--- date: '2022-12-19T14:50:09' hypothesis-meta: created: '2022-12-19T14:50:09.008193+00:00' document: title: - My AI Safety Lecture for UT Effective Altruism flagged: false group: __world__ hidden: false id: bvVepH-sEe2uPgfvTF7V-w links: html: https://hypothes.is/a/bvVepH-sEe2uPgfvTF7V-w incontext: https://hyp.is/bvVepH-sEe2uPgfvTF7V-w/scottaaronson.blog/?p=6823 json: https://hypothes.is/api/annotations/bvVepH-sEe2uPgfvTF7V-w permissions: admin: - acct:ravenscroftj@hypothes.is delete: - acct:ravenscroftj@hypothes.is read: - group:__world__ update: - acct:ravenscroftj@hypothes.is tags: - explainability - nlproc target: - selector: - endContainer: /div[2]/div[2]/div[2]/div[1]/p[72] endOffset: 437 startContainer: /div[2]/div[2]/div[2]/div[1]/p[72] startOffset: 10 type: RangeSelector - end: 29171 start: 28744 type: TextPositionSelector - exact: " Eventually GPT will say, \u201Coh, I know what game we\u2019re playing!\ \ it\u2019s the \u2018give false answers\u2019 game!\u201D And it will then\ \ continue playing that game and give you more false answers. What the new\ \ paper shows is that, in such cases, one can actually look at the inner layers\ \ of the neural net and find where it has an internal representation of what\ \ was the true answer, which then gets overridden once you get to the output\ \ layer." prefix: "Does 2+2=4? No.\u201D\n\n\n\n\nand so on." suffix: "\n\n\n\nTo be clear, there\u2019s no know" type: TextQuoteSelector source: https://scottaaronson.blog/?p=6823 text: this is fascinating - GPT learns the true answer to a question but will ignore it and let the user override this in later layers of the model updated: '2022-12-19T14:50:09.008193+00:00' uri: https://scottaaronson.blog/?p=6823 user: acct:ravenscroftj@hypothes.is user_info: display_name: James Ravenscroft in-reply-to: https://scottaaronson.blog/?p=6823 tags: - explainability - nlproc - hypothesis type: annotation url: /annotations/2022/12/19/1671461409 ---
Eventually GPT will say, “oh, I know what game we’re playing! it’s the ‘give false answers’ game!” And it will then continue playing that game and give you more false answers. What the new paper shows is that, in such cases, one can actually look at the inner layers of the neural net and find where it has an internal representation of what was the true answer, which then gets overridden once you get to the output layer.
this is fascinating - GPT learns the true answer to a question but will ignore it and let the user override this in later layers of the model