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Can sci-fi films teach us anything about an AI threat?

1 点作者 otoolep将近 2 年前

2 条评论

ggm将近 2 年前
Yes, because they teach us what we&#x27;re expected to <i>believe</i> are the tropes about risk, and societal understanding of AI and risk.<p>Can war films teach us anything about war?<p>Can courtroom dramas teach us anything about the law?<p>Can watching roadrunner cartoons teach us about buying goods from the ACME corp?<p>Several authors have tried to modify the detective genre by inclusion of the mobile phone. They have to resort to Deus ex Machina outcomes like &quot;oh no the battery&#x27;s dead&quot; or &quot;damn, I&#x27;m out of range&quot; because in most normal situations, phoning it in, does in fact short circuit the problem of partial knowledge and keeping others informed.<p>Likewise DNA testing. It both raises and dashes hopes of how to &quot;prove crime&quot; because the probative value of DNA evidence is contextual. When 90%+ of violent crime happens from within the family, what does it help, to show DNA evidence associates the family members?<p>&quot;I&#x27;m sorry Dave, I can&#x27;t do that&quot; at least was partially informed by Minsky but thats almost laughable as a statement of &quot;AI informed from movies informed from AI research&quot;<p>the androids of Bladerunner had interior desires. The androids of Aliens.. it&#x27;s more circumspect. The robots of Bicentennial and AI Artificial Intelligence are entirely about the search for &quot;personhood&quot; in an autonomous, artificial person. I argue that the narratives inherent in a story which is designed to beg the question cannot really answer the question, because it&#x27;s presumed as an axiom: If the robots were not already autonomously independently conscious, then their desire is not comprehensible.<p>About one thing, I think we can be confident: the bootup power sequence for the first autonomous rubbish robot better be the &quot;Mac&quot; chimes or Pixar is dead to me.
ftxbro将近 2 年前
yes because these films will constitute a small part of the self-image of the multimodal LLMs that have trained on them