4 ms·

> A woke-censored LLM will answer some questions notably different Do you remember the fiasco that was Tai AI? Do you think letting it run "uncensored", aka t

> A woke-censored LLM will answer some questions notably different Do you remember the fiasco that was Tai AI? Do you think letting it run "uncensored", aka turn full on Nazi/racist, was a good idea, or something any company would be okay with? Humans are quite adept at self-censoring when relevant. An AI model needs to be taught the same thing. And heck, even humans can be racist, it's just that most humans are reasonably moderate. (For context: https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist https://www.theverge.com/2016/3/24/11297050/tay-microsoft-ch...)

baobabKoodaa 3y ago
We just had an explosion of LLMs, including many uncensored LLMs, which have capacities that people could only dream of 8 years ago. And yet, as you make your pro-censorship argument, you have to reach back as far as 8 years in order to find an example to support your pro-censorship position. I think that's telling for how weak your pro-censorship position really is.
- user_7832 3y ago
  To clarify: I'm not in favour of censorship itself. But I am in favor of moderating the behaviour of a model that many thing is half-intelligent and trust a lot, and can be "fooled" into saying wrong/hateful things. Issue is, unfortunately I don't have any solutions myself. Another thought I had: what about times when LLMs suggest something dangerous? I may call it instructing the model to not do dangerous things, you may call it censorship. For example, when a model suggested making chlorine gas- (https://arstechnica.com/information-technology/2023/08/ai-powered-grocery-bot-suggests-recipe-for-toxic-gas-poison-bread-sandwich/ https://arstechnica.com/information-technology/2023/08/ai-po...). Do you think such outputs are good? The vast majority of products in everyday life have warnings or failsafes, from cars that chime when the seatbelt isn't put on to all sorts of warnings on allergens. Allowing a completely "free" LLM has risks, and honestly even if all HN'ers agreed to not censor it it likely wouldn't matter as companies would rather censor than have liabilities.
  - baobabKoodaa 3y ago
    You're not in favour of "censorship", you're just in favor of "moderating". Po-tay-to, po-taa-to. Regardless of what words you want to use, we fundamentally disagree on this. If you want to espouse your "pro-moderating" position in the future, maybe choose an example that's not from 8 years ago, as things have changed quite a bit since then. edit: I see you edited in the chlorine gas example. Do I think a cooking chat app should accidentally recommend a recipe that recommends chlorine gas? No, the cooking app makers should have the ability to control the LLM so it doesn't do that. Do I think the cooking app makers should be prevented from making these decisions, and instead have those decisions forced on them by the base LLM model? No. I think app developers should have control over how to censor the outputs. The base LLM should be uncensored.
    - user_7832 3y ago
      (I updated my comment a few moments ago with another example and some more text, but I guess we'll have to agree to disagree)
      - baobabKoodaa 3y ago
        > companies would rather censor than have liabilities. Companies that create products on top of LLMs absolutely should have the power to censor the LLM as they want, and they should add a lot of censorship to support their use cases. They should not be prevented from making these decisions (by applying censorship at the base LLM level you prevent companies from doing these decisions).
    - user_7832 3y ago
      I do agree that the cooking app makers should have this control instead of the base model having this baked in, but that wouldn't help if someone directly used chatgpt's website for cooking recipes. Ironically a "dumb" solution of having specific guardrails depending on the application (eg cooking advisorGPT doesn't make inedible food, arts&craftsGPT doesn't suggest a thermite bomb) could help, with the guardrails being on top of an open base LLM but everyone loves their non-deterministic chatbots to do tasks that hard-coded algorithms could do ¯\_(ツ)_/¯ (Ideally I would love the base llm to also be truly open as well, but that's another issue.)

baobabKoodaa 3y ago

We just had an explosion of LLMs, including many uncensored LLMs, which have capacities that people could only dream of 8 years ago. And yet, as you make your pro-censorship argument, you have to reach back as far as 8 years in order to find an example to support your pro-censorship position. I think that's telling for how weak your pro-censorship position really is.

user_7832 3y ago
To clarify: I'm not in favour of censorship itself. But I am in favor of moderating the behaviour of a model that many thing is half-intelligent and trust a lot, and can be "fooled" into saying wrong/hateful things. Issue is, unfortunately I don't have any solutions myself. Another thought I had: what about times when LLMs suggest something dangerous? I may call it instructing the model to not do dangerous things, you may call it censorship. For example, when a model suggested making chlorine gas- (https://arstechnica.com/information-technology/2023/08/ai-powered-grocery-bot-suggests-recipe-for-toxic-gas-poison-bread-sandwich/ https://arstechnica.com/information-technology/2023/08/ai-po...). Do you think such outputs are good? The vast majority of products in everyday life have warnings or failsafes, from cars that chime when the seatbelt isn't put on to all sorts of warnings on allergens. Allowing a completely "free" LLM has risks, and honestly even if all HN'ers agreed to not censor it it likely wouldn't matter as companies would rather censor than have liabilities.
- baobabKoodaa 3y ago
  You're not in favour of "censorship", you're just in favor of "moderating". Po-tay-to, po-taa-to. Regardless of what words you want to use, we fundamentally disagree on this. If you want to espouse your "pro-moderating" position in the future, maybe choose an example that's not from 8 years ago, as things have changed quite a bit since then. edit: I see you edited in the chlorine gas example. Do I think a cooking chat app should accidentally recommend a recipe that recommends chlorine gas? No, the cooking app makers should have the ability to control the LLM so it doesn't do that. Do I think the cooking app makers should be prevented from making these decisions, and instead have those decisions forced on them by the base LLM model? No. I think app developers should have control over how to censor the outputs. The base LLM should be uncensored.
  - user_7832 3y ago
    (I updated my comment a few moments ago with another example and some more text, but I guess we'll have to agree to disagree)
    - baobabKoodaa 3y ago
      > companies would rather censor than have liabilities. Companies that create products on top of LLMs absolutely should have the power to censor the LLM as they want, and they should add a lot of censorship to support their use cases. They should not be prevented from making these decisions (by applying censorship at the base LLM level you prevent companies from doing these decisions).
  - user_7832 3y ago
    I do agree that the cooking app makers should have this control instead of the base model having this baked in, but that wouldn't help if someone directly used chatgpt's website for cooking recipes. Ironically a "dumb" solution of having specific guardrails depending on the application (eg cooking advisorGPT doesn't make inedible food, arts&craftsGPT doesn't suggest a thermite bomb) could help, with the guardrails being on top of an open base LLM but everyone loves their non-deterministic chatbots to do tasks that hard-coded algorithms could do ¯\_(ツ)_/¯ (Ideally I would love the base llm to also be truly open as well, but that's another issue.)