Last week, on April 27th and 28th, I attended Algorithms and Explanations, an interdisciplinary conference hosted by NYU Law School’s Information Law Institute. The thrust of the conference could be summarized as follows:
- Humans make decisions that affect the lives of other humans
- In a number of regulatory contexts, humans must explain decisions, e.g.
- Bail, parole, and sentencing decisions
- Approving a line of credit
- Increasingly, algorithms “make” decisions traditionally made by man, e.g.
- Risk models already used to make decisions regarding incarceration
- Algorithmically-determined default risks already used to make loans
- This poses serious questions for regulators in various domains:
- Can these algorithms offer explanations?
- What sorts of explanations can they offer?
- Do these explanations satisfy the requirements of the law?
- Can humans actually explain their decisions in the first place?
The conference was organized into 9 panels. Each featured between 3 and 5 20-minute talks followed by a moderated discussion and Q&A. The first panel, moderated by Helen Nissenbaum (NYU & Cornell Tech), featured legal scholars (including conference organizer Katherine Strandburg) and addressed the legal arguments for explanations in the first place. A second panel featured sociologists Duncan Watts (MSR) and Jenna Burrell (Berkeley) as well as Solon Borocas (MSR), an organizer of the Fairness, Accountability and Transparency in Machine Learning workshop.
Katherine Jo Strandburg, NYU Law professor and conference organizer