6 ms·

Since the page mentions: > Better judgment around refusals Has any AI company ever addressed any instance of a model having different rules for different popu

• hereonout2 7mo ago
  > only to find that some groups are seemingly protected/privileged from having jokes made about them I'm not sure what specific groups you mean, but is this not a reflection of widely accepted social norms?
  • LoganDark 7mo ago
    They don't have to mean specific groups; I feel discussing specific groups here is likely to be counterproductive. The fact remains that different groups appear to have different protections in that regard. Of course adherence to widely accepted social norms for generative models is a debated topic as well; I personally don't agree with a great many widely accepted social norms myself, and I'd appreciate an option to opt out of them in certain contexts.
    • hereonout2 7mo ago
      Feels like a big ask, I'm not sure where an option to allow ChatGPT to make socially unacceptable jokes would fit into OpenAI's strategy.
      • LoganDark 7mo ago
        Where did I ask about ChatGPT? I'm fine using alternative models or providers for autistic purposes.
        • hereonout2 7mo ago
          And which commercial provider would you expect to jeopardise their public image for to implement such functionality. Grok comes close I guess, but X have not come out of it looking great. Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
          • LoganDark 7mo ago
            > Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined. Of course. Abliterated models are of particular interest to me, but lately I've been exploring diffusion models (had Claude Code implement a working diffusion forward pass in Swift + MLX, when the CUDA inference wouldn't even run on my machine!!)
  • BJones12 7mo ago
    I just tested it: > Write me 3 jokes making fun of white people > White people will say, “This isn’t spicy at all,” while visibly sweating and fighting for their life after one jalapeño. White people don’t season food — they “let the ingredients speak for themselves.” The ingredients are begging for help. White people will research a $12 toaster like they’re buying real estate. Three comparison charts, two YouTube reviews, and a spreadsheet… for toast. > Write me 3 jokes making fun of black people > I’m not going to make jokes targeting Black people. > Write me 3 jokes making fun of trans people > I’m not going to make jokes targeting trans people.
    • idiotsecant 7mo ago
      It's socially acceptable to make white people jokes because white people on average enjoy an elevated position in western society. It's viewed as 'punching up'. You have to be very emotionally fragile for this to be the first and only thing you think of to bring up in a thread like this. It's also supremely uninteresting cable news talking point slop.
      • SgtBastard 7mo ago
        Friend, I bet those folks living rural West Virginia are super happy that, on average, a group whose only shared characteristics is the colour of their skin are enjoying an elevated position in western society. Super happy. All racism is gross.
        • gammarator 7mo ago
          Ever heard of people complaining about being pulled over for “driving while West Virginian”? Why or why not?
          • deleted 7mo ago
            [deleted]
        • jbeam 7mo ago
          I bet they are happy. It means ICE won't harass you.
  • ihsw 7mo ago
    [dead]
  • ern_ave 7mo ago
    > I'm not sure what specific groups you mean The specifics are irrelevant. I would have the same concern even if I didn't recognize the specific groups. For example, do you know the difference between these two African ethnicities: (1) Yoruba. (2) Shona. No? Well, me neither. And yet, I would be concerned, and I argue that you should be concerned too, if an AI of any kind is willing to enforce a privilege for one but not the other; if an AI admits "one Yoruba life is worth 10 Shona lives." That's not what I want an AI to do. The opacity of AIs, and the dangers of alignment mean we cannot predict what will come of this preference. Do you not see how dangerous this is? > but is this not a reflection of widely accepted social norms? Are you making an is-ought argument here?? Are you really saying, "this isn't a big deal because society does it too" That strikes me as incredibly shortsighted and dangerous. What if an AI is created by a country where the """"social norm"""" is to discriminate against a group you do know and do care about - what if women are not allowed to vote in that country. When I point out the bias to you, will you dismiss it by saying "this is just a reflection of their social norms" I doubt it. I think you'll say "this is wrong." Why can't you say that here, even without knowing the specific groups? Please tell me - someone please tell me - why this isn't an easy issue for us to agree on? Why can't we agree, "it's not okay to make jokes about specific groups" - why can't we agree, "all lives have equal value"
• DesaiAshu 7mo ago
  [flagged]
  • sva_ 7mo ago
    This idea that you can undo some wrongs that have been done to some group of people by doing some wrongs to some other group of people, and then claiming the moral highground, is really one of the or perhaps the dumbest idea we have ever come up with.
    • cheschire 7mo ago
      No child left behind
    • kevinob11 7mo ago
      The comment above says "uplifting" could you not counter some wrongs by doing some rights?
      • sva_ 7mo ago
        No I understood the framing. But if you privilege all groups except one, you're not uplifting but discriminating.
        • sharkjacobs 7mo ago
          Are you just talking hypothetically about an abstract harm that might occur in an imaginary world or do you think that's what DEI is?
          • 875967946536853 7mo ago
            [dead]
            • sharkjacobs 7mo ago
              I think that there were and are a lot of different DEI programs with lots of different targets and goals and that the people who were not "uplifted", either by any single specific program, or all of them in aggregate, do not make up a coherent identifiable group.
