Register now. You can register for one or more Fast Forward sessions or for the entire conference series (with a corresponding discount and bonuses). The choice is up to you. If one of the dates doesn’t work, you can access the recorded session for 30 days (just not for CLE credit) – one advantage over an in-person conference.
12:00-1:00 pm ET
Hot, But Cool: The Latest AI and Robotics Developments
Learn about new cases, statutes, and regulations in AI and robotics since the ABA’s inaugural National Institute in January 2020. This panel will provide a snapshot overview of legal developments with rapid-fire summaries and actionable pointers on managing AI and robotics compliance and liability risks.
Stephen S. Wu, Partner, Silicon Valley Law Group; Past Chair, ABA Science & Technology Law Section [Moderator]
Colleen Chien, Professor of Law, Santa Clara University Law School
Preston Thomas, Privacy and Compliance Counsel, Dialpad, Inc.
1:15-2:15 pm ET
Contagion: Battling COVID-19 and Future Pandemics with AI and Robotics
COVID-19 has eclipsed the once-sunny national and world economy. At the same time, the U.S. healthcare system is under unprecedented strain, as it struggles to provide enough hospital beds and breathing apparatuses for patients and personal protective equipment for healthcare workers. How can AI help to track, diagnose, and treat COVID-19? Can telepresence robots facilitate treatment and minimize healthcare workers’ exposure to affected patients? This panel will discuss the technology and resulting legal issues of using AI and robotics to battle COVID-19 and future pandemics.
Heather B. Deixler, Counsel, Latham & Watkins LLP [Moderator]
John Byrnes, Principal Computer Scientist, Advanced Analytics Group, SRI International
Derek Forman, Founder/Chairman, ClearFocus Innovations
Mark Hanson, CEO, Decoded Health, Inc.
2:30-3:30 pm ET
Systematic Bias: AI as Cause and Cure
The new national dialogue on race relations following George Floyd’s death has sparked new dialogue about bias in artificial intelligence systems. Hiring, lending, and housing systems might discriminate because of the design of AI systems or the data used to create them, but they also hold the promise of decreasing bias. Media and legal journal articles have identified bias as a risk, but specific methods of mitigating bias are in short supply. This program goes beyond issue-spotting to provide actionable advice on mitigating bias in developing and operating AI systems. The panel also will cover methods to avoid discriminatory practices by companies operating robots, such as security and service robots.
Natalie A. Pierce, Partner and Chair, Labor and Employment Practice, Gunderson Dettmer [Moderator]
Jeffrey Brown, Diversity and Inclusion Research Fellow, Partnership on AI; Assistant Professor of Psychology, Minnesota State University, Mankato
Raluca Crisan, Co-Founder, etiq.ai; Director of Data Science, Merkle | Aquila
Travis LeBlanc, Member, U.S. Privacy and Civil Liberties Oversight Board; Partner, Cooley, LLP