspective. While tentative, this Essay concludes that this change is a difference in kind because of the rule-bound nature of software, the absence of transparency and accountability for algorithmic decisionmaking, and the flawed data models that inform this form of cultural gatekeeping.

Download the essay from SSRN at the link.

Davis on Robolawyers and Robojudges @usflaw @HastingsLJ

Joshua P. Davis, University of San Francisco School of Law, is publishing Of Robolawyers and Robojudges in the Hastings Law Journal (2022). Here is the abstract.

Artificial intelligence (AI) may someday play various roles in litigation, particularly complex litigation. It may be able to provide strategic advice, advocate through legal briefs and in court, help judges assess class action settlements, and propose or impose compromises. It may even write judicial opinions and decide cases. For it to perform those litigation tasks, however, would require two breakthroughs: one involving a form of instrumental reasoning that we might loosely call common sense or more precisely call abduction and the other involving a form of reasoning that we will label purposive, that is, the formation of ends or objectives. This Article predicts that AI will likely make strides at abductive reasoning but not at purposive reasoning. If those predictions prove accurate, it contends, AI will be able to perform sophisticated tasks usually reserved for lawyers, but it should not be trusted to perform similar tasks reserved for judges. In short, we might welcome a role for robolawyers but resist the rise of robojudges.

Download the article from SSRN at the link.

de la Feria and Grau Ruiz on The Robotisation of Tax Administration @delaFeriaR

Rita de la Feria, University of Leeds, and Maria Amparo Grau Ruiz, Completense University of Madrid, are publishing The Robotisation of Tax Administration as Chapter 20 of Interactive Robotics: Legal, Ethical, Social and Economic Aspects (A. Grau, ed., Springer Nature, 2022). Here is the abstract.

Developments over the last decade in the use of AI in tax administration have been nothing short of outstanding. Not only are taxpayers increasingly making use of automated systems in tax compliance, but perhaps more importantly, tax enforcement is increasingly reliant on new technologies as compliance-enhancing and fraud-prevention tools. However, whilst the use of AI brings very significant advantages to both the efficiency and the equity of tax systems, it also carries important risks. This paper identifies the development of a new AI fallacy within the tax policy sphere, namely that of unconstrained success: that the use of AI in tax compliance and enforcement can compensate for the deficiencies of the tax law. This paper considers the rationale behind the development of this fallacy, in particular the political and institutional dynamics involved in the approval of new tax legislation. It concludes that, maximising the benefits of the use of AI in tax compliance and enforcement requires departure from this fallacy, and the recognition of the wider dynamics of the tax policy-administration symbiosis.

Download the chapter from SSRN at the link.

Joh on Reckless Automation in Policing @elizabeth_joh @UCDavisLaw @BerkeleyTechLJ

Elizabeth E. Joh, University of California, Davis, School of Law, is publishing Reckless Automation in Policing at Berkeley Technology Law Journal Online (2022). Here is the abstract.

Automated decision-making plays an increasingly larger role in policing. Traditional methods of police investigation have been augmented by tools like facial recognition, predictive analytics, license plate readers, and robotics. How should we evaluate the growth of automation in policing? There is no shortage of answers, but this essay starts with a simple observation: by focusing on automation’s harms to persons first. American policing is rife with reckless automation. If we accept the premise of reckless automation, the conversation about accountability, artificial intelligence, and policing might benefit from a seemingly unrelated policy framework: that of experimentation on human subjects. Borrowing from that framework does not imply that reckless automation in policing is the literal equivalent of medical or psychological experiments on human subjects. Nor does such a comparison imply that the technical aspects of institutional review boards should apply directly to new policing strategies. But turning to a bioethical framework has value because it draws attention to the subjects - the communities affected - of policing. To the extent that the ethical considerations applied in human subjects research provide useful insights to apply to the many changes in policing, they open a new conversation. What if we think of new forms of automated decision-making in policing as experiments on communities that might impose harms with life-altering decisions?

Download the article from SSRN at the link.