Chatbots process enormous amounts of data and produce convincing outputs but, he says, they do not grasp the meaning of the concepts they manipulate.
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Humans are terrible at crunching data but remarkably good at seeing clues. That’s why we still outmatch our machines in domains where meaning matters.
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Users, whose output is used to train the AI systems, will pay higher electricity costs on account of them while experts eventually earn top salaries.
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It’s not impossible but, given technical issues and security protocols, it is much more difficult than the chatbot’s database seemed to be informed about.
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So CAN a chatbot really scheme? No, but the problem posed is a familiar one: We sometimes see what we need to believe.
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The researchers discovered a limitation when they tweaked some standard puzzlers and – never short of an answer – bots didn’t pick up on the change.
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Many Sci Foo attendees were excited by LLMs in education but I fear that — when the way they are used is considered — they will increase social inequality.
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Kobak et al. worry about LLMs’ tendency to make up references, provide inaccurate summaries and make false but convincing-sounding claims.
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A vast army of boosters is portraying chatbots as magic when their usefulness is limited by realities that are probably a hard limit.
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A recent article by James D. Walsh at New York magazine worries that AI is dooming education — such as it is these days. In January 2023, just two months after OpenAI launched ChatGPT, a survey of 1,000 college students found that nearly 90 percent of them had used the chatbot to help with homework assignments. In its first year of existence, ChatGPT’s total monthly visits steadily increased month-over-month until June, when schools let out for the summer. (That wasn’t an anomaly: Traffic dipped again over the summer in 2024.) Professors and teaching assistants increasingly found themselves staring at essays filled with clunky, robotic phrasing that, though grammatically flawless, didn’t sound quite like a college student — or even a Read More ›
The job market for recent college grads may be warning us that participation trophies for college and ChatGPT use have long-run costs.
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The gap between human and machine ways of knowing can be thought of as the correspondence horizon. When AI crosses that, it produces plausible bullshit.
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In short, philosophers distinguish between two fundamental theories of truth: correspondence and coherence, and AI does only coherence.
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It is increasingly recognized that, without extensive post-training, their authoritative answers are often remarkably bad.
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When using chatbots and other GenAI, keep the long-term goals of the developers in mind.
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Jeremy Utley uses unmistakably spiritual, almost salvation-like language: epiphanies, transformation. GenAI is a savior, and Utley is a prophet…
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Chatbots have been trained on such stories. People forget it’s just a machine and panic because they think of it as a person who really thinks things.
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Humans aren’t computers. We are persons, centers of consciousness, who have physical bodies and come from particular contexts.
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MIT’s Joseph Weizenbaum was only one of many pioneers but he saw how readily people came to depend on the bots as if they were real people.
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As people become attached to and dependent on their AI friends, they become less interested in their fellow humans.
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