My name is Mikhail Samin (diminutive Misha, @Mihonarium on Twitter, @misha in Telegram).
Humanity’s future can be huge and awesome; losing it would mean our lightcone (and maybe the universe) losing most of its potential value.
My research is currently focused on AI governance and improving the understanding of AI and AI risks among stakeholders. I also have takes on what seems to me to be the very obvious shallow stuff about the technical AI notkilleveryoneism; but many AI Safety researchers told me our conversations improved their understanding of the alignment problem.
I believe a capacity for global regulation is necessary to mitigate the risks posed by future general AI systems. I’m happy to talk to policymakers and researchers about ensuring AI benefits society.
I took the Giving What We Can pledge to donate at least 10% of my income for the rest of my life or until the day I retire (why?).
In the past, I’ve launched the most funded crowdfunding campaign in the history of Russia (it was to print HPMOR! we printed 21 000 copies =63k books) and founded audd.io, which allowed me to donate >$100k to EA causes, including >$60k to MIRI.
[Less important: I’ve also started a project to translate 80,000 Hours, a career guide that helps to find a fulfilling career that does good, into Russian. The impact and the effectiveness aside, for a year, I was the head of the Russian Pastafarian Church: a movement claiming to be a parody religion, with 200 000 members in Russia at the time, trying to increase separation between religious organisations and the state. I was a political activist and a human rights advocate. I studied relevant Russian and international law and wrote appeals that won cases against the Russian government in courts; I was able to protect people from unlawful police action. I co-founded the Moscow branch of the “Vesna” democratic movement, coordinated election observers in a Moscow district, wrote dissenting opinions for members of electoral commissions, helped Navalny’s Anti-Corruption Foundation, helped Telegram with internet censorship circumvention, and participated in and organized protests and campaigns. The large-scale goal was to build a civil society and turn Russia into a democracy through nonviolent resistance. This goal wasn’t achieved, but some of the more local campaigns were successful. That felt important and was also mostly fun- except for being detained by the police. I think it’s likely the Russian authorities will imprison me if I ever visit Russia.]
It’s reasonable to consider two agents playing against each other. “Playing against your copy” is a reasonable problem. ($9 rocks get 0 in this problem, LDTs probably get $5.)
Newcomb, Parfit’s hitchhiker, smoking, etc. are all very reasonable problems that essentially depend on the buttons you press when you play the game. It is important to get these problems right.
But playing against LDT is not necessarily in the “fair problem class” because the game might behave differently depending on your algorithm/on how you arrive at taking actions, and not just depending on your actions.
Your version of it- playing against an LDT- is indeed different from playing against a game that looks at whether we’re an alphabetizing agent and pick X instead of Y because X<Y and not because we looked at the expected utility: we would want LDT to perform optimally in this game. But the reason LDT-created-rock loses to a natural rock here isn’t fundamentally different from the reason LDT loses to an alphabetizing agent in the other game and it is known that you can construct a game like that where LDT will lose to something else. You can make the game description sound more natural, but I feel like there’s a sharp divide between the “fair problem class” problems and others.
(I also think that in real life, where this game might play out, there isn’t really a choice we can make, to make our AI a $9 rock instead of an LDT agent; because when we do that due to the rock’s better performance in this game, our rock gets slightly less than $5 in EV instead of getting $9; LDT doesn’t perform worse than other agents we could’ve chosen in this game.)