In the real world, we see portfolios excluding fossil fuels, individual retail investors refusing to put money into fossil fuels, divestment from public institutions, etc.
My current take is that to a large extent, the reason this can happen is because there are substitute technologies like solar + batteries that became cheap enough in the 2010s and are still getting cheaper such that you can actually substitute it for fossil fuels.
AI has for all intents and purposes zero substitute.
To put it another way, there’s ~zero counterfactual impact from the things you list, and ~all of the impact if you wanted to end fossil fuel usage is to pursue policies that make gas more expensive and making alternative low-carbon stuff cheaper.
It’s not a coincidence that the commitments you mentioned were made about as soon as it was practical to make them without suffering economic losses, and by the late 2010s are even profitable, so in essence this was a thing where the profitable thing also correlated to what we want.
Unfortunately AI lacks this, so divestment/exclusion (without government intervention) doesn’t work.
Keep in mind, for the most part, AI right now is barely profitable. AI adopting firms are only doing marginally better than other firms and that had only been in the past year that it has really been making a measurable difference. The attitude that AI profitability is unstoppable and omnipresent doesn’t match the current reality. The more investment there is, the sooner it is likely for AI firms to accelerate and develop larger profit margins, but if there is a hump of profitability with no turning back, we are just at the foot of it. The less appealing and profitable it looks and the lest investment there is, the longer it will take. And the more likely regulation is. The more appealing it is and the more heagily it is invested in, the more the development will accelerate and the less likely regulation is.
is that to a large extent, the reason this can happen is because there are substitute technologies like solar + batteries that
As I described before, it is a feedback loop. Divestment and moving sentiment makes other methods more profitable, leads to more less investment in fossil fuels and more in alternatives, and that combined with public media efforts makes regulation much more feasible.
To put it another way, there’s ~zero counterfactual impact from the things you list,
No public divestment and disintentives to use fossil fuels, investments don’t move into developing alternative energy, outside of niche applications, solar and wind are seen as unprofitable and not researched, more research is put into fossil fuels, making them cheaper making the bar to entry higher for alternatives, policy makers are less willing to impose regulations on fossil fuels since the costs of doing so are greater (since alternatives are more expensive) further slowing development.
You can look at places in the US where attitudes towards fossil fuel are different and investment is seen as more acceptable and you see exactly that.
AI has for all intents and purposes zero substitute.
This is just not true. AI is being used as a substitute. Sometimes for more specialized SaaS solutions, sometimes for reducing the number of HR staff, and sometimes replacing interns assigned to doc review, etc. You can argue it has a qualitative advantage over substitutes, sometimes it has a clear disadvantage even and trade offs.
My current take is that to a large extent, the reason this can happen is because there are substitute technologies like solar + batteries that became cheap enough in the 2010s and are still getting cheaper such that you can actually substitute it for fossil fuels.
AI has for all intents and purposes zero substitute.
To put it another way, there’s ~zero counterfactual impact from the things you list, and ~all of the impact if you wanted to end fossil fuel usage is to pursue policies that make gas more expensive and making alternative low-carbon stuff cheaper.
It’s not a coincidence that the commitments you mentioned were made about as soon as it was practical to make them without suffering economic losses, and by the late 2010s are even profitable, so in essence this was a thing where the profitable thing also correlated to what we want.
Unfortunately AI lacks this, so divestment/exclusion (without government intervention) doesn’t work.
Keep in mind, for the most part, AI right now is barely profitable. AI adopting firms are only doing marginally better than other firms and that had only been in the past year that it has really been making a measurable difference. The attitude that AI profitability is unstoppable and omnipresent doesn’t match the current reality. The more investment there is, the sooner it is likely for AI firms to accelerate and develop larger profit margins, but if there is a hump of profitability with no turning back, we are just at the foot of it. The less appealing and profitable it looks and the lest investment there is, the longer it will take. And the more likely regulation is. The more appealing it is and the more heagily it is invested in, the more the development will accelerate and the less likely regulation is.
As I described before, it is a feedback loop. Divestment and moving sentiment makes other methods more profitable, leads to more less investment in fossil fuels and more in alternatives, and that combined with public media efforts makes regulation much more feasible.
No public divestment and disintentives to use fossil fuels, investments don’t move into developing alternative energy, outside of niche applications, solar and wind are seen as unprofitable and not researched, more research is put into fossil fuels, making them cheaper making the bar to entry higher for alternatives, policy makers are less willing to impose regulations on fossil fuels since the costs of doing so are greater (since alternatives are more expensive) further slowing development.
You can look at places in the US where attitudes towards fossil fuel are different and investment is seen as more acceptable and you see exactly that.
This is just not true. AI is being used as a substitute. Sometimes for more specialized SaaS solutions, sometimes for reducing the number of HR staff, and sometimes replacing interns assigned to doc review, etc. You can argue it has a qualitative advantage over substitutes, sometimes it has a clear disadvantage even and trade offs.