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I still haven't found a good talk or essay about how exactly 'AI' will change anything. The only obvious difference is shifts in wealth. The Google Duplex appe

by tgb29 8y ago

I still haven't found a good talk or essay about how exactly 'AI' will change anything. The only obvious difference is shifts in wealth. The Google Duplex appears to be a great breakthrough. But what happens if it's sold and deployed? More wealth to an already wealthy Google. Low income earners who can barely make it as a receptionist will be out of work. In the restaurant example, owners cut costs and possibly earn more -- which is great for these types of operators. But as someone who wants to schedule an appointment, my life doesn't change. Google also just released auto complete and response emails. How does something like this change my life? Any drastic change in AI is abstract and hypothetical, based more in science fiction than reality. In the 1940s, with advances in Nuclear research, it was thought that nuclear power for energy would change the world. 70 years later, we're still using over 80% fossil fuels. Not a great example, but I'll hold this line about 'AI' until I'm convinced otherwise.

WorldMaker 8y ago
I'm in a similar skepticism camp. I studied a lot of AI and Big Data in Graduate school, but haven't done much with it after graduation. My impression from my studies and what I read of things today is that the tools haven't really changed since the last big AI boom in the '60s. There have been incremental enhancements to many of the algorithms, but the algorithms themselves haven't had major breakthroughs. What has changed is we've accelerated GIGO to an extraordinary level that the '60s could have only imagined/dreamed of. With a firehose of inputs on one side and a firehose of outputs on the other side, it's easy for the man-behind-the-curtain/model-in-the-machine to seem quite capable/intelligent, but how are we QA/QCing that that is actually the case? Take everyone's growing frustrations with auto-correct systems using words they'd never themselves use, are those mistakes in the model that will get trained away eventually or representative of the firehose of garbage-in/garbage-out. Similarly, when was the last time that YouTube's "Auto-Play" feature was useful to you? I find I've turned it off on every device I own because it is nonsensical and useless and often full of literal garbage. Some of the early logic mathematicians such as Boole and Bayes, names that come up commonly in AI algorithms, thought they might find proof of God in probability theory, and I sometimes wonder if we may find that probability theory may not prove God, but could definitely prove that (soylent) Devils are real. What's going on with machine learning in YouTube and in the ad spaces frightens me in aggregate, and the problem is still people, but we've massively accelerated GIGO around people.
tacon 8y ago
Leaving out AI, Robin Hanson has an entire book on what happens when we "only" start to emulate existing human thought in machines, what he calls "ems". Given only that, no new algorithms, just an increase in speed, he goes into some detail predicting economic effects.[0][1] [0] https://www.youtube.com/watch?v=XP-p-O200jo https://www.youtube.com/watch?v=XP-p-O200jo [1] https://www.amazon.com/Age-Em-Work-Robots-Earth/dp/0198754620/ https://www.amazon.com/Age-Em-Work-Robots-Earth/dp/019875462...

by tgb29 8y ago

WorldMaker 8y ago

I'm in a similar skepticism camp. I studied a lot of AI and Big Data in Graduate school, but haven't done much with it after graduation. My impression from my studies and what I read of things today is that the tools haven't really changed since the last big AI boom in the '60s. There have been incremental enhancements to many of the algorithms, but the algorithms themselves haven't had major breakthroughs. What has changed is we've accelerated GIGO to an extraordinary level that the '60s could have only imagined/dreamed of. With a firehose of inputs on one side and a firehose of outputs on the other side, it's easy for the man-behind-the-curtain/model-in-the-machine to seem quite capable/intelligent, but how are we QA/QCing that that is actually the case? Take everyone's growing frustrations with auto-correct systems using words they'd never themselves use, are those mistakes in the model that will get trained away eventually or representative of the firehose of garbage-in/garbage-out. Similarly, when was the last time that YouTube's "Auto-Play" feature was useful to you? I find I've turned it off on every device I own because it is nonsensical and useless and often full of literal garbage. Some of the early logic mathematicians such as Boole and Bayes, names that come up commonly in AI algorithms, thought they might find proof of God in probability theory, and I sometimes wonder if we may find that probability theory may not prove God, but could definitely prove that (soylent) Devils are real. What's going on with machine learning in YouTube and in the ad spaces frightens me in aggregate, and the problem is still people, but we've massively accelerated GIGO around people.

tacon 8y ago

Leaving out AI, Robin Hanson has an entire book on what happens when we "only" start to emulate existing human thought in machines, what he calls "ems". Given only that, no new algorithms, just an increase in speed, he goes into some detail predicting economic effects.[0][1] [0] https://www.youtube.com/watch?v=XP-p-O200jo https://www.youtube.com/watch?v=XP-p-O200jo [1] https://www.amazon.com/Age-Em-Work-Robots-Earth/dp/0198754620/ https://www.amazon.com/Age-Em-Work-Robots-Earth/dp/019875462...