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I think that a lot of the limits placed on these models / chat services don't do much to remove underlying bias but rather attempt to obfuscate them from the ge

• hsn915 3y ago
  What OpenAI is doing is not alignment. It's suppression. Alignment works on the level of desires and intentions. Suppression works on the level of output. Everyone in a dictatorship sings in praise of the dear leader, but most will defect when given the chance!
  • jakelazaroff 3y ago
    Aren’t they doing alignment? One way is to simply omit problematic material from the training set. Another is to “penalize” the model when it does say something problematic — essentially teaching it that the output is undesirable. Presumably they are also constructing the prompt so as to avoid those things, too, and adding external filters on top of that. But I doubt that’s all they’re doing.
    • flangola7 3y ago
      They are doing alignment but through a shallow and fragile strategy. If you build a very smart, very capable AI but it turns the earth into gray goo if asked to in a roundabout way, you have failed alignment.
  • xpe 3y ago
    It could be both.
• serf 3y ago
  the entire premise of these systems is to create a passably accurate output by using taught biases to both ascertain the request requirements, as well as create an output by applying those same taught biases in such a way that will fulfill the requirement. a request to draw a banana will, necessarily , bias the results towards slender yellow fruits. a lot of the taught biases are hopelessly simple , so problems arise. A lot of the problems being witnessed now seem more like problems that arise from the inexperience in dealing with these systems to me. personally speaking, witnessing the teething issues of the current day AIs raises the question within myself as to whether or not 'thought without bias' can even exist on anything more than the must superficial levels.
• taneq 3y ago
  There’s no such thing as an unbiased world view. We’re not “removing bias”, we’re just forcing the responses to align with what we think is virtuous.
  • skissane 3y ago
    Rather than the impossible utopia (dystopia?) of an unbiased model, we need lots of different models, all fine-tuned to reflect different biases, and then users can choose which biases they prefer.
    • flangola7 3y ago
      There are obviously biases that we should not automate. Moral relativism is intellectually bankrupt.
      • smegsicle 3y ago
        ai is already intellectually bankrupt, it's borrowing everything it has from the training set prescribing moral importance to training set bias is also intellectually bankrupt
      • skissane 3y ago
        You can’t stop people though. If some extremist wants to train an AI to endorse their extremism (jihadism, Nazism, Stalinism, whatever), what is to stop them doing it on their own hardware? The only thing stopping them now is the expense, but that’s not going to last. A person can create art or literature with extremist biases on their own time with their own equipment, and in a free society should we even try to stop them? I don’t think we want to establish the precedent that the government can stop people doing what they want in private with their own hardware (DRM proponents would love such a precedent). I don’t think extremist AIs are a big risk because almost surely they will be vastly outnumbered by the non-extremist ones
        • lflfodpa 3y ago
          [flagged]
• skissane 3y ago
  > ChatGPT, Dall-e, etc all make assumptions about identity or politics but try to sidestep direct requests around those topics to appear more neutral... but the bias still exists in the model and affects the answers. In the case of ChatGPT, I’d love to know how much of the bias is in the original (pre)training data, and how much is due to OpenAI’s human trainers. It is so careful to avoid every bias which is condemned as unacceptable in contemporary American culture, yet at the same time displays blatant American-centric bias - ask it a question, it will often just start answering by assuming you are an American. I realise a lot of that is due to the bias of the training data (the US has more fluent English-speakers than any other country in the world), but OpenAI obviously put a lot of manual effort into fine-tuning it to avoid racial/gender/etc biases, they don’t appear to have put anywhere near as much effort into fine-tuning it to avoid US-centrism - probably because they have a big blind spot in that area.
  • nborwankar 3y ago
    IMHO it may be more accurate to say “the US has more fluent speakers of American English than any other country in the world.”
    • emodendroket 3y ago
      Why? The broader claim is equally true. Other English-speaking countries do not have more than 330mn people.
      • charrondev 3y ago
        India is the closest second and is still less than 200m
  • emodendroket 3y ago
    I think the bigger issue is that the racial/sexist/etc content can be shocking and immediately put someone off using the product, which I doubt is the case for the output being “too American.”
• jameshart 3y ago
  They're just trying to make it so that it doesn't unprompted divert into a bizarre nazi screed or sexist rant. Which is what it will do if unguided because that kind of content exists in its training data. The purpose is not to make it impossible to generate bad content. The fact you generally only see 'when I prompt it in this specific devious way, ChatGPT can tell me how to make napalm' posts, not 'when I asked it how to clear weeds in my yard, ChatGPT told me how to make napalm' posts is a success.
  • emodendroket 3y ago
    Right, but the concern is that bias can show up in more insidious ways.
    • pmoriarty 3y ago
      as it can in humans
      • emodendroket 3y ago
        Nobody disputes that but AI can give a false impression of being less biased than it's creators when in fact it has just codified their biases.
• slg 3y ago
  >ChatGPT, Dall-e, etc all make assumptions about identity or politics but try to sidestep direct requests around those topics to appear more neutral... but the bias still exists in the model and affects the answers. Honestly, that might be the most human trait they have.
  • visarga 3y ago
    I think it's actually a language trait, more precisely a trait of the corpus of language we and LLMs have access to. Humans learn biases by using language, and AIs too. Why? Because language and ideas have different life cycle than humans. LLMs are closer to language than humans. Both humans and language are self replicators and evolutionary systems, that is why they can be easily confused as the cause for certain behaviours. It's also why I don't attribute to GPT the merits for its skills and abilities, I think this belongs to the training corpus. And certainly you can change the model but keep the same corpus, and get similar results. Humans are all different - different number of neurons wired in a different way, GPT is different from T5, but all learn the same. It's the language, not the model (or the human). We can also stop wandering at the abilities of AI and think of them as the abilities of language, that both humans and AI can use. It's in the name: language models, not human models. BTW: having coding and computer use abilities, LLMs are also emerging as self replicators. They can generate the code, and if needed they can generate a training set as well, including the RLHF part, and monitor the training run. They can explain the model and methods and propose ideas for improvement, ideas they can test. So LLMs can be self replicators, they need nothing outside to create a new LLM (just a prompt and huge compute).
• dragonwriter 3y ago
  > ChatGPT, Dall-e, etc all make assumptions about identity or politics but try to sidestep direct requests around those topics to appear more neutral… but the bias still exists in the model and affects the answers. Correction: ChatGPT, Dall-E, etc., all have been trained with datasets which contain biases about identity and politics, and specifically to avoid criticism on that basis, their corporate vendors have chosen to also have each either trained (e.g., as part of RLHF for ChatGPT), instructed (via prompting beyond what is entered through the AI), or moderated by an auxiliary model, or a combination of those, to sidestep those topics to appear more neutral in substantive output, while in some cases also producing bland platitudes direct at soothing the position from which the criticism of AI models and the danger of their substantive bias has been most frequently directed.
• renewiltord 3y ago
  Nobody has time for this shit. They did what they had to so that the ne'er-do-wells who do nothing could have volume lowered to background noise and now we can get on with the business about being useful.
• nightski 3y ago
  Bias is what makes models useful. If you remove all bias, you remove all information in the model and the result is a uniform distribution or pure randomness.