Maths and philosophy undergrad. Inter alia interested in decision theory, formal epistemology, s-risk reduction.
Related post (which I don't think is mentioned here): Longtermism, risk, and extinction by Richard Pettigrew.
and then he just surprised us by posting.
Judging from the email in this comment, it seems like you were aware that Ben intended to post some time before the post appeared on the Forum and LW, which seemingly contradicts what you are saying here.
Seems like you are thinking of a case without full introspection. Both Eells and Ahmed provide convincing tickle defences in this case as well. See Oesterheld (2022) for a review of the arguments (especially sections 6.3 and 6.4).
As Ahmed notes (chapter 4.3.1), if the lesion doesn't work through your beliefs and desires, smoking is not a genuine option, and so this is not an argument against evidentialism.
Evidential decision theory would say that you shouldn’t smoke because smoking gives you evidence that you’ll have a shorter life.
Not so important, but I feel obliged to mention that this has been forcefully argued against by e.g. Eells (1982) and Ahmed (2014). In short, smoking will plausibly be preceded by a desire to smoke, and at the point of observing your own desire to do so, smoking or not does not provide additional evidence of cancer.
Related paper: A bargaining-theoretic approach to moral uncertainty.
There is also the evidentialist consideration (see e.g. section 5 of Leslie ): to cast your vote plausibly gives you evidence that others decided to do so as well. The correlation between you and any given person is of course very low, but if the population is sufficiently large then the effect could be substantial.
However, this is not necessarily an argument in favour of voting since you might be more correlated with people who would vote for the other party.
Also, Pooling: A User’s Guide by the same authors. Abstract (where Upco is one specific multiplicative method):
We often learn the credences of others without getting to hear the evidence on which they’re based. And, in these cases, it is often unfeasible or overly onerous to update on this social evidence by conditionalizing on it. How, then, should we respond to it? We consider four methods for aggregating your credences with the credences of others: arithmetic, geometric, multiplicative, and harmonic pooling. Each performs well for some purposes and poorly for others. We describe these in Sections 1-4. In Section 5, we explore three specific applications of our general results: How should we understand cases in which each individual raises their credences in response to learning the credences of the others (Section 5.1)? How do the updating rules used by individuals affect the epistemic performance of the group as a whole (Section 5.2)? How does a population that obeys the Uniqueness Thesis perform compared to one that doesn’t (Section 5.3)?
A recent and related paper: Jeffrey Pooling by Pettigrew and Weisberg. Abstract (bold emphasis mine):
How should your opinion change in response to that of an epistemic peer? We show that the pooling rule known as “upco” is the unique answer satisfying some natural desiderata. If your revised opinion will impact your opinions on other matters by Jeffrey conditionalization, then upco is the only standard pooling rule that ensures the order in which peers are consulted makes no difference. Popular proposals like linear pooling, geometric pooling, and harmonic pooling cannot boast the same. In fact, no alternative to upco can, if it possesses four minimal properties—properties which these proposals all share.
Related: Neartermists should consider AGI timelines in their spending decisions by Tristan Cook.