How We've Moved on From Good Old Fashioned AI

According to today’s guest, the human mind is both genius and pathetic, brilliant and idiotic. As a species, we have learned to control fire, established democratic institutions, walked on the moon, and sequenced our genome. Our societies and technologies are extremely complex, but most of us do not really know how a pen or a toilet works. How have we achieved so much despite understanding so little? 

In his book, The Knowledge Illusion, cognitive scientist Steven Sloman points out that the key to our intelligence lies in the people and things around us. We’re constantly drawing on information and expertise stored outside our heads: our environment and the community with which we interact—without realizing it.

In this episode, Steven and Greg unpack how collaborative minds enable humans to do amazing things. Join us as we learn why and how our true genius can be found in the ways we create intelligence using our communities.

Episode Quotes:

How did cognitive science change over the years, especially the theories about the brain being like a computer?

So, you're absolutely right that cognitive science originated with the idea that the mind was effectively a computer. What's often called a von Neumann computer or a Turing machine type computer. One that processes information serially, one step at a time, in the way that most modern computers do. And I think that that view has largely been abandoned for multiple reasons. One of them is that it turns out that you can show that the brain doesn't operate in that serial fashion, but rather operates through massive parallel processing. The best models of memory and reasoning and perception, and problem-solving all have this character — that rather than processing information step-by-step — what people seem to do is to take huge amounts of information and figure out how they constrain the solution that we're looking for.

Why do people often need stories or narratives to make sense of causal mechanisms?

I mean, if you're telling a story, you're generally describing a chronology of events. But you're doing so by having a bunch of characters, and those characters have motivations, right? What are motivations? They're causes of behavior, and the characters take actions in order to change the world in some way that has consequences. And the consequence is a causal effect. So, narratives are very human, understandable ways to understand the causal processes that govern the world.

How humans depend on each other to understand the environment around them

What has really changed my world and my understanding of thought is this observation: that we don't think inside our skull, but rather we depend on other people to think, that we live in a community of knowledge. And the mind really exists in that community. So, the reason I think we experienced this knowledge illusion, this sense that we understand things better than we do, is because other people understand things. And we inherit the knowledge that's sitting in other people's heads. And as we go through life, we're constantly making use of other people's knowledge without being aware that we're doing so.

Do you think companies in Silicon Valley are starting to lean towards people with generalist knowledge when hiring?

One thing we discussed in the book is, some venture capital firms that aren't willing to fund ideas. But rather, they fund teams because they know that it's the quality of the team that matters. And there are people in business schools who are studying this. There's a fair amount of evidence now that if you want to predict the effectiveness of a team, you just can't do it by looking at the horsepower of the individuals, right? The IQ of the individuals is just not a good predictor of how well the team's going to do. But things, like how often they take conversational turns, turns out to be a better predictor.

Time Code Guide:

00:01:52 Is the intention to write a book that tackles cognitive science, anthropology and as a response to those, who are perplexed with how people think?

00:03:48 The illusion of explanatory depth by Leon Rosenfeld and Frank Kyle

00:05:27 Applying the illusion of explanatory depth in political contexts

00:06:59 When interviewing people, did you find personality differences? Are there people 

more willing to acknowledge or learn the limits of their knowledge than the others?

00:08:41 Correlation of preference of chocolate with instant and delayed gratification

00:12:57 How do the heuristics in computer and processing unlocking new ways of doing things?

00:15:03 Causal reasoning in contrast to computational view

00:20:21 Why certain types of narrative archetypes do a better job of leaving an impact compared to other kinds of stories?

00:22:10 Current innovation in machine learning and cognitive science

00:26:29 Our very limited capacity to process information that’s out there

00:29:24 Understanding the demand for specialists and the role of generalists

00:35:26 Intentionality and animals working towards common goals as a unit

00:37:28 Do the lack of proximity during the pandemic impair our ability to infer intentionality?

00:38:34 To what extent is wisdom of the crowd susceptible to lack of sensible and critical thinking?

00:41:31 Relying on experts and the possible problems of doing this

00:43:30 What are the key skills that people should have, given we rely so much on the knowledge generated by others and on technology to do most of the memory storage and processing for us?

00:47:11 Do you see your career as an embodiment of this jigsaw theory of knowledge?

Show Links:

Guest Profile

• Faculty Profile at Brown University
• Researcher Profile at Brown University
• Speaker Profile at the RSA Org

His Work

• Articles and Citation on Google Scholar
• The Knowledge Illusion: Why We Never Think Alone
• Causal Models: How People Think About the World and Its Alternatives
• Similarity and Symbols in Human Thinking (Cognition Special Issue)

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