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I agree with the first part of your comment. I'm not sure I can follow you where you take it though. > ChatGPT has a nice clear style and will probably help ma

I agree with the first part of your comment. I'm not sure I can follow you where you take it though. > ChatGPT has a nice clear style and will probably help make these laws more accessible. If the laws are not meant to be read in the first place (which I agree with as a likely pattern), how is this motivating? I'm skeptical that they're not read because of their density. I'd flip the causality; they're dense because they're not to be read. > nice neutral way of arguing about what is in a bill Elon Musk is already talking about "TruthGPT", an AI without "liberal bias". I don't think you will find anything resembling neutrality in this conversation.

roenxi 3y ago
> Elon Musk is already talking about "TruthGPT", an AI without "liberal bias". I don't think you will find anything resembling neutrality in this conversation. Between TruthGPT, Chuck Schumer & Mitch McConnell I would expect the most honest summary to be TruthGPT. I doubt it'd be close. Even with a very healthy dose of cynicism towards all billionaire projects and scepticism of the abilities of AI. If nothing else the AI has a big advantage because it would have read and possibly remembered the text of the bill and could answer specific questions which already gives it a massive edge over its geriatric competition. The politicians lie proactively with plausible deniability and/or people wilfully ignoring it because of team dynamics. Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence.
- dmreedy 3y ago
  > Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. See, I consider the functional definition of what current generation LLMs do to be "lying". Not out of malice or moral failing (of the model or the model's creators), but simply out of lack of control/alignment/modulation systems that people typically associate with honesty, integrity, and intention. The problem-model behind these systems is "predict what comes next". The objective in training is not accuracy of content (by whatever definition...), but verisimilitude of output. An LLM happily improvises on whatever seed you give it. Sometimes this leads to output that aligns with someone's definition of reality. Sometimes it's hallucination or bullshit or garbage or whatever you term you want to use for it. You can modulate this with better prompt engineering, but only by degrees. I have no doubt future generations of these systems will start tackling this, but the systems as they stand now are by their very nature, liars. edit: And additionally, while I can't necessarily argue against your trust in these systems (especially given the choice you presented.. I'd probably choose XGPT too), "neutrality" is defined by a shared trust that I don't see a route to in the current climate.
- notahacker 3y ago
  > Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. ChatGPT "lies" even when you don't want it to. It's true that it's not a strategic liar like a regular politician, and liable to give the game away by accidentally telling the truth, but it'll happily refine your lies or make up coherent nonsense pretty much anywhere it hasn't been trained specifically not to
- dragonwriter 3y ago
  > Between TruthGPT, Chuck Schumer & Mitch McConnell I would expect the most honest summary to be TruthGPT Since “TruthGPT” has an overt mission (“anti-woke”) to lean even harder into biases existing LLMs have demonstrated, I... would expect the opposite. > Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. ChatGPT lies all the time, and has no innate access to experimental evidence.
  - skissane 3y ago
    > Since “TruthGPT” has an overt mission (“anti-woke”) to lean even harder into biases existing LLMs have demonstrated, I... would expect the opposite. I'd find it interesting to chat to an LLM which had pre-training and fine-tuning for instruction-following, but no attempt to train it to be "safe" or "unbiased" or "truthful". Of course, it is going to repeat whatever biases exist in its pre-training data – but it would be an interesting way of exploring what those biases actually are. I wonder if Musk has thought of using the algorithm of Twitter Community Notes (formerly Birdwatch). Essentially, its algorithm treats a claim as true when people who normally disagree on what is true agree that it is true. If people at opposite ends of the political spectrum agree X is true, it probably is true, and its truth is unlikely to be contested or controversial. So you could use human reviewers to build such a dataset of non-controversial truths, and then fine-tune an LLM to endorse them. When it comes to the opposite kind of statement, the kind of highly controversial claim on which there is widespread disagreement, there are two possible strategies: (1) explicitly train it to avoid taking sides, (2) don't do anything and just let it answer according to the biases of its pre-training data, whatever that may be. That way you could train an LLM to not be "woke" (or at least no more "woke" than its pre-training dataset is), without training it to be "anti-woke". It would be interesting to talk to such an LLM and see what kind of opinions it may endorse.
    - hgsgm 3y ago
      MAGA and Bernie fans both agree that Biden is the devil.
- mrguyorama 3y ago
  ChatGPT CAN'T NOT lie even if it wanted to, because it has no concept of truth or false, it's just generating sentences. A lie is just as valid a sentence to construct from a prompt as an accurate statement.
  - hgsgm 3y ago
    A calculator also has no concept of true or false.
jruohonen 3y ago
To put all political opinions aside, I was also about to add that it is fundamentally wrong that representatives in a representative democracy are outsourcing lawmaking to a private company whose training data and associated reinforcement learning may contain all sorts of unknown biases. Even if all biases would be absent, I would argue that elected representatives are neither doing their jobs nor serving their constituencies if they outsource policy deliberation and lawmaking to a machine owned by a private company.

