Thread: My problem with this critique has always been that the actual point of most academic presentations of the problem since the first article-length discussion of it by Judith Jarvis Thomson is precisely to demonstrate that it *isn't* true that consequences justify murder! https://twitter.com/NathanJRobinson/status/1297368104650055681

Read the article! Thomson is precisely saying that calculations about numbers of people saved and killed *can't* justify actively intervening in a situation to take lives. She agrees with Robinson and Rennix.

https://learning.hccs.edu/faculty/david.poston/phil1301.80361/readings-for-march-31/JJ%20Thomson%20-%20Killing-%20Letting%20Die-%20and%20the%20Trolley%20Problem.pdf

It was first formulated by Philippa Foot as a throwaway example in a discussion of other issues (her overall point in context was to argue that Catholic moral teachings prohibit abortion were misguided) but as far as I know the JJT article is the first extended discussion of it.

And in 99% of cases where philosophy profs start drawing trolley tracks on the whiteboard for ethics classes, their point is to present it as a *problem* for utilitarianism. Like, you do the first version where most people have a utilitarian reaction:

https://chaospet.com/30-the-trolley-case/

...and then the punchline is the second version that's precisely designed to elicit an extremely anti-utilitarian "good Lord that's just murder" reaction:

https://chaospet.com/31-trolley-problem-again/

This is a way of getting students to *question* utilitarianism so they take e.g. Kant more seriously.

If your impression of the Trolley Problem were derived from watching the Good Place and reading trolley memes on Facebook you might get the impression that the whole thing is an exercise to get people to be willing to make steely-eyed calculations about lives lost and saved, but:

Trust me when I say that academic discussion of it and use of it in classroom contexts usually has exactly the opposite point. I'm a fan of both authors but this all feels a little bit like accusing statisticians of not understanding that correlation=/=causation.