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I could not agree more. Taking two of the things you said, I would take it one step further. Not about just the direction, but about the structure/gameboard not only when it gets close, but mostly on the way there [0]. About ensuring most researchers and companies have the most incentive for a good outcome. (This ties back with guaranteed basic income, so that people can work on this unconstrained by salaries and papers citation metrics. Or stealing researchers from Google et al to AI safety, without overinflating salaries. Elon and company should be (seems they are?) dropping as much as needed on this (not just money, but PR and status as well).) Naturally, gym, universe, etc can provide more leverage to do all of this, otherwise researchers feel more compelled to join Google/Amazon/etc, just for the raw computing power and software infrastructure (the data advantage is largely overplayed for advertising purposes; what's useful is the GPU clusters for hyper parameter sweeps (of course, in RL the data reappears as an advantage if there is no open gym)). I realize some of the examples above are naive or incomplete, but they serve mostly as an example to illustrate the point. In the blog you mention balancing managing people and technology, and I could not agree more. The AI safety problem will have the best odds if individuals are incentivized to contribute in their own short term selfish reward way. Specially among extremely intelligent and ambitious people, the danger of self denial is quite present, one can convince oneself that this is actually in everyone's best interest, when in fact one is looking for the always needed social and intellectual validation. Please do not underestimate this, and try to find ways to counter it. Edit: This is also related to Conway's Law [0], as I think you make an allusion to (values of inventors). [0] http://neuralnetworksanddeeplearning.com/chap6.html |