#042 – Prof Pedro Domingos
Today we have professor Pedro Domingos and we are going to talk about activism in machine learning, AI ethics and kernels. In Pedro’s book the master algorithm, he segmented the AI community into 5 distinct tribes with 5 unique identities (and before you ask, no the irony of an anti-identitarian doing do was not lost on us!). Pedro recently published an article in Quillette called Beating Back Cancel Culture: A Case Study from the Field of Artificial Intelligence. Domingos has railed against political activism in the machine learning community and cancel culture. Recently Pedro was involved in a controversy where he asserted the NeurIPS broader impact statements are an ideological filter mechanism.
Important Disclaimer: All views expressed are personal opinions.
00:04:08 Main intro
00:07:44 Cancelling culture is a culture and intellectual weakness
00:24:46 Should we have gateways and gatekeepers?
00:29:30 Does everything require broader impact statements?
00:33:55 We are stifling diversity (of thought) not promoting it.
00:39:09 What is fair and how to do fair?
00:45:11 Models can introduce biases by compressing away minority data
00:48:36 Accurate but unequal soap dispensers
00:53:55 Agendas are not even self-consistent
00:56:42 Is vs Ought: all variables should be used for Is
01:00:38 Fighting back cancellation with cancellation?
01:10:01 Intent and degree matter in right vs wrong.
01:11:08 Limiting principles matter
01:15:10 Gradient descent and kernels
01:20:16 Training Journey matter more than Destination
01:24:36 Can training paths teach us about symmetry?
01:28:37 What is the most promising path to AGI?
01:31:29 Intelligence will lose its mystery
Pod version: https://anchor.fm/machinelearningstreettalk/episodes/042—Pedro-Domingos—Ethics-and-Cancel-Culture-eq864v
Yannic’s video on Kernel Paper;
“Every Model Learned by Gradient Descent Is Approximately a Kernel Machine”