{"id":11808,"date":"2022-06-29T11:26:00","date_gmt":"2022-06-29T11:26:00","guid":{"rendered":"http:\/\/TheNextWeb=1388816"},"modified":"2022-06-29T11:26:00","modified_gmt":"2022-06-29T11:26:00","slug":"ai-models-can-sound-human-but-that-doesnt-mean-they-feel-or-think","status":"publish","type":"post","link":"https:\/\/www.londonchiropracter.com\/?p=11808","title":{"rendered":"AI models can \u2018sound\u2019 human, but that doesn\u2019t mean they feel or think"},"content":{"rendered":"\n

When you read a sentence like this one, your past experience tells you that it\u2019s written by a thinking, feeling human. And, in this case, there is indeed a human typing these words: [Hi, there!] But these days, some sentences that appear remarkably humanlike are actually generated by artificial intelligence systems trained on massive amounts of human text.<\/p>\n

People are so accustomed to assuming that fluent language comes from a thinking, feeling human that evidence to the contrary can be difficult to wrap your head around. How are people likely to navigate this relatively uncharted territory? Because of a persistent tendency to associate fluent expression with fluent thought, it is natural \u2013 but potentially misleading \u2013 to think that if an AI model can express itself fluently, that means it thinks and feels just like humans do.<\/p>\n

Thus, it is perhaps unsurprising that a former Google engineer recently claimed that Google\u2019s AI system LaMDA has a sense of self because it can eloquently generate text about its purported feelings. This event and the subsequent media coverage<\/a> led to a number<\/a> of rightly skeptical articles<\/a> and posts<\/a> about the claim that computational models of human language are sentient, meaning capable of thinking and feeling and experiencing.<\/p>\n

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Greetings, humanoids<\/h2>\n

Subscribe to our newsletter now for a weekly recap of our favorite AI stories in your inbox.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

The question of what it would mean for an AI model to be sentient is complicated (see, for instance, our colleague\u2019s take<\/a>), and our goal here is not to settle it. But as language<\/a> researchers<\/a>, we can use our work in cognitive science and linguistics to explain why it is all too easy for humans to fall into the cognitive trap of thinking that an entity that can use language fluently is sentient, conscious or intelligent.<\/p>\n

Using AI to generate humanlike language<\/h2>\n

Text generated by models like Google\u2019s LaMDA can be hard to distinguish from text written by humans. This impressive achievement is a result of a decadeslong program to build models that generate grammatical, meaningful language.<\/p>\n

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