Let's say you are interviewing a candidate for a job. In casual conversation, the candidate mentions that he is a member of a rather old and prestigious country club. You've never heard the name of the club before.
You look up the country club afterwards, and are surprised by what you read. The club refuses membership to homosexuals. It revokes the membership of couples who use birth control. Leadership positions are reserved to unmarried males.
The candidate is otherwise competent. Under what conditions would you hire him? Would you want a law passed banning hiring discrimination based on country club membership?
(The country club is analogous to a nicer version of the Catholic church. I left out a couple bad things.)
Religious discrimination is illegal in many parts of the world, and I think that's probably a good thing. Still, keeping this at the object level (no meta-rules or veils of ignorance) it seems to me that discriminating against religious people is fine. I'm curious what other people think.
On further reflection, this post highlights an important omission in TDT (aka the categorical imperative): how do you judge the similarity of other agents to you? If each of your actions establishes a universal law, exactly how wide and universal does it become? You may think of yourself as optimizing your little corner of the world, because you feel uncomfortable around some people; or you may think of yourself bringing about a brave new world where the accursed papists must starve because nobody hires them; or maybe a not-so-brave new world where people are routinely denied jobs for ideological reasons. Right now I see no rational arguments to choose between these different perspectives.
This is one of the central open problems in our branch of decision theory. TDT is actually even weaker: it allows to express acausal dependencies, but figuring out what acausally depends on what is not part of it. Thus, in Newcomb's problem, TDT doesn't really insist on constructing the correct causal graph with platonic agent in control, even though it informally lays out guidelines that suggest that particular graph to be a good idea (for example, two identical computations are not independent, hence causal decision theorist's graph is in error).
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