An Anthropic Argument against the Future Existence of Superintelligent Artificial Intelligence
This addresses a foundational problem in AI safety and philosophy for researchers concerned with existential risks from AI, but it is incremental as it builds on existing anthropic principles like SSA and SSSA.
The paper tackles the problem of predicting the future existence of superintelligent AI by introducing the Super-Strong Self-Sampling Assumption (SSSSA), an anthropic principle that weights observer samples by cognitive size, and argues that this reduces the likelihood of superintelligent AI being created.
This paper uses anthropic reasoning to argue for a reduced likelihood that superintelligent AI will come into existence in the future. To make this argument, a new principle is introduced: the Super-Strong Self-Sampling Assumption (SSSSA), building on the Self-Sampling Assumption (SSA) and the Strong Self-Sampling Assumption (SSSA). SSA uses as its sample the relevant observers, whereas SSSA goes further by using observer-moments. SSSSA goes further still and weights each sample proportionally, according to the size of a mind in cognitive terms. SSSSA is required for human observer-samples to be typical, given by how much non-human animals outnumber humans. Given SSSSA, the assumption that humans experience typical observer-samples relies on a future where superintelligent AI does not dominate, which in turn reduces the likelihood of it being created at all.