When pharma companies produce a new drug which appears to have a positive effect, they don't know that it will cause problems and don't have any data to back up any concerns.
So do they rush full-steam-ahead into the unknown? Do you unleash the drug to whomever wants it, without regulation? No, of course not; you approach with caution, you hold clinical trials, you collect data as you go and you look for potential problems before the drug is widespread.
Arguably a similarly controlled approach would have helped in the case of carbon output and will help in the case of AI. It's not about fear mongering or preventing progress, it's about discussing ways to approach with caution and solve problems (and minimise the damage they cause), if and when they arise.
If someone can do forecasting of AGI with similar empiricism that would be revolutionary and welcomed.
Moravec's 70s papers are roughly comparable to Arrhenius's formula. The basic computational power predictions (a minor extension of Moore's law) still seem to be basically correct. There's a reasonable debate to be had about whether more interesting predictions made by Moravec/Kurzweil/etc. have been validated or not.
It's akin to someone back then worrying about the long-term effects of steam/water vapor.
You don't know if vapor is actually a problem, or will become one, and you don't have any data in any field to back up your concerns.