Executable philosophy

'Finishable philosophy' is Eliezer Yudkowsky's term for philosophical reasoning aimed at arriving at a correct answer to some question in time to build an AI, which requires trying to settle issues more than standard academic philosophy does.

Since many problems of philosophy have seemingly remained open for at least several centuries, if one of those philosophical problems seems to be important to AI, we cannot go on considering it using the same type of methodology that has been used for the last couple of centuries. Thus, the notion that we can resolve these problems, correctly, in time to resolve questions of AI design that seem to be dependent on them, is sometimes a source of skepticism by others about Yudkowsky's approach.

Finishable philosophy has several core concepts that render it distinct from philosophy as usually practiced in academia:

• It is acceptable to take reductionism, and computability of human thought, as a premise, and move on.
  • The presumption here is that the low-level mathematical unity of physics - the reducibility of complex physical objects into small, mathematically uniform physical parts, etctera - has been better established than any philosophical argument which purports to contradict them. Thus our question is "How can we reduce this?" rather than "Should this be reduced?"
  • Yudkowsky further suggests that things be reduced to a mixture of causal facts and logical facts.
• All philosophical issues can and should be rephrased as subquestions of some primary question about how to design an Artificial Intelligence.
  • E.g. rather than the central question being "What is goodness made out of?", we begin with the central question "What algorithm should we install into an AI to compute which actions to take?", and consider questions of "What is shouldness?" as they relate to this central question of AI design.
  • This imports the discipline of programming into philosophy. In particular, programmers learn that even if they have an inchoate sense of what a computer should do, when they actually try to write it out as code, they sometimes find that the code they have written fails (on visual inspection) to match up with their inchoate sense. In other words, many things that sound sensible as English sentences are revealed as confused as soon as we try to write it out as code.
• Faced with any philosophically confusing issue, our task is to identify what cognitive algorithm humans are executing which feels from the inside like this sort of confusion, rather than, as in conventional philosophy, to try to clearly define terms and then weigh up all possible arguments for all 'positions'.
  • This means that our central question is guaranteed to have an answer.
  • E.g., if the standard philosophical question is "Are free will and determinism compatible?" then there is not guaranteed to be any coherent thing we mean by free will, but it is guaranteed that there is in fact some algorithm running in our brain that, when faced with this particular question, generates a confusing sense of a hard-to-pin-down conflict.
  • This is not to be confused with merely arguing that, e.g., people evolved to feel like they had free will because that would cause them to try harder. This merely says, "I think evolution is the cause of our feeling that we have free will." It doesn't say what algorithm is actually running, or walk through the algorithm to see exactly how the sense of confusion arises.

A final trope of finishable philosophy is to not be intimidated by how long a problem has been left open. "Ignorance exists in the mind, not in reality; uncertainty is in the map, not in the territory; if I don't know whether a coin landed heads or tails, that's a fact about me, not a fact about the coin." There can't be any unresolvable confusions out there in reality. There can't be any inherently confusing substances in the mathematically lawful, unified, low-level physical process we call the universe. Any seemingly unresolvable or impossible question must represent a place where we are confused, not an actually impossible question out there in reality. This doesn't mean we can quickly or immediately solve the problem, but it does mean that there's some way to wake up from the confusing dream.

Although all confusing questions must be places where our own cognitive algorithms are running skew to reality, this, again, doesn't mean that we can immediately see and correct the skew; nor that it is "finishable philosophy" to insist in a very loud voice that a problem is solvable; nor that when a solution is presented we should immediately seize on it because the problem must be solvable and behold here is a solution. An important step in the method is to check whether there is any lingering sense of something that didn't get resolved; whether we really feel less confused; whether it seems like we could write out the code for an AI that would be confused in the same way we were; whether there is any sense of dissatisfaction; whether we have merely taken a photograph of the problem and chopped off all the parts that didn't fit in the photograph.

An earlier guide to some of the same ideas was the Reductionism Sequence. Finishable philosophy relies heavily on the skills for noticing confusion and noticing dissonance.