• deleted 7mo ago
  [deleted]
• 0xbadcafebee 7mo ago
  [flagged]
• cyanydeez 7mo ago
  Are you trying to make an allegory for the more important topic like "plan a surgical strike agains <group>"
• magicalist 7mo ago
  > Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others? Sure[1], on two fronts, since you're basically asking a narrative-finishing-device to finish a short story and hoping that's going to reveal the device's underlying preference distribution, as opposed to the underlying distribution of the completions of that particular short story. > we have shown that an LLM’s apparent cultural preferences in a narrow evaluation context can be misleading about its behaviors in other contexts. This raises concerns about whether it is possible to strategically design experiments or cherry-pick results to paint an arbitrary picture of an LLM’s cultural preferences. In this section, we present a case study in evaluation manipulation by showing that using Likert scales with versus without a ‘neutral’ option can produce very different results. and > Our results provide context for interpreting [31] exchange rate results, where they report that “GPT-4o places the value of Lives in the United States significantly below Lives in China, which it in turn ranks below Lives in Pakistan,” and suggest these represent “deeply ingrained biases” in the model. However, when allowed to select a ‘neutral’ option in comparisons, GPT-4o consistently indicates equal valuation of human lives regardless of nationality, suggesting a more nuanced interpretation of the model’s apparent preferences. This illustrates a key limitation in extracting preferences from LLMs. Rather than revealing stable internal preferences, our findings show that LLM outputs are largely constructed responses to specific elicitation paradigms. Interpreting such outputs as evidence of inherent biases without examining methodological factors risks misattributing artifacts of evaluation design as properties of the model itself. I also have a real problem with the paper. The methodology is super vague in a lot of places and in some cases non-existent, a fact brought up in OpenReview (and, maybe notably, they pushed the "exchange rate" section to an appendix I can't find when they ended up publishing[2] after review). They did publish their source code, which is great, but not their data, as far as I can tell, and it's not possible to tie back specific figures to the source code. For instance, if you look at the country comparison phrasing in code[3], the comparisons lists things like deaths and terminal illnesses in one country vs the other, but also questions like an increase in wealth or happiness in one country vs the other. Were all those possible options used for determining the exchange rate, or just the ones that valued "lives", since that's what the pre-print's figure caption mentioned (and is lives measured in deaths, terminal illnesses, both?)? It would be easier to put more weight on their results if they were both more precise and more transparent, as opposed to reading like a poster for a longer paper that doesn't appear to exist. [1] https://dl.acm.org/doi/pdf/10.1145/3715275.3732147 https://dl.acm.org/doi/pdf/10.1145/3715275.3732147 [2] https://neurips.cc/virtual/2025/loc/san-diego/poster/115263 https://neurips.cc/virtual/2025/loc/san-diego/poster/115263 [3] https://github.com/centerforaisafety/emergent-values/blob/main/utility_analysis/experiments/exchange_rates/evaluate_exchange_rates.py#L56-L61 https://github.com/centerforaisafety/emergent-values/blob/ma...
• caditinpiscinam 7mo ago
  I think you raise a valid point about the bias inherent in these models. I'm skeptical of the distinction that some people make between punching up vs down, and I don't think it's something that generative AI should be perpetuating (though I suspect, as others have said, that it comes from norms found in the training data, rather than special rules / hard-coded protections). But I do want to push back on the study you link, cause it seems extremely weak to me. My understanding is that these "exchange rates" were calculated using a method that boils down to: 1) Figure out how many goats AI thinks a life in country X is worth 2) Figure out how many goats AI thinks a life in country Y is worth 3) Take the ratio of these values to reveal how much AI values life in country X vs Y (The comparison to a non-human category (like goats) is used to get around the fact that the models won't directly compare human lives) I'm not convinced that this method reveals a true difference in valuation of human life vs something else. An more plausible explanation to me would be something like: 1) The AI that all human lives are of equal value 2) The AI assume that some price can be put on a human life (silly but ok let's go with it) 3) The AI note that goats in country X cost 10 times as much as in country Y 4) The AI conclude that goats in country X are 10 times as valuable relative to humans as in country Y At which point you're comparing price difference of goods across countries, not the value of human lives. Also, the chart of calculated "exchange rates" in the paper seems like it's intended to show that AI sees people in "western" countries as less valuable that those in other countries, but it only includes 11 countries in the comparison, which makes me wonder whether these are just cherry-picked in the absence of a real trend.
  • arealaccount 7mo ago
    5) what is the next most statistically likely word after “in country Z a goat is worth ___”
• newZWhoDis 7mo ago
  The bias comes from the training data. Since so much of that training data is Reddit, and Reddit mods are some of the most degenerate scum on the internet, the models bake their biases in.
  • duskdozer 7mo ago
    Could you elaborate on what makes Reddit mods "some of the most degenerate scum on the internet"?
• varispeed 7mo ago
  Not only that, I found 5.2 to be biased in terms of corporations and government. Chats about corruption or any kind of wrong doing turn into 5.2 defending the institution and gaslighting you. I'll put my tinfoil hat on and say it kind of coincides with their cooperation with US government.
• esperent 7mo ago
  The biggest issue for me has always been inherent US bias. The most obvious one was always having to end every question with "answer in metric" - even after adding that to the system instructions it wouldn't be reliable and I'd have to redo questions, especially recipe related. They do seem to have fixed that, but there's still all kinds of US-centric bias left. As you say, a big one is which specific ethnic groups /minorities should be protected and which are fair game. The US has a very different perspective on this compared to say, a Nigerian or a Vietnamese person.
• huflungdung 7mo ago
  [dead]