My comment was not clear and I wrote it poorly, sorry! I will edit parts of it.
I'm not really sure why you think the refusal to decouple can't co-exist with people wanting clarity?
My objection to "EA posing more questions than answers" is that a lot of what people are objecting to are the answers that many people take in the movement (eg: future people matter a ton, AI x-risk is a serious issue, etc.). People also seem to be upset about its overconfidence rather than its underconfidence.
The thing I was trying to gesture at with "decoupling" was that people find many thought experiments very weird and counterintuitive (eg: torture vs dust specks, strong longtermist thought experiments). Then, people often not separating them out from questions like "is AI a potential existential threat" or "is factory farming bad" which aren't too different. I'm now unsure if this is related to your initial point.
And I'm also not sure why you think philosophers hating EA means people don't hate EA the same way they hate philosophers? I think a lot of philosophers hate each other as well, and those same people get hated on by outsiders for philosophy-vibes reasons. Unfortunately hatred is not a zero-sum game.
This explanation is interesting, but imo its more of a minor factor than a major factor. It seems to me that the dislike for EA doesn't seem like a respectful disagreement but much more of a strong dislike. However, I'm not super confident about this since I'm not super familiar with how academic philosophers relate to one another.
I think #1 is not right (ETA: I explain in my below comment). I think there's a somewhat related problem where people are refusing to decouple. Taking philosophy seriously can lead you to beliefs that, on first sight, appear incredibly strange (eg: strong longtermism).
#2 and #3 seem quite likely to me.
But these critiques presumably can't be exclusively because of philosophers, since unfortunately academic philosophers seem to dislike EA (on aggregate)[1]
Copying Mitchell Porter's comment from LessWrong (which I agree with)
I think an anti-anti-aging movement is more likely, on the model of the anti-data-center movement: "stop the rich from creating a sinister transhumanist world"...
I would add a few points for why this is unlikely:
The average person tends to be far more risk-averse than EAs/rationalists/Bay Area people, so people would probably be willing to gamble for even 25% death, 75% utopia where you live much longer
People often have a strong status quo bias which leads them to want to live a normal life, not the singularity.
I think religion often pushes back against transhumanism, especially if people cease to have jobs
Yes, I have seen the pictures too... it is awful and moving. Luckily, it is already being well-funded (as is common in such situations). The USA alone for example has pledged $150M in aid. Therefore, I doubt that it is one of the best causes to donate to for impartial scope-sensitive impact. If someone is seriously moved by this (as with other causes), I would encourage them to donate to other causes that are more neglected and use these experiences as a way to stay in touch with why they're donating.
Thanks! This post was interesting and helped clarify my thoughts on some relevant issues. Still, I want to push in the other direction.
I think historical data poses its own sets of flaws and limitations -- and there are certain questions that it cannot easily answer. Therefore, I still think one should from philosophical/conceptual analysis since there's often no better approach to answering the questions. To be concrete, here are two main categories of questions that AI forecasting is looking to answer and where conceptual analysis must be used.
1. Timelines and capabilities forecasting Here, I think the historical data about other technologies and their diffusion is pretty good to predict AI's diffusion in the economy.
But to answer questions like "will AI automate all human-level cognitive labor", I think it would be dubious to only look through the history of other transformative technology and conclude "no because electricity/TV/internet/phones did not". There is a much clearer mechanism for AI to automate these tasks than any of those past technologies, and therefore the historical data just isn't that persuasive to me.
2. What risks does TAI pose and how should we mitigate them Here I think conceptual analysis is much more valuable. There are benefits of doing some economic modelling to see how to react to issues like job loss etc., especially for the near-term. But for questions like "how likely is human disempowerment from powerful AI", I don't see any good alternative to conceptual thinking. I really like Forethought's post about what to focus on here which encompasses non-alignment problems and basically focuses on high level strategic questions since those are easier to predict:
Of course, there are lots of possible issues with conceptual thinking that you mention in the post. Where I'm at is just accepting that no approach is especially good and that we should keep some amount of epistemic humility in our arguments since it's very easy to be deeply confused in both directions.
Thanks for sharing! I feel the same way towards Singer's thought experiment. I personally find it much more motivating to use Joe Carlsmith's version of it.
Suppose that I am setting off to walk in the forest on a crisp fall afternoon — something I’ve been looking forward to all week. As I near the forest, I notice, far away, what looks like some sort of commotion down by the river, off of my walking route, though I can’t see very clearly. I consider going to see what’s going on, but the light is fading, so I decide to continue on my way.
