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arXiv· arXiv:2302.07459· Deep Ganguli, Amanda Askell, Nicholas Schiefer, Thomas I. Liao, Kamilė Lukošiūtė, Anna Chen, Anna Goldie, Azalia Mirhoseini, Catherine Olsson, Danny Hernandez, Dawn Drain, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jackson Kernion, Jamie Kerr, Jared Mueller, Joshua Landau, Kamal Ndousse, Karina Nguyen, Liane Lovitt, Michael Sellitto, Nelson Elhage, Noemi Mercado, Nova DasSarma, Oliver Rausch, Robert Lasenby, Robin Larson, Sam Ringer, Sandipan Kundu, Saurav Kadavath, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, Christopher Olah, Jack Clark, Samuel R. Bowman, Jared Kaplan·本站收录· 原文发表

大语言模型的道德自我纠正能力

The Capacity for Moral Self-Correction in Large Language Models

AI 导读

研究者测试了经 RLHF 训练的大语言模型在被指示时能否进行道德自我纠正、避免产生有害输出,在三项实验中均发现支持该假设的有力证据。该能力在 22B 参数规模时出现,通常随模型规模增大和 RLHF 训练而提升。作者认为,达到这一规模后模型具备两项可用于道德自我纠正的能力:遵循指令,以及学习刻板印象、偏见和歧视等复杂的有害规范概念;结果为训练语言模型遵守伦理原则提供了谨慎乐观的理由。

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