Anthropomorphizing intelligence and asking whether a system 'understands' is unnecessary, inappropriate, and a distraction — what matters is whether the predictive system is safely embedded in a larger engineering ecosystem, not whether anyone can peer inside it.
Jordan argues that demanding AI 'understand' things (as with AlphaFold or Amazon's supply-chain models) is a category error; what's needed instead is engineering context — inputs, outputs, and constraints — not interpretability of an internal 'understanding'. ✦ AI generated
Michael I. Jordan · Machine Learning Street Talk · 2026-05-20 · original ↗
starts at this moment · 22:55
“Why why should AlphaFold understand?”
You cannot there's no way that any human can understand what's happening in that big big box. Um but it's not necessary. And in fact you can ask does that overall system understand you know transport and logistics and the answer is who cares. It does a very important optimization and prediction process that allows an engineering system to be built around it.
verbatim transcript · starts at 22:55
22:35kind of created. It's refined. There's this recycle pathway. You can put the thing through multiple times. you can kind of corrupt it halfway through and the network is just iteratively kind of you know it solves the complex bit first and then it's refining refining refining and like could we interpret that as an understanding process >> I don't think we need to see I think this anthropomorphizing of intelligence
22:55and understanding all that is not necessary not appropriate and is is a distraction for many many problems why say it understands you know some of my heritage comes from seeing in in real life in in industrial settings machine learning algorithms being rolled out 20 30 years ago so When I first went to the west coast, I visited Amazon in around 2000. They were using huge amounts of
23:16data to do supply chain modeling using the neural networks of the day. It was random forests and it was really working. They could make really fantastic predictions of you know whether certain ships would be delayed in the Indian Ocean or whatever and so certain parts wouldn't arrive in time and the overall supply chain takes billions of products and sends it to 100 millions of people per day. And so you
23:35cannot there's no way that any human can understand what's happening in that big big u box. Um but it's not necessary. Uh and in fact you can ask does that overall system understand you know transport and logistics and the answer is who cares. It's it's it does a a very important optimization and and prediction process that allows an engineering system to be built around it. It brings down uncertainty. It makes
24:03you possible to do kind of stockpiling and you know planning and that's what you ask for. You don't care whether it's uh has to have a word like understand it or intelligence applied to it. That's for the media. The media that's that's kind of my problem with a lot of these people rolling out AGI and and AI terminology. The media laps it up and they know that even though we don't have
24:23a clue what understanding intelligence mean and we we in our own research realize we don't care or need it. We want to build good systems. >> Yeah. It's interesting because I agree that we live in this complex adaptive irreducible system. we can't essententralize it and uh folks like France or even David Krakow they talk about intelligence as the you know adaptation synthesis of course grain representations but what if there is a
24:46bit of a step so let's not anthropomor anthropomorphize it let's say that understanding is about like not not the end point it's about the path which led us there and we know that in the real world we're a collective intelligence and there's the blind men and the elephant and we all take our own paths and lives and we we have different perspectives on the same hole so what if