#1 seems like a bit of drag on progress, but to the extent that many regulations also limit liability (or at least reduce charges of negligence), it may actually be net-positive.
#2 IMO is the primary issue.
Successful applications of AI (text generation, chatbots, image manipulation, etc.) just don’t matter if a significant fraction of decisions are wrong—just try again. There are always human supervisors between generator and use. In driving, a mistake hurts someone, or annoys the passenger enough to prefer to pay for a human driver.
#2.5 (a extension of robustness into the physical world) is that operations are VASTLY harder, and the economics are very different too. Pure-information AI is expensive to develop and train, but not that expensive to run. And it’s hard to physically interfere with or steal a chatbot. Driving is expensive to actually execute—it requires expensive sensors and maintenance, so the variable cost to deliver it is much higher, which makes it harder to be usefully (profitably) deployed. And it can be stolen or vandalized, adding to the difficulty of operations. And don’t forget the latency and mobility requirements which make it WAY harder to use shared (cloud) resources for multiple instances.
#1 seems like a bit of drag on progress, but to the extent that many regulations also limit liability (or at least reduce charges of negligence), it may actually be net-positive.
#2 IMO is the primary issue.
Successful applications of AI (text generation, chatbots, image manipulation, etc.) just don’t matter if a significant fraction of decisions are wrong—just try again. There are always human supervisors between generator and use. In driving, a mistake hurts someone, or annoys the passenger enough to prefer to pay for a human driver.
#2.5 (a extension of robustness into the physical world) is that operations are VASTLY harder, and the economics are very different too. Pure-information AI is expensive to develop and train, but not that expensive to run. And it’s hard to physically interfere with or steal a chatbot. Driving is expensive to actually execute—it requires expensive sensors and maintenance, so the variable cost to deliver it is much higher, which makes it harder to be usefully (profitably) deployed. And it can be stolen or vandalized, adding to the difficulty of operations. And don’t forget the latency and mobility requirements which make it WAY harder to use shared (cloud) resources for multiple instances.