Human safety problem
A human safety problem is a counterpart to an AI safety problem that appears in humans. For instance, distributional shift is an AI safety problem where an AI trained in one environment will behave poorly when deployed in an unfamiliar environment (for example, a cleaning robot that was trained in a factory environment may behave dangerously when it is used in an office, or a model that was trained on clean speech may handle noisy speech poorly).[1] The counterpart to this in humans would be if a human encounters an unfamiliar situation that it hasn't learned to deal from its previous experience, or also the modern world in general relative to the human environment of evolutionary adaptedness.
Contents
History
Potential issues if human safety problems are not addressed
notes
the most canonical-seeming post is https://www.greaterwrong.com/posts/vbtvgNXkufFRSrx4j/three-ai-safety-related-ideas
e.g. "Think of the human as a really badly designed AI with a convoluted architecture that nobody understands, spaghetti code, full of security holes, has no idea what its terminal values are and is really confused even about its "interim" values, has all kinds of potential safety problems like not being robust to distributional shifts, and is only "safe" in the sense of having passed certain tests for a very narrow distribution of inputs." [1]
https://www.alignmentforum.org/posts/HTgakSs6JpnogD6c2/two-neglected-problems-in-human-ai-safety
References
- ↑ Examples from https://arxiv.org/pdf/1606.06565.pdf#section.7
