493. What Human-Centered AI Looks Like with Alex ‘Sandy’ Pentland

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Dec 20, 2024

In this engaging discussion, Alex ‘Sandy’ Pentland, a renowned fellow at Stanford’s Human Centered AI Institute and a pioneer in social physics, delves into the reshaping of social dynamics by AI. He explores the need for knowledge-sharing in organizations and how AI can bridge knowledge silos. Sandy also addresses the complex relationship between social media and community, urging for accountability among influencers. With insights on balancing curiosity and productivity, he emphasizes the critical role of human connection in an increasingly digital world.

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INSIGHT

Social Physics Evolution

Social physics, coined in the early 1800s, originally focused on demographics like population counts and mortality rates.
Today, it studies how human relationships and behaviors can be leveraged for societal and organizational design.

INSIGHT

Limitations of Brownian Motion

Traditional finance models, like Brownian motion, often fail to capture the true dynamics of markets and human behavior.
This can have severe consequences like the 2008 crash, highlighting the importance of more accurate physics-like models for financial decision-making.

INSIGHT

Idea Diffusion Complexity

Simply increasing idea diffusion isn't always beneficial; factors like limited human cognition and received wisdom can hinder optimal decision-making.
People tend to stick to a few familiar strategies, limiting their consideration of all available options, and can get trapped in bubbles or panics.

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How is artificial intelligence reshaping social dynamics, knowledge sharing, and the workplace in the digital age?

Alex “Sandy” Pentland is a fellow at Stanford University’s Human Centered AI Institute and helped create the MIT Media Lab. He’s the author of numerous books including, Honest Signals: How They Shape Our World, Social Physics: How Social Networks Can Make Us Smarter, and most recently, The Digitalist Papers: Artificial Intelligence and Democracy in America.

Sandy and Greg discuss the evolution of social physics and computational social science, the importance of knowledge sharing in the age of AI, and AI’s implications on connectivity and curiosity.

*unSILOed Podcast is produced by University FM.*

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Human Centered AI Institute at Stanford University

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What impedes the transmission of good ideas from one part of the organization to the other?

13:34: Organizations are always, today, siloed, and they're siloed for a variety of reasons. One is that we're not so smart. We can only understand a certain amount really well, and when it gets more complex than that, we go create another silo. We break it apart and create another silo, and people don't like to share things out of their silo because that means they're not valuable anymore. You like to control the staff and believe that your expertise is valuable. And if someone comes and says, "Well, give me all your data," that's like, "Hey, we're going to fire you in a month," right? People don't like to do that. And the data that they have is not contextualized, right? It means something to them, but somebody else looking at it will say, "Well, I don't know, it's a bunch of ones and zeros. What does that mean?" Right? You need to know what it's measuring and why. The intention is usually not in the data; it's in the context around it.

Does the rise of new AI tools stimulate curiosity or potentially dampen it?

59:34: The phenomenon of people not meeting other humans because they're all on social media is real and disturbing, and AI can make it worse. That's not quite the same thing as being curious. They are curious, just about things that are not actually in their physical environment or likely to affect them in that sort of immediate way.

Why smaller teams move faster and learn better

44:52: The smaller teams are necessary to move fast. If you have a big team, it's really hard to get everybody educated and on the same page. But with software and the sort of things that they do, you can do it with small teams. And so, you can have small teams, which means you can get consensus about what to do pretty fast. And, of course, the connections to everybody else mean you can look for opportunities and learn from other people much better than other people. So, it's a win-win thing. You get people that are able to put things out there quicker; they're able to learn from all the other people that have done it better. And it works pretty well.