I learn later that while I was walking, a man in his early forties drowned in that river. He was pinned under some sort of machinery. Five other people were there, including his wife and son, but they weren’t strong enough to lift the machinery by themselves. One extra person might have made the difference.
(Here I try to imagine vividly what it was like trying to save him — his wife desperate, weeping, pulling at him, his own eyes frantic, the fear and chaos, the eventual despair– and the pain of his absence afterwards; and the counterfactual world in which instead, another person arrived in time to help, and he lives.)
The intuition this pumps for me is: I wish I’d gone to the river. Importantly, though, at least for me, the case leaves the focus of attention on the drowned man himself, and the clear sense in which a beautiful walk would be worth trading, cancelling, disappearing, to grant him multiple decades of life, and his family multiple decades of time together. The question of whether my choice to continue walking was wrong, though not entirely absent, is less salient. That is, for me (at least as a thought experiment — who knows how I’d feel if something like this really happened), the case touches most centrally into a feeling of regret, rather than guilt. I wish I could go back, and create a world where I had one fewer beautiful walk, and he lived.
My comment was not clear and I wrote it poorly, sorry! I will edit parts of it.
My objection to "EA posing more questions than answers" is that a lot of what people are objecting to are the answers that many people take in the movement (eg: future people matter a ton, AI x-risk is a serious issue, etc.). People also seem to be upset about its overconfidence rather than its underconfidence.
The thing I was trying to gesture at with "decoupling" was that people find many thought experiments very weird and counterintuitive (eg: torture vs dust specks, strong longtermist thought experiments). Then, people often not separating them out from questions like "is AI a potential existential threat" or "is factory farming bad" which aren't too different. I'm now unsure if this is related to your initial point.
This explanation is interesting, but imo its more of a minor factor than a major factor. It seems to me that the dislike for EA doesn't seem like a respectful disagreement but much more of a strong dislike. However, I'm not super confident about this since I'm not super familiar with how academic philosophers relate to one another.
I think #1 is not right (ETA: I explain in my below comment). I think there's a somewhat related problem where people are refusing to decouple. Taking philosophy seriously can lead you to beliefs that, on first sight, appear incredibly strange (eg: strong longtermism).
#2 and #3 seem quite likely to me.
But these critiques presumably can't be exclusively because of philosophers, since unfortunately academic philosophers seem to dislike EA (on aggregate)[1]
I think a lot of these critiques from philosophers seem to rely on weak arguments, but nonetheless they exist
Copying Mitchell Porter's comment from LessWrong (which I agree with)
I would add a few points for why this is unlikely:
Yes, I have seen the pictures too... it is awful and moving. Luckily, it is already being well-funded (as is common in such situations). The USA alone for example has pledged $150M in aid. Therefore, I doubt that it is one of the best causes to donate to for impartial scope-sensitive impact. If someone is seriously moved by this (as with other causes), I would encourage them to donate to other causes that are more neglected and use these experiences as a way to stay in touch with why they're donating.
(Copying my comment from Substack)
Thanks! This post was interesting and helped clarify my thoughts on some relevant issues. Still, I want to push in the other direction.
I think historical data poses its own sets of flaws and limitations -- and there are certain questions that it cannot easily answer. Therefore, I still think one should from philosophical/conceptual analysis since there's often no better approach to answering the questions. To be concrete, here are two main categories of questions that AI forecasting is looking to answer and where conceptual analysis must be used.
1. Timelines and capabilities forecasting
Here, I think the historical data about other technologies and their diffusion is pretty good to predict AI's diffusion in the economy.
But to answer questions like "will AI automate all human-level cognitive labor", I think it would be dubious to only look through the history of other transformative technology and conclude "no because electricity/TV/internet/phones did not". There is a much clearer mechanism for AI to automate these tasks than any of those past technologies, and therefore the historical data just isn't that persuasive to me.
2. What risks does TAI pose and how should we mitigate them
Here I think conceptual analysis is much more valuable. There are benefits of doing some economic modelling to see how to react to issues like job loss etc., especially for the near-term. But for questions like "how likely is human disempowerment from powerful AI", I don't see any good alternative to conceptual thinking. I really like Forethought's post about what to focus on here which encompasses non-alignment problems and basically focuses on high level strategic questions since those are easier to predict:
Of course, there are lots of possible issues with conceptual thinking that you mention in the post. Where I'm at is just accepting that no approach is especially good and that we should keep some amount of epistemic humility in our arguments since it's very easy to be deeply confused in both directions.
Thanks for sharing! I feel the same way towards Singer's thought experiment. I personally find it much more motivating to use Joe Carlsmith's version of it.