Human-Complete Problems !!

I want to explore a particular bunny trail: the relationship between being human and the ability to solve infinite game problems in the sense of James Carse. I think this leads to an interesting perspective on the meaning and purpose of AI.

The phrase human complete is constructed via analogy to the term AI complete, an ambiguously defined class of problems, including machine vision and natural language processing, that is supposed to contain the hardest problems in AI.

That term itself is a reference to a much more precise one used in computer science: NP complete, which is a class of the hardest problems in computer science in a certain technical sense. NP complete is a subset of a larger class known as NP, which is the set of all problems for a certain class of non-God-level computers. It contains another subset called P, which are easy problems in a related technical sense.

It is not known whether P and NP complete are proper subsets of NP. If you can prove that P≠NP, you will win a million dollars. If you can prove P=NP, the terrorists will win and civilization will end. In the diagram above, if you replace the acronyms FG, IG and HC with P, NP and NP Complete, you will get the diagram used to explain computational complexity in standard textbooks.

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The idea is a natural extension of Moravec’s paradox into the negative range. If the apparent hard problems are easy and the apparent easy problems are hard, perhaps the set of meaningful problems does not stop at apparent zero-hardness problems like “do nothing for one clock cycle.”

Perhaps there are anti-hard problems that require negatively increasing amounts of stupidity below zero — or active anti-intelligence, rather than mere lack of intelligence — to solve.

Anti-intelligence in this sense is not really stupidity. Stupidity is the absence of positive intelligence, evidenced by failure to solve challenging problems as rationally as possible. Anti-intelligence is the ability to imaginatively manufacture and inflate non-problems into motives containing absurd amounts of “meaning,” and choosing to pursue them (so lack of anti-intelligence, such as an inability to find humor in a juvenile joke, would be a kind of anti-stupidity).

Perhaps this negative range is what defines human. Perhaps some animals go into this negative range (there have been recent reports about spirituality in chimps), but so far I haven’t seen any non-human entity suffer from, and beat, something like Precious Snowflake syndrome.

It’s pretty easy to get AIs to mimic low, but positive levels of human stupidity, like losing a game of tic-tac-toe, or forgetting to check your mirrors before changing lanes. I can write a program capable of losing tic-tac-toe in 10 minutes.

If you can get your AI anti-intelligent enough to suffer boredom, depression and precious-snowflake syndrome, then we’ll start getting somewhere.

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