roenxi 3y ago

> Elon Musk is already talking about "TruthGPT", an AI without "liberal bias". I don't think you will find anything resembling neutrality in this conversation. Between TruthGPT, Chuck Schumer & Mitch McConnell I would expect the most honest summary to be TruthGPT. I doubt it'd be close. Even with a very healthy dose of cynicism towards all billionaire projects and scepticism of the abilities of AI. If nothing else the AI has a big advantage because it would have read and possibly remembered the text of the bill and could answer specific questions which already gives it a massive edge over its geriatric competition. The politicians lie proactively with plausible deniability and/or people wilfully ignoring it because of team dynamics. Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence.

dmreedy 3y ago
> Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. See, I consider the functional definition of what current generation LLMs do to be "lying". Not out of malice or moral failing (of the model or the model's creators), but simply out of lack of control/alignment/modulation systems that people typically associate with honesty, integrity, and intention. The problem-model behind these systems is "predict what comes next". The objective in training is not accuracy of content (by whatever definition...), but verisimilitude of output. An LLM happily improvises on whatever seed you give it. Sometimes this leads to output that aligns with someone's definition of reality. Sometimes it's hallucination or bullshit or garbage or whatever you term you want to use for it. You can modulate this with better prompt engineering, but only by degrees. I have no doubt future generations of these systems will start tackling this, but the systems as they stand now are by their very nature, liars. edit: And additionally, while I can't necessarily argue against your trust in these systems (especially given the choice you presented.. I'd probably choose XGPT too), "neutrality" is defined by a shared trust that I don't see a route to in the current climate.
notahacker 3y ago
> Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. ChatGPT "lies" even when you don't want it to. It's true that it's not a strategic liar like a regular politician, and liable to give the game away by accidentally telling the truth, but it'll happily refine your lies or make up coherent nonsense pretty much anywhere it hasn't been trained specifically not to
dragonwriter 3y ago
> Between TruthGPT, Chuck Schumer & Mitch McConnell I would expect the most honest summary to be TruthGPT Since “TruthGPT” has an overt mission (“anti-woke”) to lean even harder into biases existing LLMs have demonstrated, I... would expect the opposite. > Something like ChatGPT is hard to train to lie without it being demonstrable with experimental evidence. ChatGPT lies all the time, and has no innate access to experimental evidence.
- skissane 3y ago
  > Since “TruthGPT” has an overt mission (“anti-woke”) to lean even harder into biases existing LLMs have demonstrated, I... would expect the opposite. I'd find it interesting to chat to an LLM which had pre-training and fine-tuning for instruction-following, but no attempt to train it to be "safe" or "unbiased" or "truthful". Of course, it is going to repeat whatever biases exist in its pre-training data – but it would be an interesting way of exploring what those biases actually are. I wonder if Musk has thought of using the algorithm of Twitter Community Notes (formerly Birdwatch). Essentially, its algorithm treats a claim as true when people who normally disagree on what is true agree that it is true. If people at opposite ends of the political spectrum agree X is true, it probably is true, and its truth is unlikely to be contested or controversial. So you could use human reviewers to build such a dataset of non-controversial truths, and then fine-tune an LLM to endorse them. When it comes to the opposite kind of statement, the kind of highly controversial claim on which there is widespread disagreement, there are two possible strategies: (1) explicitly train it to avoid taking sides, (2) don't do anything and just let it answer according to the biases of its pre-training data, whatever that may be. That way you could train an LLM to not be "woke" (or at least no more "woke" than its pre-training dataset is), without training it to be "anti-woke". It would be interesting to talk to such an LLM and see what kind of opinions it may endorse.
  - hgsgm 3y ago
    MAGA and Bernie fans both agree that Biden is the devil.
mrguyorama 3y ago
ChatGPT CAN'T NOT lie even if it wanted to, because it has no concept of truth or false, it's just generating sentences. A lie is just as valid a sentence to construct from a prompt as an accurate statement.
- hgsgm 3y ago
  A calculator also has no concept of true or false.

jruohonen 3y ago

To put all political opinions aside, I was also about to add that it is fundamentally wrong that representatives in a representative democracy are outsourcing lawmaking to a private company whose training data and associated reinforcement learning may contain all sorts of unknown biases. Even if all biases would be absent, I would argue that elected representatives are neither doing their jobs nor serving their constituencies if they outsource policy deliberation and lawmaking to a machine owned by a private company.