Striving to come up with answers that please humans may make chatbots more likely to pull the wool over our eyes
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Giving AI chatbots human feedback on their responses seems to make them better at giving convincing, but wrong, answers.
The raw output of large language models (LLMs), which power chatbots like ChatGPT, often contains biased, harmful or irrelevant information, and their style of interaction can seem unnatural to humans. To get around this, developers often get people to evaluate a model’s responses and then fine-tune it based on this feedback.
