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AI Mistakes Are Very Different from Human Mistakes
- AI systems and humans make different types of mistakes, with AI errors seeming much more random, without clustering around particular topics.
- Indeed, AI mistakes are frequently accompanied by a level of confidence that can be difficult to ignore, regardless of how obviously incorrect a statement seems to humans.
- AI’s random and inconsistent inconsistency makes trusting reasoning in complex and multi step problems almost impossible.
- One area of research for addressing the issues posed by AI is to engineer models for language that more closely resemble human responses.
- The other area involves creating new systems specifically for correcting the sorts of mistakes that AI models tend to make.
- The strange inconsistency of AI necessitates systems such as asking the same question repeatedly in slightly different ways and then combining responses.
- In some cases, what's bizarre about LLMs is that they act more like humans than we think they should.
- AI systems that make consistently random and unpredictable errors, like LLMs, should perhaps be confined to applications that play to their strengths or are more trivial.
- The need for new security systems to address the challenges posed by AI is arguing for an urgent rethink in this area.
- Researchers are still struggling to understand where LLM mistakes diverge from human ones.
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