2018 BCLT AI Workshop

September  6 & 7, 2018
The Faculty Club
UC Berkeley
Minor Lane, Berkeley, CA

In the past few years, AI has become a highly visible and important sector of the software industry, having considerable commercial significance. AI’s rapid adoption in the public and private sectors (ranging from medical to military) has raised urgent legal and policy questions. This workshop will bring together legal academics and scholars from sociology, computer science, and the humanities researching the impacts of AI, AI specialists, and lawyers and policy experts from leading tech companies to address the overlaps of IP issues (e.g., who owns the outputs of AI systems) and issues of fairness, accountability, transparency, and interpretability, bias, accountability, and governance. One expected result of the workshop will be a short statement or paper by the organizers outlining areas of convergence in understanding the legal significance of AI advances, plus an agenda for further legal and policy research.

Resources

AI and Intellectual Property
• Colleen Chien, Can AI Fix patent Quality? (March 2018)
Robert Denicola, Ex Machina: Copyright Protection for Computer-Generated Works (2016)
• Jane Ginsburg and Luke Ali Budiardjo, Authors and Machines (2018)
• Matthias Leistner, Patents & AI in Germany and Europe – The Future is Now (2018)
• Summary of three categories of patent prosecution tools and company deep dives, prepared by Katharine Rubschlager, Andrew Parkhurst, and Elaine Chou (SCU law students)

Privacy, Fairness, Accountability
• Papers resulting from the June 2018 workshop of the Algorithmic Fairness and Opacity Working Group (AFOG) at UC Berkeley “Algorithms are Opaque and Unfair: Now What?” 

  1. What a technical ‘fix’ for fairness can and can’t accomplish 
  2. Automated decision-making is imperfect, but it’s arguably an improvement over biased human decision-making
  3. Human autonomy and empowerment
  4. From the black box society to the audit society— are algorithms auditable?

• Michael Hind et al., “Increasing Trust in AI Services through Supplier’s Declarations of Conformity”
(Aug 22, 2018)  (https://arxiv.org/abs/1808.07261). 

• See also https://www.ibm.com/blogs/research/2018/08/factsheets-ai/
and https://venturebeat.com/2018/08/22/ibm-ai-transparency-factsheets/

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