Machine learning systems that we have today have become so powerful and are being introduced into everything from self‐driving cars, to predictive policing, to assisting judges, to producing your news feed on Facebook on what you ought to see. And they have a lot of societal impacts. But they’re very difficult to audit.
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I think there are countless amazing opportunities for artificial intelligence and its impact on society. I think one of the areas I’m truly the most excited about is education.
I think developments in artificial intelligence do pose a strong challenge for humanity. I think at a very fundamental level, people don’t quite understand what artificial intelligence is, yet it’s used as a buzzword that’s going to solve every single problem.
Some of the long‐term challenges are very hypothetical—we don’t really know if they will ever materialize in this way. But in the short term I think AI poses some regulatory challenges for society.
Back in 1980, working with the artificial intelligence guys, we had this idea we were going to make smart machines. But it needed to read good books, don’t you think?
The smartphone is the ultimate example of a universal computer. Apps transform the phone into different devices. Unfortunately, the computational revolution has done little for the sustainability of our Earth. Yet, sustainability problems are unique in scale and complexity, often involving significant computational challenges.
When I go talk about this, the thing that I tell people is that I’m not worried about algorithms taking over humanity, because they kind of suck at a lot of things, right. And we’re really not that good at a lot of things we do. But there are things that we’re good at. And so the example that I like to give is Amazon recommender systems. You all run into this on Netflix or Amazon, where they recommend stuff to you. And those algorithms are actually very similar to a lot of the sophisticated artificial intelligence we see now. It’s the same underneath.