Interested in math puzzles, fermi estimation, strange facts about the world, toy models of weird scenarios, unusual social technologies, and deep dives into the details of random phenomena.
Working on the pretraining team at Anthropic as of October 2024; before that I did independent alignment research of various flavors and worked in quantitative finance.
I asked Claude to research it and looked at some of the studies it turned up.
Ma et al administer (nothing, MDMA, DXM 5 minutes before MDMA) to 3 monkeys each and use radioisotopes to look for sertonergic abnormality 24 and 30 months after administration. The DXM sure looks like it helps but also there are literally just three monkeys in this image, maybe the middle guy just didn't have very many serotonin transporters to start with?? Maybe I can email the authors and get the raw data.
(Also they give these monkeys a lot of DXM - these are not cough suppressant dosages, the monkeys are probably tripping balls even without the MDMA. And DXM+MDMA is generally considered a dangerous combination - if you look up trip reports on Erowid they reliably describe having a bad time that lasts for days - so I would not try this on humans.)
Malberg et al find that after giving rats high-dose MDMA (recreational dose would be like 1mg/kg and they do 20 or 40) and autopsying brains 2 weeks later, serotonin levels were much lower on the rats who spent their MDMA trip in a high-temperature room than in a low-temperature room. 8 rats for each of the 18 experimental conditions.
Aguirre et al find that alpha-lipolic acid cuts serotonin decrease in half a week after administration, though they used a temperature-controlled room at 22ºC which the above study claims doesn't decrease serotonin, so idk. They also use 8 rats per experimental condition, but they only have 4 such conditions so I trust them a bit less.
Shankaran et al find that vitamin C substantially decreases 2,3-DHBA during the trip but don't look at effects afterwards.
As far as Claude could tell, no one's ever done human RCTs for MDMA mitigations and looked at cognitive or neurochemical effects afterwards.
Yeah, sorry - I agree that was a bit sloppy of me. I think it is very reasonable to accuse people working at major AI labs of something like negligence / willful ignorance, and I agree that can be a pretty serious moral failing (indeed I think it's plausibly the primary moral failing of many AI lab employees). My objection is more to the way the parent comment is connoting "evil" just from one's employer leading to bad outcomes as if those outcomes are the known intent of such employees.
I think this is a pretty unhelpful frame. Most people working at an AI lab are somewhere between "person of unremarkable moral character who tells themselves a vague story about how they're doing good things" and "deeply principled person trying their best to improve the world as best they can". I think working at an AI lab requires less failure of moral character than, say, working at a tobacco company, for all that the former can have much worse effects on the world.
There are a few people I think it is fair to describe as actively morally bad, and willfully violating deontology - it seems likely to me that this is true of Sam Altman, for instance - but I think "evil" is just not a very helpful word here, will not usefully model the actions of AI lab employees, and will come across as obviously disingenuous to anyone who hears such rhetoric if they actually interact with any of the people you're denigrating. If you had to be evil to end the world, the world would be a lot safer!
I think it's fine and good to concentrate moral opprobrium at specific actions people take that are unprincipled or clear violations of deontology - companies going back on commitments, people taking on roles or supporting positions that violate principles they've previously expressed, people making cowardly statements that don't accurately reflect their beliefs for the sake of currying favor. I think it's also fine and good to try and convince people that what they're doing is harmful, and that they should quit their jobs or turn whistleblower or otherwise change course. But the mere choice of job title is usually not a deontology violation for these people, because they don't think it has the harms to the world you think it does! (I think at this point it is probably somewhat of a deontological violation to work in most roles at OpenAI or Meta AI even under typical x-risk-skeptical worldviews, but only one that indicates ethical mediocrity rather than ethical bankruptcy.)
(For context, I work on capabilities at Anthropic, because I think that reduces existential risk on net; I think there's around a 25% chance that this is a horrible mistake and immensely harmful for the world. I think it's probably quite bad for the world to work on capabilities at other AI labs.)
Assorted followup thoughts:
Suppose you want to collect some kind of data from a population, but people vary widely in their willingness to provide the data (eg maybe you want to conduct a 30 minute phone survey but some people really dislike phone calls or have much higher hourly wages this funges against).
One thing you could do is offer to pay everyone dollars for data collection. But this will only capture the people whose cost of providing data is below , which will distort your sample.
Here's another proposal: ask everyone for their fair price to provide the data. If they quote you , pay them to collect the data with probability , or with certainty if they quote you a value less than . (If your RNG doesn't return yes, do nothing.) Then upweight the data from your randomly-chosen respondents in inverse proportion to the odds that they were selected. You can do a bit of calculus to see that this scheme incentivizes respondents to quote their fair value, and will provide an expected surplus of dollars to a respondent who disvalues providing data at .
Now you have an unbiased sample of your population and you'll pay at most dollars in expectation if you reach out to people. The cost is that you'll have a noisier sample of the high-reluctance population, but that's a lot better than definitely having none of that population in your study.
Coming to this comment late, but off the cuff takes:
Thanks for writing this up! Two questions I'm curious if you have good data on:
I agree with you that a typical instance of working at an AI lab has worse consequences in expectation than working at a tobacco company, and I think that for a person who shares all your epistemic beliefs to work in a typical role at an AI lab would indeed be a worse failure of moral character than to work at a tobacco company.
I also agree that in many cases people at AI labs have been exposed at least once to arguments which, if they had better epistemics and dedicated more time to thinking about the consequences of their work, could have convinced them that it was bad for the world for them to do such work. And I do think the failure to engage with such arguments and seriously consider them, in situations like these, is a stain on someone's character! But I think it's the sort of ethical failure which a majority of humans will make by default, rather than something indicative of remarkably bad morality.
I just don't think this sort of utilitarian calculus makes sense to apply when considering the actions of people who don't share the object-level beliefs at hand! I think people who worked to promulgate communism in the late 19th century were not unusually evil, for instance.