Our guest today is Dr. Gillian Hadfield from the Schwartz Reisman Institute for Technology and Society, who is here to bring her extensive experience and acute insight to issues around AI governance, regulation, and the challenge of alignment. The conversation covers the difference between AI justifiability and explainability, and how to build the legal and economic environment for AI that builds value.
A broad thinker from an unusual background, Dr. Gillian Hadfield shares a different take on building these models from the general norm, as well as how to incorporate transparency into justifiable systems, and the hypothesis of building a system where decisions are attached back to a person responsible. We also talk about the need for safe, consistent, and up-to-date regulatory structures, and the effects of not having this, before closing with some powerful advice around the work we have to do going forward in this sector! We hope you can join us for this hugely insightful conversation.
Key Points From This Episode:
Tweetables:
“There's no one solution to how you align AI.” — @ghadfield [0:10:19]
“We have the alignment problem everywhere. How do you get a corporation to do what you want it to do, how do you get governments to do what you want them to do?” — @ghadfield [0:23:52]
“AI is a general-purpose technology, it's a way of solving problems, it's a way of coming up with new ideas. It's going to be everywhere. I prefer to think of the regulatory challenge as, how is AI changing your capacity to achieve your regulatory goals, in any domain?” — @ghadfield [0:37:41]
“We need way more people who are not engineers, deeply engaged in the process of building our systems.” — @ghadfield [0:42:13]
Links Mentioned in Today’s Episode: