Not all AI is, well, AI

Marketplace Tech

American Public Media

Technology, News

4.6 • 1.2K Ratings

🗓️ 2 January 2025

⏱️ 12 minutes

🔗️ Recording | iTunes | RSS

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Summary

Artificial intelligence and promises about the tech are everywhere these days. But excitement about genuine advances can easily veer into hype, according to Arvind Narayanan, computer science professor at Princeton who along with PhD candidate Sayash Kapoor wrote the book “AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.” He says even the term AI doesn’t always mean what you think.

Transcript

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0:00.0	From all of us at Marketplace, we want to say happy new year and a special thank you to everybody who stepped up to donate and help us plan for the year ahead.
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0:18.3	Give now at Marketplace.org slash donate and thanks.
0:22.8	Can you tell AI snake oil when you see it? From American public media, this is Marketplace
0:29.3	Tech. I'm Megan McCarty Carrino. Artificial intelligence and promises about the tech are everywhere these days,
0:47.2	but excitement about genuine advances can easily veer into hype, according to Arvin Narayanan.
0:53.7	And he's a computer science professor at Princeton, who, along with PhD candidate Syash Kapoor,
1:00.2	wrote the book AI Snake Oil, What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference.
1:07.8	He says even the term, AI, doesn't always mean what you think.
1:12.6	AI is an umbrella term. It refers to a collection of loosely related technologies. So many
1:18.2	different products are called AI. In some ways, AI has certainly made remarkable progress.
1:23.6	But in other cases, what is being sold as AI, first of all, is a hundred-year-old statistics,
1:30.4	simple formulas that are being rebranded as AI.
1:33.3	But more importantly, it's being used in situations where we should not expect AI or any other
1:40.2	technology to work, like trying to predict a person's future. So in the criminal justice
1:45.6	system, AI is used to predict who might commit another crime if they are released before
1:52.7	their trial. And if they're deemed too risky because the algorithm predicts they might
1:57.5	commit another crime, then they're detained. And, you know, that could be
2:01.0	months or years until their trial. And that's just one example. It's used in the health system.
2:07.1	It's used in automated hiring. So in so many cases, these kinds of predictive technologies,
2:12.6	they can pick up some basic statistical patterns in the data. That's true, but they are not at the level of
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