Blue Cross of California Distinguished Associate Professor
Ziad trained as an emergency doctor – and he still gets away as often as he can to work in the ER. But these days, Ziad spends most of his time doing research and teaching, at UC Berkeley. Inspired by his clinical work, he builds machine learning algorithms that help doctors make better decisions. He also studies where algorithms can go wrong – how they can scale up racial bias – and how to fix them. He has received numerous awards (from the National Academy of Medicine, the NIH, professional societies in medicine and economics). His work has been highly influential, and is frequently cited in the public debate about algorithms, as well as federal and state regulatory guidance and civil investigations.
It’s widely agreed that automated decisions generated using AI should be underpinned by ethics and responsible good practice. It’s also a strongly held view that decisions should yield ‘good’...
- Melissa McSherry - SVP Global Head of Data, Security, and Identity Products - VISA
- Ziad Obermeyer - Blue Cross of California Distinguished Associate Professor - UC Berkeley
- Ashleigh Ainsley - Co-Founder - Colorintech
- Mark Durkee - Head of Tech, Assurance & Good Practice - Centre for Data Ethics and Innovation
- Ivana Bartoletti - Director, Deloitte and Visiting Policy Fellow, University of Oxford - Deloitte (Moderator)