Claude Steele is a professor of psychology at Stanford University and the author of the landmark book, Whistling Vivaldi: How Stereotypes Affect Us and What We Can Do. His new book, Churn: The Tension That Divides Us and How to Overcome It, takes the theories from Whistling Vivaldi and examines the psychological stress that comes with navigating diversity.

Claude joins Greg to discuss his decades' worth of research on the concept of identity, the impacts stereotypes have on our cognitive load, even if we don’t subscribe to those stereotypes, the limits to “colorblindness”s, the concept of “wiseness,” and why trust could be the antidote to the churn.

*unSILOed Podcast is produced by University FM.*

The tension beneath how we come together

08:39: I'm trying to characterize, with the term “churn,” this sort of emotion that can be a real factor in our experience of diversity and our coming together. We're a multiracial, multi-ethnic, multi-religious, multi-class society. And to function well, we have to get along well in these critical situations—school, workplace—and churn is a symptom of the tensions that can arise.

Trust is the antidote of churn

10:10: The hopeful part of churn is that it does have a remedy, an antidote, and that is trust. As soon as we've built trust together, then I relax. Well, I know you're not going to do that.

How do you build trust?

29:13: You really do have to try to get yourself in the position of the other, to see the world from the other person's shoes. That really helps to build trust. Just the effort that you're interested in doing that is maybe the most fundamental step forward that a person in authority can take to build trust in people that work for them or work with them.

The limits of being colorblind

19:48: I think in many aspects of our society, it's absolutely essential. We have to think that way, that we have to have policing, healthcare access, housing, mortgages be colorblind. So, I'm uncompromising on many aspects of it, but I think if we take it too far, we can ignore the experiences that people have because of their identities. Yeah, just because of their identity. So, if we're colorblind, I don't need to know about all those things that affect your life that have to do with your identity.

Recommended Resources:

• Erving Goffman
• Affirmative action
• “Differences in STEM doctoral publication by ethnicity, gender and academic field at a large public research university” by Mendoza-Denton and Fisher

Guest Profile:

• Faculty Profile at Stanford University
• Former Provost Bio at UC Berkeley

Guest Work:

• Churn: The Tension That Divides Us and How to Overcome It
• Whistling Vivaldi: How Stereotypes Affect Us and What We Can Do

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When AI tells us what we want to hear, is it acting in a rogue way, or is it emulating behavior that society clearly values? How does our ability to sleep enable us to update faster than neural networks currently can, and what will be different when they can update themselves more frequently?

Christopher Summerfield is a professor of cognitive neuroscience at Oxford University, the Research Director at the UK’s AI Safety Institute, and the author of the book These Strange New Minds: How AI Learned to Talk and What It Means.

Christopher and Greg discuss the historical split between symbolic, rule-based “rationalist” AI and data-driven “empiricist” learning, arguing that the recent success of large models vindicates the latter despite earlier skepticism. They discuss how structured behavior can emerge from messy networks, how modern models are trained with reinforcement learning to produce step-by-step reasoning, and why systems often “make” solutions by writing code rather than routing to specialized tools.

*unSILOed Podcast is produced by University FM.*

From messy brains to intelligent machines

04:40: If you look inside the brain, your brain and mine and the brains of other biological species, they're really messy. They're like really, really messy and unstructured. So nature managed to solve the problem. And so maybe that gave impetus for this movement to kind of, you know, continue to sort of plug away. And when we finally got computers big enough to process lots and lots of data, it started to take off. And the rest is history.

Hallucinations aren’t just an AI problem

34:36: How does the model know what is the kind of socially or culturally appropriate response?  We're often very worried about the models,  like, the models don't tell the truth and  they make stuff up.  But people forget that most of language is literally making stuff up. That is what you do when you open your mouth.

Is language more powerful than we thought?

32:05: The surprising thing is that language, it turns out, is sufficiently rich and expressive that if you have it in huge volumes and you process it effectively, then you can actually make a whole bunch of inferences about the world, which are surprisingly accurate. So you would think that you would need to actually experience them firsthand rather than just through hearsay, because we work like that, right? Like we rely on our senses. Of course, we rely on hearsay a little bit, and we think about what other people say, and it allows us to infer new things. But like the models just have language, well, I mean now they have multimodal data, but let's take a conversational agents lms, and what I think has been so surprising is that language contains enough structure that you can really uncover patterns of information that you would think that you would need to see.

Recommended Resources:

• Rationalism
• Empiric School
• George Bull
• Frank Rosenblatt
• Neural Network (machine learning)
• Marvin Minsky
• Perceptron
• GPTs

Guest Profile:

• Human Information Processing Lab
• Social Profile on X

Guest Work:

• These Strange New Minds: How AI Learned to Talk and What It Means
• Google Scholar Page

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.