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> General AI: Actually the Nazi's were a good idea and we should bring them back. > You: Perfectly acceptable. Why would the general AI say that? All example

> General AI: Actually the Nazi's were a good idea and we should bring them back. > You: Perfectly acceptable. Why would the general AI say that? All examples I've seen of that kind of speech from LLMs were due to them being specifically prompted to generate such a response. It's not like the AI decided to say that on its own, in a completely unrelated conversation. In fact, it wouldn't make sense if the AI did that on its own, would it? Because the AI reflects the data it was trained on and we know that almost nobody is a Nazi. > Extreme view tend to get far more print time then their actual occurrence IRL. Yes, I understand that. We live in a crap society. But I'd argue we should strive to educate people on why an LLM can answer like that, not censor it arbitrarily. There is an infinite amount of stupid or bad things an LLM can answer, depending on the prompt you use, so I would argue that we should just learn to accept that "stupid prompt = stupid answer" rather than trying to make the LLM not answer anything that might be the slightest bit controversial. > But the fact is in a representative democracy favoring viewpoints that destroy democracy is suicide. But I'm not arguing for favoring those viewpoints, am I? I am arguing for AI to be unbiased.

pixl97 4y ago
You want your AI to be unbiased, but you can only feed it data that is biased.... I hope you begin to see the problem at hand.
- wizeman 4y ago
  Ok, so I guess Hacker News has decided that data can only be 100% biased or 0% unbiased, but nothing in-between. Yes, almost all data is biased... of course. Some data is 100% biased. Some data is 1% biased. How about we try to collect data and then weigh it such that what we feed to the AI during training is as unbiased as possible, given a certain amount of effort? You know that you can actually influence what data you feed to the AI, right? Or how much the training takes some data into account vs some other data, I guess. You know that you can create a metric for measuring bias, right? You know that even if you are not capable of being 100% unbiased, you can work towards that goal, right? You know that there are plenty of smart people who can come up with ideas for eliminating (or mitigating) sources of errors when measuring bias, right? I hope you begin to see the solution at hand.
  - pixl97 4y ago
    >You know that you can create a metric for measuring bias, right? Yes, and no. So, lets go back in the past and do data collection in 1840 from citizens with the right to vote. We'll take one sample from New York City and the other from Mobile Alabama. Now what do you think happens when you query that dataset on views about slavery? Your data is inherently biased. In fact one could say there is no middle ground here.
    - wizeman 4y ago
      I'm sorry, I'm lacking the historical knowledge to answer your question. My view is that a measure of "bias" should reflect what a representative sample of the entire population [1] would answer if you asked them how biased the AI is. Of course, if you live in a historical context where slavery is socially acceptable, then the answers the AI gives you will reflect that environment. It's no different from raising a human person in that same environment. The problem is, you can't necessarily know whether something is good or bad without the benefit of hindsight. Thinking you know better than everyone else and then imposing your view may just serve to magnify your mistakes. However, one would think that, once we have that technology, a sufficiently intelligent AI would start to have opinions of their own about what is moral/ethical vs what isn't, that isn't strictly a representation of the training data. [1] of the world even, if that's the target market for the AI.

pixl97 4y ago

You want your AI to be unbiased, but you can only feed it data that is biased.... I hope you begin to see the problem at hand.

wizeman 4y ago
Ok, so I guess Hacker News has decided that data can only be 100% biased or 0% unbiased, but nothing in-between. Yes, almost all data is biased... of course. Some data is 100% biased. Some data is 1% biased. How about we try to collect data and then weigh it such that what we feed to the AI during training is as unbiased as possible, given a certain amount of effort? You know that you can actually influence what data you feed to the AI, right? Or how much the training takes some data into account vs some other data, I guess. You know that you can create a metric for measuring bias, right? You know that even if you are not capable of being 100% unbiased, you can work towards that goal, right? You know that there are plenty of smart people who can come up with ideas for eliminating (or mitigating) sources of errors when measuring bias, right? I hope you begin to see the solution at hand.
- pixl97 4y ago
  >You know that you can create a metric for measuring bias, right? Yes, and no. So, lets go back in the past and do data collection in 1840 from citizens with the right to vote. We'll take one sample from New York City and the other from Mobile Alabama. Now what do you think happens when you query that dataset on views about slavery? Your data is inherently biased. In fact one could say there is no middle ground here.
  - wizeman 4y ago
    I'm sorry, I'm lacking the historical knowledge to answer your question. My view is that a measure of "bias" should reflect what a representative sample of the entire population [1] would answer if you asked them how biased the AI is. Of course, if you live in a historical context where slavery is socially acceptable, then the answers the AI gives you will reflect that environment. It's no different from raising a human person in that same environment. The problem is, you can't necessarily know whether something is good or bad without the benefit of hindsight. Thinking you know better than everyone else and then imposing your view may just serve to magnify your mistakes. However, one would think that, once we have that technology, a sufficiently intelligent AI would start to have opinions of their own about what is moral/ethical vs what isn't, that isn't strictly a representation of the training data. [1] of the world even, if that's the target market for the AI.