I'm probably too late to the party for this comment to matter but: what the AI community pushes as "Safety" isn't actually Safety. Read Sidney Dekker. Read Nancy Leveson. Read Jens Rasmussen. Safety is not building perfect technology that never makes a mistake.
When I was working in defense technology I had two questions for engineers when we talked about Safety:
1) Can the operator assess the risk of using this technology?
2) If something goes wrong during operations, can the operator mitigate the risk?
The degree to which either of those statements is true is a measure of how safe that technology is. Technology that is simple to understand and executes deterministically every single time and where it is obvious if it is malfunctioning and the operator has enough time to either correct it or stop it, is generally perceived as safe. Technology that hides what it is really doing, confuses the operator about what the effects of operating it might be, and either executes faster than the operator can respond or specifically prevents the operator from responding, is more likely to trigger negative safety outcomes.
The problem the AI industry faces is that tricking the operator into thinking the technology is doing something it is not is explicitly part of their business model. Read any of the mentioned authors (Dekker is probably the best starting point) and it will become obvious why AI Safety is impossible when AI is dependent on pretending to "think" and "reason". In order to be safe they would have to abandon that. If they abandon that, they will be unable to raise the capital they need to keep the bubble from bursting. The technology will survive, maybe with another AI winter, but many of the businesses will not.
So they will abandon the lip service about Safety instead, but then that was never real Safety to begin with. Real Safety is not about zero risk. It is just as impossible to have zero risk as it is to have 100% uptime. Real Safety is about how the technology is designed to manage risk as part of an overall system.
When I was working in defense technology I had two questions for engineers when we talked about Safety:
1) Can the operator assess the risk of using this technology? 2) If something goes wrong during operations, can the operator mitigate the risk?
The degree to which either of those statements is true is a measure of how safe that technology is. Technology that is simple to understand and executes deterministically every single time and where it is obvious if it is malfunctioning and the operator has enough time to either correct it or stop it, is generally perceived as safe. Technology that hides what it is really doing, confuses the operator about what the effects of operating it might be, and either executes faster than the operator can respond or specifically prevents the operator from responding, is more likely to trigger negative safety outcomes.
The problem the AI industry faces is that tricking the operator into thinking the technology is doing something it is not is explicitly part of their business model. Read any of the mentioned authors (Dekker is probably the best starting point) and it will become obvious why AI Safety is impossible when AI is dependent on pretending to "think" and "reason". In order to be safe they would have to abandon that. If they abandon that, they will be unable to raise the capital they need to keep the bubble from bursting. The technology will survive, maybe with another AI winter, but many of the businesses will not.
So they will abandon the lip service about Safety instead, but then that was never real Safety to begin with. Real Safety is not about zero risk. It is just as impossible to have zero risk as it is to have 100% uptime. Real Safety is about how the technology is designed to manage risk as part of an overall system.