casens

But there’s an additional problem here. People overestimate foreign aid, and these polling methods exaggerate how much they overestimate. In the KFF data, the majority of respondents said it was below 20%, and the largest decile by far was 0-10%. KFF said that average was 26%, but their own data show that this isn’t what most people actually believe; it's an artifact of using the wrong statistic.

the KFF data shows that the median respondent thinks foreign aid is somewhere in the 11-20% of the budget, so reporting the average is roughly 2.4 to 1.3 times an overestimate of the median belief.  but reporting the average is what most people do, because most... (read more)

your entire analysis is broken in that you assume that an elo rating is something objective like an atomic weight or the speed of light. in reality, an elo rating is an estimation of playing strength among a particular pool of players.

the problem that elo was trying to solve was, if you have players A and B, who have both played among players C through Q, but A and B have never played each other, can you concretely say whether A is stronger than B? the genius of the system is that you can, and in fact, the comparison of 2 scores gives you a probability of whether A will... (read more)

The True Believers hypothesis rings false because that would be a frankly ridiculous belief to hold. Sometimes people profess ridiculous things, but very few of them put their money where their mouth is on prediction markets. [1]

1. I’ve seen some pretty mispriced markets. At one point in 2019, PredictIt had Andrew Yang at 16% to win the Democratic presidential primary. And in 2020, Donald Trump was about 16% to become president even after he had lost the election. But the sorts of people who bet on prediction markets are not the sorts of fundamentalist Christians who think that Jesus Christ has a high chance of returning this year.

yes, no one would put... (read more)

this is a fair response, and to be honest i was skimming your post a bit. i do think my point somewhat holds, that there is no "intelligence skill tree" where you must unlock the level 1 skills before you progress to level 2.

i think a more fair response to your post is:

1. companies are trying to make software engineer agents, not bloggers, so the optimization is towards the former.
2. making a blog that's actually worth reading is hard. no one reads 99% of blogs.
3. i wouldn't act so confident that we aren't surrounded by LLM comments and posts. are you really sure that everything you're reading is from a human?

Surely it would be exceptionally good at those kinds of writing, too, right?

surely an LLM capable of writing A+ freshman college papers would correctly add two 2-digit numbers?  surely an AI capable of beating grandmasters in chess would be able to tutor a 1000 elo player to a 1500 elo or beyond?  surely an AI capable of answering questions at a university level in diverse subjects such as math, coding, science, law, would be able to recursively improve itself and cause an intelligence explosion?  surely such an AI would at least be able to do a simple task like unload a dishwasher without breaking a dish?

i think surely it should be obvious... (read more)

In some sense, the Agent Foundations program at MIRI sees the problem as: human values are currently an informal object. We can only get meaningful guarantees for formal systems. So, we need to work on formalizing concepts like human values. Only then will we be able to get formal safety guarantees.

unless i'm misunderstanding you or MIRI, that's not their primary concern at all:

Another way of putting this view is that nearly all of the effort should be going into solving the technical problem, "How would you get an AI system to do some very modest concrete action requiring extremely high levels of intelligence, such as building two strawberries that are completely identical