Keynote

Beyond models – Applying AI and data science effectively

By Alfred Spector

Visiting Scholar, MIT and Senior Advisor at Blackstone

Applying artificial intelligence and data science effectively requires a considerably broader focus than just data and machine learning. Based on the speaker and his co-authors’ recent book, Data Science in Context (and an associated MIT Course), this presentation distills these additional challenges into a rubric and illustrates its application with a number of examples.

Beyond the rubric, the presentation also presents useful frameworks for making the complex trade-offs that are present and growing. While the talk should have practical value to those applying and regulating AI and DS, it also illustrates contemporary research challenges.

Biography

Dr. Alfred Spector is a Visiting Scholar at MIT, and a Senior Advisor at Blackstone. His career has led him from innovation in large scale, networked computing systems to broad engineering and research leadership. He obtained a Ph.D. in computer science from Stanford and a B.A. in applied math from Harvard.

Recently, Dr. Spector co-authored a Cambridge University Press textbook, Data Science in Context: Foundations, Challenges, Opportunities.

Previously, Dr. Spector was CTO, and Head of Engineering at Two Sigma Investments. Before that, he spent eight years as VP of Research and Special Initiatives at Google, and he held various senior-level positions at IBM, including as global VP of Services and Software Research and global CTO of IBM’s Software Business.

Spector was a Hertz Fellow at Stanford and is also a Fellow of both the ACM, and the IEEE. He is a member of the National Academy of Engineering and the American Academy of Arts and Sciences