My name is Paul de Font-Reaulx, and I'm a PhD student in philosophy at the University of Michigan, Ann Arbor. I was previously at Oxford for my undergrad and masters. My research is primarily about motivation and rationality, drawing on computational cognitive science. I also work on ethics, decision theory, and AI safety. I'm currently funded by a grant from Open Philanthropy.
I tried avoiding including too much of my own experiences to avoid making the post too idiosyncratic, but I'm happy to elaborate on it!
I haven't had a period of working only 2h consistently, so I don't know how I would feel about that. However, during busy periods (e.g. if I have both teaching and service obligations) I think my main option to this would be to do nothing and then binge work during vacations, which I have done before and I would expect to be more common.
I have had periods of working 6 hours a day pretty consistently. What distinguished these periods I think was that I was very intrinsically motivated about the research and had minimal other obligations to navigate at the same time, so I naturally ended up just thinking about my work most of the time.
Today when I'm in a position with more regular events during my week, I find this harder. If I schedule 6 hours of work a day (which I did for a large part of last year), I often end up with the feeling that I don't have enough time to navigate other things. I have done this for a few weeks for particular projects, but find it difficult to have as a default working aim. I personally found 4h/day somewhat of a sweet spot, and have been doing that consistently for the last few weeks.
With that said, I have pretty low confidence that effective 6h/day cannot be achieved by others. My main aim with this post was to illustrate some ways in which a lower number achieves many of the benefits I was aspiring to with working more, and might at least for some have a substantial marginal impact on the costs of work. More generally, my experiences are obviously personal, and not something I would want people to put too much weight on.
Thanks for writing this, it was genuinely informative and interesting. I thought the description of urges as intrusive thoughts was especially helpful for developing empathy for addiction, and I think provides a useful contrast to the picture of irresistible urges, which I think dominates the common view. Hope the trajectory continues well, and kudos for sharing.
Thank you for organizing this! I have two questions. First, is there any update regarding when the official announcement will be made? Second, will essays submitted to other competitions, or for publication, be eligible? In other other words, is there any risk that submitting research elsewhere prior to the announcement of the competition will render it ineligible for the competition?
I'm not sure that this responds to the objection. Specifically, I think that we would need to clarify what is meant by 'risk' here. It sounds like what you're imagining is having credences over objective chances. The typical case of that would be not knowing whether a coin was biased or not, where the biased one would have (say) 90% chance of heads, and having a credence about whether the coin is biased. In such a case the hypotheses would be chance-statements, and it does make sense to have credences over them.
However, it's unclear to me whether we can view either the house example or AGI risk as involving objective chances. The most plausible interpretation of an objective chance usually involves a pretty clear stochastic causal mechanism (and some would limit real chances to quantum events). But if we don't want to allow talk of objective chances, then all the evidence you receive about Smith's electricity skills, and the probability that they built the house, is just more evidence to conditionalize your credences on, which will leave you with a new final credence over the proposition we ultimately care about: whether your house will burn down. If so, the levels wouldn't make sense, I think, and you should just multiply through.
I'm not sure how this affects the overall method and argument, but I do wonder whether it would be helpful to be more explicit what is on the respective axes of the graphs (e.g. the first bar chart), and what exactly is meant by risk, to avoid risks of equivocation.
Thank you for writing this, I found it very interesting and helpful. I have something between a belief and a hope that the antagonistic dynamics (which I agree are likely driven by the idea that AI safety is merely speculative) will settle down in the short-ish future as more empirical results emerge on the difficulty of training models with the intended goals (e.g. avoiding sycophancy) and get more widely appreciated. I think many people on the critical side still have the idea of AI safety as grounded largely in thought experiments only loosely connected to current technology.