{"id":14870,"date":"2026-04-01T21:04:19","date_gmt":"2026-04-02T01:04:19","guid":{"rendered":"https:\/\/www.data-mania.com\/blog\/?p=14870"},"modified":"2026-04-01T21:04:19","modified_gmt":"2026-04-02T01:04:19","slug":"generative-ai-ethics-rlhf","status":"publish","type":"post","link":"https:\/\/www.data-mania.com\/blog\/generative-ai-ethics-rlhf\/","title":{"rendered":"Ugly Generative AI Ethics Concerns: RLHF Edition"},"content":{"rendered":"

In this post we’re looking at one of the biggest generative AI ethics concerns I\u2019ve uncovered in my recent research of large language models (LLMs), that of fairness implications involved in reinforcement learning with human feedback (RLHF).<\/p>\n

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But first, if you\u2019re completely new to the world of generative AI and LLMs, just know that one of the more fundamental aspects of working with them involves fine-tuning LLMs.<\/p>\n

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