Abhishek Rao's blog

Here is an ethics thought experiment that explores personal connection in altruism, similar to Peter Singer's thought experiments. Suppose you were given these two choices Choice A: You can give any single person you know (other than yourself) 2 million $ openly. Choice B: You can give 200 million of the poorest people on the earth 1 $ each, anonymously.  If one were a sensing and feeling type of person, then the choice would be obviously A. You could give your loved one 2 million dollars and that would be enough to make them financially independent for the rest of their life (assuming they use the money judiciously). You would be interacting with them regularly, you know them well for a long time and will continue seeing them be happy for the rest of your life. This is similar to the ending in The Last of Us. If one were logical, intuitive and truly selfless then choice B is clearly the better choice. Poor people across the globe would benefit many orders of magnitude more than in...

Originally posted in https://ideafair.bearblog.dev/social-network-and-trust/ One of the main issues with the current social networks is the issue of favoring appeal over truth. Posts that appear good get likes, regardless of whether they are actually true or not. Thus they are susceptible to people's biases. This leads to the problem of false news travelling faster than true news. Our current recommender systems promote posts that get a higher number of likes from people and thus this gets amplified. Instead we need to change our recommender systems to value truth over likings. Perhaps we can associate each user with a truth score based on how true their past predictions were and then promote posts from truthful people. This is similar to the ideas in the book "Signal and Noise" by Nate Silver. We can have a system where people can make testable predictions, something like https://longbets.org/ and develop a truth score for each user. Then the social network should promot...