It seems to me there is a difference between doing science (in particular, figuring out the ways in which the physical world works) and making far-future predictions.
When Newton described the law of gravity he did not make far-future predictions about objects falling. He just discovered a law of nature. In the same way, Arrhenius was trying to figure out how the link between atmospheric CO2 and global climate works. It's just normal science and as such doesn't offer evidence for or against far-future predictions.
Oh, and by the way, whether global warming has positive or negative net impact critically depends on its magnitude. Minor global warming (up to about 2 degrees C, I believe) is commonly considered beneficial.
When Newton described the law of gravity he did not make far-future predictions about objects falling. He just discovered a law of nature. In the same way, Arrhenius was trying to figure out how the link between atmospheric CO2 and global climate works. It's just normal science and as such doesn't offer evidence for or against far-future predictions.
There might be, e.g., economic laws that can be thought of as "science" that have relevance to predicting things related to artificial intelligence.
...Oh, and by the way, whether global warming has
In Intelligence Explosion analysis draft: introduction, Luke Muehlhauser and Anna Salamon wrote
As a part of the project "Can we know what to do about AI?", I've summarized my initial impressions of Arrhenius's predictions and the impact that they might have had. The object level material is all draw from Wikipedia, and I have not vetted it.
Taking this all together, based on my surface impressions, I think that this case study gives evidence against attempting to predict the far future being useful: