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Automated Driving and Other Failures of AI

How would autonomous cars manage in an environment where eye contact with other drivers is important?

Yesterday I posted a review here of philosopher and programmer Erik Larson’s The Myth of Artificial Intelligence. There’s a lot more I would like to say. Here are some additional notes, to which I will add in a couple of future posts. Three of the failures of Big Tech that I listed earlier (Eugene Goostman, Tay, and the image analyzer that Google lobotomized so that it could no longer detect gorillas, even mistakenly) were obvious frauds and/or blunders. Goostman was a fraud out of the box. Tay a blunder that might be fixed in the sense that its racist language could be mitigated through some appropriate machine learning. And the Google image analyzer — well that was just pathetic: either retire the image…

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Artificial Intelligence: Unseating the Inevitability Narrative

World-class chess, Go, and Jeopardy-playing programs are impressive, but they prove nothing about whether computers can be made to achieve AGI

Back in 1998, I moderated a discussion at which Ray Kurzweil gave listeners a preview of his then forthcoming book The Age of Spiritual Machines, in which he described how machines were poised to match and then exceed human cognition, a theme he doubled down on in subsequent books (such as The Singularity Is Near and How to Create a Mind). For Kurzweil, it is inevitable that machines will match and then exceed us: Moore’s Law guarantees that machines will attain the needed computational power to simulate our brains, after which the challenge will be for us to keep pace with machines..  Kurzweil’s respondents at the discussion were John Searle, Thomas Ray, and Michael Denton, and they were all to varying degrees critical of his strong…

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Why Do Some People Try To Poison Big Tech’s Data Well?

Some social media users confuse Big Tech about their interests so as to preserve privacy and rein in relentless marketing campaigns

Here’s an article on a theme you probably didn’t expect to read about in a top tier tech magazine: How to poison the data Big Tech collects about you. It’s certainly evidence of the growing discontent with Monopoly Power and Big Surveillance: Now researchers at Northwestern University are suggesting new ways to redress this power imbalance by treating our collective data as a bargaining chip. Tech giants may have fancy algorithms at their disposal, but they are meaningless without enough of the right data to train on. Karen Hao, “How to poison the data that Big Tech uses to surveil you” at Technology Review (March 5, 2021) Researchers Nicholas Vincent and Hanlin Li presented a paper at the recent Association…