Robustness to fundamental uncertainty in AGI alignment

July 25, 2018 Β· Declared Dead Β· πŸ› arXiv.org

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Authors G Gordon Worley arXiv ID 1807.09836 Category cs.AI: Artificial Intelligence Citations 4 Venue arXiv.org Last Checked 4 months ago
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.
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