English

Robustness to fundamental uncertainty in AGI alignment

Artificial Intelligence 2020-02-18 v2

Abstract

The AGI alignment problem has a bimodal distribution of outcomes with most outcomes clustering around the poles of total success and existential, catastrophic failure. Consequently, attempts to solve AGI alignment should, all else equal, prefer false negatives (ignoring research programs that would have been successful) to false positives (pursuing research programs that will unexpectedly fail). Thus, we propose adopting a policy of responding to points of philosophical and practical uncertainty associated with the alignment problem by limiting and choosing necessary assumptions to reduce the risk of false positives. Herein we explore in detail two relevant points of uncertainty that AGI alignment research hinges on---meta-ethical uncertainty and uncertainty about mental phenomena---and show how to reduce false positives in response to them.

Keywords

Cite

@article{arxiv.1807.09836,
  title  = {Robustness to fundamental uncertainty in AGI alignment},
  author = {G Gordon Worley},
  journal= {arXiv preprint arXiv:1807.09836},
  year   = {2020}
}
R2 v1 2026-06-23T03:14:34.516Z