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Expanding the AI & Law Matrix

As I plan and prepare for the Third Annual AI & Law Workshop, scheduled for April 19-20 here at Vanderbilt Law School (details to follow), I thought back to last year’s workshop and my 2×2 matrix of the AI & Law space. I broke it down based on the “AI for Law” and “Law for AI” distinction on one axis and the “Theory and Research” and “Practice and Experience” split on the other. In retrospect, after a year of editing the SSRN Law eJournal on Artificial Intelligence – Law, Policy, and Ethics, I have unpacked it to more fully represent the breadth and depth of the AI & Law world. Here’s my shot at it, with examples of the content and types of questions that fit in each box:

THE AI and LAW MATRIX AI for Lawyers

 Applications of AI within legal practice

AI for Legal Administration

Applications of AI in the work of courts and agencies

Law for AI

 Legal regimes governing the use and impacts of AI

AI for Law for AI

 Employing AI to implement Law for AI regimes


How do we conceptualize AI in this space?

When is AI “practicing law”? Can AI “judge”?


Can AI design standards better than agencies?

Does machine learning “discriminate” within the meaning constitutional and civil rights laws? Can AI make AI obey the law?

What are the moral implications and ethical duties?

What duties do lawyers have when incorporating (or not) AI in practice? Is it ethically sound to turn over decisions such as bail and agency enforcement to AI? How transparent should government be when it uses AI to monitor? Is it morally acceptable to turn regulation of AI over to AI

What are the societal goals and tradeoffs?

What level of AI knowledge should lawyers be required to have? Do we want to promote or contain AI in criminal law administration—e.g., setting bail? What concerns are there regarding using AI to develop “threat scores” and “citizen scores”? Who decides what AI applications to regulate with other AI?

How do we design legal instruments and institutions?

Who is liable for AI’s role in malpractice? How will machine learning be admitted as evidence in the court room—under Daubert or a new standard? Is a government produced “citizen score” an invasion of privacy? A violation of due process? Of equal protection? How could we design mandatory AI monitoring and reporting of use of AI in private employment decisions?

What are the practical implications?

How will lawyers actually use and evaluate others’ use of AI? How will we deal with different levels of access to AI by parties? Do agencies have the capacity to design and administer regulatory AI? How will AI be deployed on top of AI as a technical matter?

What is the track record?

How far have smart contracts gained traction in commercial transactions? Is there evidence that use of AI in probation is more or less discriminatory than human judges acting alone? Have anti-discrimination laws been effective in regulating uses of AI in housing, lending, and other private decisions Is there evidence from AI development that the “black box” of machine learning can be “interrogated”?

I plan to float this at the workshop and again at our Summit on Law & Innovation, which my colleagues Larry Bridgesmith and Cat Moon are organizing for April 30, and I  also welcome comments.



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