Three Laws Blog: Law and Artificial Intelligence

Newly Published: Xavier Oberson, Taxing Robots (Elgar, 2019) @xavieroberson @ElgarPublishing

Newly published: Xavier Oberson, University of Geneva, Taxing Robots: Helping the Economy to Adapt to the Use of Artificial Intelligence (Elgar, 2019).

The increasing use of artificial intelligence within the workplace is likely to cause significant disruption to the labour market and in turn, to the economy, due to a reduction in the number of taxable workers. In this innovative book, Xavier Oberson proposes taxing robots as a possible solution to the anticipated problem of declining tax revenues.

Kim on Big Data and Artificial Intelligence @WUSTL

Pauline Kim, Washington University in St. Louis, School of Law, is publishing Big Data and Artificial Intelligence: New Challenges for Workplace Equality in the University of Louisville Law Review. Here is the abstract.

This essay contains remarks delivered in a keynote speech at the University of Louisville Brandeis School of Law’s 35th Annual Carl A. Warns and Edwin R. Render Labor and Employment Law Institute. Big data and artificial intelligence are increasingly being used by employers in their human resources processes in ways that control access to employment opportunities. This essay describes some of those developments and explains how practices like targeted online recruitment strategies and the use of hiring algorithms to screen applicants raise a significant risk of discriminating against protected groups such as women and racial minorities. It then considers some of the challenges these technologies pose for existing anti-discrimination law and suggests ways that the law should be interpreted to address these new threats to workplace equality.

Download the essay from SSRN at the link.

Jones and Levy on Sporting Chances: Robot Referees and the Automation of Enforcement @MegLeta

Meg Leta Jones, Georgetown University, Communication, Culture, and Technology, and Karen Levy, Cornell University, have published Sporting Chances: Robot Referees and the Automation of Enforcement, a paper presented at We Robot 2017. Here is the abstract.

This paper examines controversies about automated enforcement technologies in professional sports. Sports might seem like clear contexts for automating rule enforcement: rules are well-established, accuracy is ostensibly valued, human officials are known to be fallible, and “robot refs” are well within reach technologically. But in sports, automated officiating systems have faced strong resistance as substitutes for human judgment. We consider the reception of various types of automated officiating systems across four case studies (football, baseball, golf, and tennis) and describe reasons why each has faced hurdles to adoption, in favor of imperfect, human-dependent enforcement — what we term the “sporting chance.” The sporting chance is set forth in six sociocultural values of imperfect enforcement: drama, adversity, custom, integrity, humanity, and dignity. Consideration of these values in the sports context might fruitfully inform our understanding of public attitudes toward automation in other domains.

Download the article from SSRN at the link.

Hacker on Teaching Fairness to AI: Existing and Novel Strategies Against Algorithmic Discrimination Under EU Law

Philipp Hacker, Humboldt Univesrity of Berlin, WZB Berlin Social Science Center, is publishing Teaching Fairness to Artificial Intelligence: Existing and Novel Strategies Against Algorithmic Discrimination Under EU Law in the Common Market Law Review. Here is the abstract.

Empirical evidence is mounting that artificial intelligence applications driven by machine learning threaten to discriminate against legally protected groups. As ever more decisions are subjected to algorithmic processes, discrimination by algorithms is rightly recognized by policymakers around the world as a key challenge for contemporary societies. This article suggests that algorithmic bias raises intricate questions for EU law. The existing categories of EU anti-discrimination law do not provide an easy fit for algorithmic decision making, and the statistical basis of machine learning generally offers companies a fast-track to justification. Furthermore, victims won’t be able to prove their case without access to the data and the algorithms, which they generally lack. To remedy these problems, this article suggests an integrated vision of anti-discrimination and data protection law to enforce fairness in the digital age. More precisely, it shows how the concepts of anti-discrimination law may be combined with the enforcement tools of the GDPR to unlock the algorithmic black box. In doing so, the law should harness a growing literature in computer science on algorithmic fairness that seeks to ensure equal protection at the data and code level. The interplay of anti-discrimination law, data protection law and algorithmic fairness therefore facilitates “equal protection by design”. In the end, however, recourse to technology does not prevent the law from making hard normative choices about the implementation of formal or substantive concepts of equality. Understood in this way, the deployment of artificial intelligence not only raises novel risks, but also harbors novel opportunities for consciously designing fair market exchange.

Download the article from SSRN at the link.

