Right, that's the problem. Before 2016 or so, "AI Safety" meant the types of things I listed above: how to design AI systems that are safe to use in safety-cri

Right, that's the problem. Before 2016 or so, "AI Safety" meant the types of things I listed above: how to design AI systems that are safe to use in safety-critical settings. Unfortunately, the term "AI Safety" has been overrun with effective altruist longtermism folks talking about something closer to https://en.wikipedia.org/wiki/Existential_risk_from_artificial_general_intelligence https://en.wikipedia.org/wiki/Existential_risk_from_artifici... which is ill-defined and, frankly, usually completely vapid nonsense. > so the question of how to mitigate its risks is going to be at least as squishy a concept as the underlying tech + applications. No, no, no!!! AI safety methods -- methods that really increase confidence in real systems -- are not generic. ALL of the useful AI safety work I know of is deeply related to one or more of: the specific model architecture, the specific optimization algorithm, the specific data, or the specific application. Almost always all of the above.