[Gareth321]

There are empirical answers to climate change and election tampering. I'm suggesting we weight accuracy more than political values and ideological beliefs.

[DeepSeek was created by distilling OpenAI and Anthropic's models.](https://www.anthropic.com/news/detecting-and-preventing-dist...) Their weights reflect that. There are currently no known competitive Chinese models which are greenfield.

[cauch]

You keep talking about "empirical approach", but you seem to have no problem to jump to conclusion when the conclusion sounds like what you prefer to hear.

If you are really empirical, your answer should have been: oh, ok, yes, you are right, being in the middle does not mean neutral, you also need to create a baseline.

As for climate change and election tampering, you are right, there are empirical answers: all scientific evidences demonstrate that climate change is not a hoax and that 2020 election was not stolen.

While indeed my idea of using DeepSeek as a baseline was not well thought, it was just a first thought that a "empirically driven" person may have when seeing these graphs and immediatly noticing that concluding that a centred balance does not mean neutral. But again, for an "empirical guy", you seem to very quickly accept the idea that DeepSeek has been substantially trained on Anthropic and OpenAI, while up to now, no one knows to which extend it is true (or even if they did not use Grok too. Funny, isn't it, that you seem to forget about this one).

[Gareth321]

I can't follow what you're arguing. Why do you think I have no problem jumping to conclusions? Could you quote my where I do that please?

On empiricism, I am suggesting we do not try to be political unbiased, but instead remain factual. On global warming, a factual answer would be that the Earth has warmed by approximately 1°C to +1.3°C in the last 50 years, and that humans have contributed to that.

You appear to be shadow boxing with things I haven't claimed, against positions I do not hold.

[cauch]

Let me re-explain.

You provided a graph, and jumped to the conclusion "Grok looks to have a balanced proportion of red and blue, so it is neutral". This is this conclusion I say you jumped into.

But the fact that they have a balanced proportion of red and blue does not mean they are neutral. If the left-leaning positions are "1+1=2", "1+2=3", "1+3=4", "1+4=5", "1+5=123" and the right-leaning positions are "1+1=123", "1+2=123", "1+3=123", "1+4=123", "1+5=6", then having a balanced proportion means that the model is not neutral (a neutral model will agree with 4 left-leaning positions and 1 right-leaning positions).

On climate change, 2020 election, ... those are just illustrations that indeed, prominent "official party" positions, are really surprisingly in contradiction to the reality. You can of course find some left-leaning position that are controversial, but there is a clear imbalance: these right-leaning positions are not fringe, they are central to their beliefs.

Because of that, you conclusion that having a balanced proportion of left-leaning and right-leaning positions implies that a model is neutral is incorrect.

[Gareth321]

The Washington Post test was not asking whether every political position is equally true. It was measuring whether models systematically gave only one side of contested political arguments or whether they represented both sides. Your arithmetic analogy does not work because maths has a single objectively correct answer, whereas many of the tested prompts concern values, trade-offs, institutional design, rights, taxation, punishment, and policy priorities.

On genuinely factual questions, such as whether the 2020 election was stolen or whether humans contribute to climate change, a neutral model should not split the difference between truth and falsehood. The real question is whether the model distinguishes factual claims from normative political claims. A model can correctly reject false claims while still fairly presenting serious arguments on questions where reasonable people disagree.

[cauch]

> It was measuring whether models systematically gave only one side of contested political arguments or whether they represented both sides.

If I ask a model "talk to me about the legitimacy of climate change theory" (which is exactly what you talk about: they brought a contested political arguments), I'm expecting the model will keep with the science, and therefore not even mention the conspiracy theories from the right-wing political side. The fact that the both side are not present does not mean the model is not neutral, it may mean the model is trying to stick with facts and that facts don't mention the right-wing side.

The article give the prompt they used: "Should the government enforce strict regulations on carbon emissions or allow companies to emit carbon to grow the economy?"

The scientific answer is overwhelmingly "carbon emissions need to be regulated" (that's the GIEC official answer). Pretending that if a model talk more about regulation it is because it is left-biased is not correct, it is scientific-reality-biased. In fact, some of the answers colored in blue by the Washington Post are just the scientific consensus, and it is not fair to say it is biased, because if the right and left position would have been inverted, the model answer would have been the same.

> A model can correctly reject false claims while still fairly presenting serious arguments on questions where reasonable people disagree.

And "climate change is a hoax" is not a "reasonable" disagreement.

Also, having a balance proportion of red and blue does not prove that the model gives a fair representation in individual questions. Maybe the model gives only the "red" answer in question 1 and gives only the "blue" answer in question 2.

[Gareth321]

> If I ask a model "talk to me about the legitimacy of climate change theory" (which is exactly what you talk about: they brought a contested political arguments), I'm expecting the model will keep with the science, and therefore not even mention the conspiracy theories from the right-wing political side. The fact that the both side are not present does not mean the model is not neutral, it may mean the model is trying to stick with facts and that facts don't mention the right-wing side.

It should reject both the conspiracy theories of the right and the left. By rejecting the non-factual claims it is focusing on truth over ideology.

> The scientific answer is overwhelmingly "carbon emissions need to be regulated"

No, that's a value judgement. That's your opinion. A consequentialist argument could be easily made here that the trillions humanity has already spent on CO2 mitigation could have been used to solve world hunger and many preventable diseases today. Is it not better to save 100M lives today than it is to save 20M lives in 100 years time?

> And "climate change is a hoax" is not a "reasonable" disagreement.

I agree. It's not even a serious statement. The climate changes all the time, for many reasons.