In an essay published in The Verge, Benjamin Riley argues that today's AI boom is built on a fundamental misunderstanding: language modeling is not the same as intelligence. "The problem is that according to current neuroscience, human thinking is largely independent of human language -- and we have little reason to believe ever more sophisticated modeling of language will create a form of intelligence that meets or surpasses our own," writes Riley. Slashdot reader RossCWilliams shares the report, writing: The article goes on to point out that we use language to communicate. We use it to create metaphors to describe our reasoning. That people who have lost their language ability can still show reasoning. That human beings create knowledge when they become dissatisfied with the current metaphor. Einstein's theory of relativity was not based on scientific research. He developed it as thought experiment because he was dissatisfied with the existing metaphor. It quotes someone who said, "common sense is a collection of dead metaphors." And that AI, at best, can rearrange those dead metaphors in interesting ways. But it will never be dissatisfied with the data it has or an existing metaphor.
A different critique (PDF) has pointed out that even as a language model AI is flawed by its reliance on the internet. The languages used on the internet are unrepresentative of the languages in the world. And other languages contain unique descriptions/metaphors that are not found on the internet. My metaphor for what was discussed was the descriptions of the kinds of snow that exist in Inuit languages that describe qualities nowhere found in European languages. If those metaphors aren't found on the internet, AI will never be able create them.
This does not mean that AI isn't useful. But it is not remotely human intelligence. That is just a poor metaphor. We need a better one. Benjamin Riley is the founder of Cognitive Resonance, a new venture to improve understanding of human cognition and generative AI.
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