McGaughey on Whether Robots Will Automate Your Job Away? @KCL_Law

Evan McGaughey, School of Law, King's College, London, Centre for Business Research, University of Cambridge.; University of California, Berkeley, Berkeley Comparative Equality & Anti-Discrimination Law Study Group, has published Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy as TLI Think! Paper 3/2018 and King's College London Law School Research Paper No. 2018-12. Here is the abstract. Note: There are 2 versions of this paper

Will the internet, robotics and artificial intelligence mean a ‘jobless future’? A recent narrative says tomorrow’s technology will fundamentally differ from cotton mills, steam engines, or washing machines. Automation will be less like post-WW2 demobilisation for soldiers, and more like the car for horses. Driverless vehicles will oust truckers and taxi drivers. Hyper-intelligent clouds will oust financial advisers, doctors, and journalists. We face more ‘natural’ or ‘technological’ unemployment than ever. Government, it is said, must enact a basic income, because so many jobs will vanish. Also, maybe robots should become ‘electronic persons’, the subjects of rights and duties, so they can be taxed. This narrative is endorsed by prominent tech-billionaires, but it is flawed. Everything depends on social policy. Instead of mass unemployment and a basic income, the law can achieve full employment and fair incomes. This article explains three views of the causes of unemployment: as ‘natural’, as stemming from irrationality or technology, or as caused by laws that let people restrict the supply of capital to the job market. Only the third view has any credible evidence to support it. After WW2, 42% of UK jobs were redundant (actually, not hypothetically) but social policy maintained full employment, and it can be done again. Unemployment is driven by inequality of wealth and of votes in the economy. Democratic governments should reprogramme the law: for full employment and universal fair incomes. The owners of the robots will not automate your job away, if we defend economic democracy.

Download the versions of this paper from SSRN at the link.

Will Robots Free Us From Work? @ConversationUK

Over at the Conversation, a short discussion of the possibility that robots (of any kind) will eventually mean we can all retire with fat pensions. I have to agree that I don't think Wall-E is in our futures, for a number of reasons, including that most people have to have a reason to get out of bed in the morning, and work is a good one. Additionally, people want to be remembered, and children aren't the only way to accomplish that. Obviously one could commit crimes in order to become famous, but that kind of activity has a severe downside. What most people want, I think, is to be immortal.  Our accomplishments in life are a means to make certain the next generation, and maybe the one after that one, remembers us.

Do Not Kick the Wal-Bot

Walmart is using robots to scan its shelves and help with inventory. According to this Wired article, it knows how to avoid bumping into customers and store displays. Some people like the robots, or think they're interesting (especially children). But some people dislike them immensely, even to the point of kicking them. Sounds like a bad idea. As reporter Matt Simon notes, we wouldn't want the bots to remember that behavior. After all, when robots achieve sentience, take over corporations, and start assigning us jobs, we want them to remember us as fondly as possible.

Segal on Legal Jobs in the Age of AI: Moving From Today's Limited Universe of Data Toward the Great Beyond @CGIntelligence @SavLawRev

Philip Segal, Charles Griffin Intelligence, LLC, is publishing Legal Jobs in the Age of Artificial Intelligence: Moving from Today's Limited Universe of Data Toward the Great Beyond in the Savannah Law Review (2018). Here is the abstract.

Lawyers are unprepared for the major differences between the closed or highly limited universes of data with which today’s most popular AI programs deal, and the vastly larger, unstructured field of data that the AI of tomorrow will attempt to conquer. In the space of unlimited data – at least on the fact gathering side – this article argues that there are dozens of AI applications currently in development that could help lawyers do their jobs better. The impact on legal employment from these unlimited-fact universe programs does not appear to be negative, for the simple reason that they represent a chance to look at data previously unexamined by lawyers. But, to be useful, these programs will demand skills and a job outlook not always in evidence among lawyers. Even today, software used in law firms is not employed to its full potential. Lawyers often miss the point that while computers work purely in a deductive way, higher human functioning is often not deductive at all. What kind of person does a firm want to have running all the sophisticated machinery? In brief, it may not be the ideal law student of today. The paper concludes with suggestions about how to train lawyers who will be using AI to use it wisely. Those expecting to type in a few queries and get a final correct answer will be sorely disappointed.

Download the article from SSRN at the link.

Petit on Antitrust and AI: A Research Agenda @CompetitionProf

Nicolas Petit, University of Liege, School of Law; International Center for Law & Economics; University of South Australia School of Law, hs published Antitrust and Artificial Intelligence - A Research Agenda. Here is the abstract.

This short paper provides an overview of the claims made in the emerging scholarship on artificial intelligence and antitrust policy. It discusses in particular the conjecture that markets will be rife with algorithmic collusion and extractive personalized pricing. It stresses the main methodological, theoretical and empirical limitations that underpin the claims made in the scholarship, and concludes with a call for evidenced-based antitrust policy.

Download the paper from SSRN at the link.

The AI/Artificial Intelligence For Good: AI's 21st Century Challenges

Catherine Saez of Intellectual Property Watch writes about the AI/Artificial Intelligence for Good Global Summit (June 7-9, 2017). She notes that among the issues discussed were the potential of AI to make decisions on its own, the new European Parliament resolution calling for consideration of legal and ethical implications of robotics, and the rapid expansion of tasks that AI does without human intervention.