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Episode #19

The Turing Test is not Intelligent (and what it would take for AI to understand)

Epsiode featuring Lisa Titus, Professor of Philosophy at the ⁠University of Denver⁠. If I look inside your head when you’re talking, I’ll see various neurons lighting up, probably in the prefrontal cortex as you engage in the reasoning that’s necessary to say whatever it is you’re saying. But if I opened your head and instead found a record playing and no brain, I’d realize I was dealing with a puppet, not a person with a brain/intellect.

In both cases you’re saying the same things (let’s suppose). But because of what’s going on in the head, or “under the hood,” it’s clear there’s intelligence in the first case and not in the second.

Does an LLM (large language model like GPT or Bard) have intelligence. Well, to know that we need to look under the hood, as Lisa Titus argues. It’s not impossible that AI could be intelligent, she says, but judging by what’s going on under the hood at the moment, it’s not.

Fascinating discussion about the nature of intelligence, why we attribute it to each other (mostly) and why we shouldn’t attribute it to AI.

Lisa Titus (née Lisa Miracchi) is a tenured Associate Professor of Philosophy at the ⁠University of Denver⁠.
Previously, she was a tenured Associate Professor of Philosophy at the ⁠University of Pennsylvania⁠, where she was also a General Robotics, Automation, Sensing, and Perception (⁠GRASP⁠) Lab affiliate and a ⁠MindCORE⁠ affiliate.

She works on issues regarding mind and intelligence. What makes intelligent systems different from other kinds of systems? What kinds of explanations of intelligent systems are possible, or most important? What are appropriate conceptions of real-world intelligent capacities like those for agency, knowledge, and rationality? How can conceptual clarity on these issues advance cognitive science and aid in the effective and ethical development and application of AI and robotic systems? Her work draws together diverse literatures in the cognitive sciences, AI, robotics, epistemology, ethics, law, and policy to systematically address these questions.