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I think he's trying to make the argument that AI need not be limited to automating tasks that directly replace human jobs but can also augment human labor in a
by DebtDeflation 8y ago
I think he's trying to make the argument that AI need not be limited to automating tasks that directly replace human jobs but can also augment human labor in a way that enables people to do new things that couldn't previously be imagined. It's a variation on the old economics story of how the bulldozer does not replace humans with shovels, it enables those humans to build skyscrapers instead of being limited to building shacks.
He's making a valid argument in the abstract. However, like so many authors from outside the field, his concept of AI is primarily informed by works like The Singularity Is Near and Superintelligence, and completely disconnected from the current state of the art and its development for the foreseeable future.
- cle 8y agoCan you elaborate on how his concept of AI is disconnected from reality?
- Retric 8y agoCurrently AI is based around optimizing something, but AGI has no specific thing to optimize around. Human intelligence has a lot of issues with for example mental heath because it’s not so easy to optimize for general intelligence. Fiction glosses over that stuff and generally paints AI as some extremely rational extremely intelligent system. But, rationality may be more of a social construct than we assume with many or even most AGI turning to criminal or deviant behavior.
- DebtDeflation 8y agoHis concept of AI seems to be more AGI in the sense of abstract reasoning and creative problem solving applied to problems in one domain where the AI can then accumulate the lessons learned and apply them to another domain. As opposed to the current reality which is mainly stringing classifiers together. I work as a consultant, and I get these sort of questions from my clients all the time. "Can't we just load the (unlabeled) data into the AI solution and just have it 'figure things out' without training it?" "Can't we take the model that we already trained (on one very narrow domain) and use it (on some completely different domain) without going through all that again?" People want unsupervised transfer learning with a whole lot of a priori knowledge baked into it.