Generative AI in the Real World: Learning How to Do AI Effectively with Alfred Spector
What does successful AI development require? Where are the skills gaps?
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Alfred Spector has been a leader in AI and machine learning at Google, IBM, and Two Sigma. He is now a visiting scholar at MIT, an advisor at Blackstone, and coauthor of the text book Data Science in Context. Alfred talks with Ben Lorica about what people developing with AI need to be successful. Succeeding with AI is about more than just a model. We need to think about the application and its context. We need humanities and social sciences in addition to technology.
Check out other episodes of this podcast or the full-length version on the O’Reilly learning platform.
About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.
Timestamps
- 0:00: Intro
- 0:23: Why did you end up writing the book Data Science in Context?
- 1:55: Data science is about more than the model. More than “just get some data, build a model, and hope for the best.”
- 3:42: It’s easy to gloss over the system’s objectives.
- 4:36: We have to design systems knowing that they will fail on occasion.
- 5:00: We have to think about long-term societal impacts.
- 5:27: We need to think about the application, the application’s context, and the society.
- 6:38: Ethics alone isn’t enough.
- 7:15: We have to attend to all the technical issues. We have to do this truthfully.
- 9:22: We need to think about rights and wrongs. Students need a good basis in economics, political science, history, and literature.
- 11:42: We have to think more broadly than “which ad gets the most clicks.”