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The conversations are from a time span of five months and include a rich diversity of 150 languages with 210K users along a wide range of topics. To analyze the data, the team used a sample size of 100,000 randomly sampled English conversations. The team found that while the majority of user prompts were related to coding and software, there was a significant number of unsafe topics.
The team noted that these unsafe conversations can serve as a rich resource for examining the safety issues of LLMs. They also noted that while they used OpenAI’s API to tag a conversation as unsafe, it had some limitations. The moderation API can accurately detect highly toxic content, but many potentially harmful conversations were not flagged.had reported earlier that Meta's open-sourced LLaMA is being used to build sexbots.
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