Relevant skills for an AI economy would include mathematics, programming, ML, web development, etc.
It’s hard to extrapolate out that far, but AI still has a lot of trouble with robotics (e.g. we don’t have good dish washing household robots). So there will probably be e.g. construction jobs for a while. AI is helpful for programming but using AI to program relies on a lot of human support; I doubt programming will be entirely automated in 30 years. AI tends to have trouble with contextualized, embodied/embedded problems; it’s better at decontextualized, schoolwork-like problems. For example if you’re doing sales you need to manage a set of relationships whose data is gathered over a lot of contexts, mostly not recorded, and AI is going to have more trouble with parsing that context into something a transformer can operate on and give a good response to. Self-driving is an example of an embedded, though low-context, problem and progress on that has been slower than expected, although due to all the data from electric cars it’s possible to train a transformer to imitate humans using that data.
Thanks. What are the things that AI will, in 10, 20 or 30 years, have “trouble with”, and want are the “relevant skills” to train your kids in?
Relevant skills for an AI economy would include mathematics, programming, ML, web development, etc.
It’s hard to extrapolate out that far, but AI still has a lot of trouble with robotics (e.g. we don’t have good dish washing household robots). So there will probably be e.g. construction jobs for a while. AI is helpful for programming but using AI to program relies on a lot of human support; I doubt programming will be entirely automated in 30 years. AI tends to have trouble with contextualized, embodied/embedded problems; it’s better at decontextualized, schoolwork-like problems. For example if you’re doing sales you need to manage a set of relationships whose data is gathered over a lot of contexts, mostly not recorded, and AI is going to have more trouble with parsing that context into something a transformer can operate on and give a good response to. Self-driving is an example of an embedded, though low-context, problem and progress on that has been slower than expected, although due to all the data from electric cars it’s possible to train a transformer to imitate humans using that data.