I absolutely agree that this is a good way to look at things. For example, the 3 minutes per person per day moloch I referenced was a hypothetical bad future that a lot of people worried about, but as it turned out, the capabilities to use gradient descent to steer human behavior in measurable directions may have resulted in a good outcome, where the superior precision allows them to reduce quit rates, but balancing that optimization with optimizing for preventing overuse. This featured heavily in the Facebook files; whenever Facebook encountered some awful problem, the proposed solution was allegedly “we need better AI so we can optimize for things like that not happening”.
I don’t want to dismiss the potentially-high probability that things will just go fine; in fact, I actually covered that somewhat:
Facebook and the other 4 large tech companies (of whom Twitter/X is not yet a member due to vastly weaker data security) might be testing out their own pro-democracy anti-influence technologies and paradigms, akin to Twitter/X’s open-sourcing its algorithm, but behind closed doors due to the harsher infosec requirements that the big 5 tech companies face. Perhaps there are ideological splits among executives e.g. with some executives trying to find a solution to the influence problem because they’re worried about their children and grandchildren ending up as floor rags in a world ruined by mind control technology, and other executives nihilistically marching towards increasingly effective influence technologies so that they and their children personally have better odds of ending up on top instead of someone else.
I’m just advocating for being prepared both for the good outcome and the bad one. I think that the 2020s will be a flashpoint for this, especially if it’s determined that an AI pause really is the minimum ask for humanity to survive (which is a reasonable proposition).
I absolutely agree that this is a good way to look at things. For example, the 3 minutes per person per day moloch I referenced was a hypothetical bad future that a lot of people worried about, but as it turned out, the capabilities to use gradient descent to steer human behavior in measurable directions may have resulted in a good outcome, where the superior precision allows them to reduce quit rates, but balancing that optimization with optimizing for preventing overuse. This featured heavily in the Facebook files; whenever Facebook encountered some awful problem, the proposed solution was allegedly “we need better AI so we can optimize for things like that not happening”.
I don’t want to dismiss the potentially-high probability that things will just go fine; in fact, I actually covered that somewhat:
I’m just advocating for being prepared both for the good outcome and the bad one. I think that the 2020s will be a flashpoint for this, especially if it’s determined that an AI pause really is the minimum ask for humanity to survive (which is a reasonable proposition).