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How Does AI Affect Your Online Shopping?
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<blockquote data-quote="Umbran" data-source="post: 9832309" data-attributes="member: 177"><p>It... <em>doesn't</em>? </p><p></p><p>By all means, then - try to practice it without the years of specialized education and training required. What could possibly go wrong?</p><p></p><p>Wait... People die and you go to jail? You get sued into oblivion by former patients you harmed? Gee, I guess it was a specialized field after all!</p><p></p><p></p><p></p><p></p><p></p><p>There are some technical and legal issues here - and while there's an adage that all problems can be solved with sufficient code, since the purveyors of AI have been resisting regulation, the trust we can give them with things like HIPAA concerns is questionable.</p><p></p><p>After all, we are talking about systems that are typically trained on data that was taken without permission. Not exactly a strong ethical ground upon which to base a trust relationship with supposedly private health data.</p><p></p><p>But, the biggest issue that pops to mind is one that has plagued genAI - the fact that it does not present facts, or answers. It presents things that <em>look like</em> facts and answers, and that need significant oversight and editing to get right. If the AI hallucinates something into, or out of that summary, someone's health and life can be at stake.</p><p></p><p></p><p></p><p>Generative AI doing transcription of phone messages can't seem to get "euthanasia" right most of the time. See previous issues of trust and hallucination risk, which apply here as well.</p><p></p><p>The study you cited included measures of quality, which is good. However, I would be wary of the issues that genAI systems typically run into when they attempt to handle technical information: When you focus on task completion, they look like they produce a savings. When you look at overall workflow, with the AI task integrated into the rest of work done, those savings are overcome by post AI corrections.</p></blockquote><p></p>
[QUOTE="Umbran, post: 9832309, member: 177"] It... [I]doesn't[/I]? By all means, then - try to practice it without the years of specialized education and training required. What could possibly go wrong? Wait... People die and you go to jail? You get sued into oblivion by former patients you harmed? Gee, I guess it was a specialized field after all! There are some technical and legal issues here - and while there's an adage that all problems can be solved with sufficient code, since the purveyors of AI have been resisting regulation, the trust we can give them with things like HIPAA concerns is questionable. After all, we are talking about systems that are typically trained on data that was taken without permission. Not exactly a strong ethical ground upon which to base a trust relationship with supposedly private health data. But, the biggest issue that pops to mind is one that has plagued genAI - the fact that it does not present facts, or answers. It presents things that [I]look like[/I] facts and answers, and that need significant oversight and editing to get right. If the AI hallucinates something into, or out of that summary, someone's health and life can be at stake. Generative AI doing transcription of phone messages can't seem to get "euthanasia" right most of the time. See previous issues of trust and hallucination risk, which apply here as well. The study you cited included measures of quality, which is good. However, I would be wary of the issues that genAI systems typically run into when they attempt to handle technical information: When you focus on task completion, they look like they produce a savings. When you look at overall workflow, with the AI task integrated into the rest of work done, those savings are overcome by post AI corrections. [/QUOTE]
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