Backhoes and Artificial Intelligence
“Deep learning is making a lot of things, behind-the-scenes, much better.”
“So it’s a bit like … as soon as you have good mechanical technology, you can make things like backhoes that can dig holes in the road. But of course a backhoe can knock your head off.”
You can make things like backhoes that can dig holes in the road OR use it to knock your head off
“But you don’t want to not develop a backhoe because it can knock your head off, that would be regarded as silly.”
“Obviously, if they’re used wrong, that can happen. Any new technology, if it’s used by evil people, bad things can happen. But that’s more a question of the politics of the technology. I think we should think of AI as the intellectual equivalent of a backhoe. It will be much better than us at a lot of things. And it can be incredibly good — backhoes can save us a lot of digging. But of course, you can misuse it.”
like every other technology it is up to us on how to use the technology. It is a good idea to put checks and balances, so humans do not use misuse technology, but without being an alarmist.
So about Robots taking over and killing people, let’s not underestimate the competence of humans.
Let’s focus on humans doing more harm to humans by misusing technology, than “recursive self-improving robots” doing harm to humans.
Geoffrey Hinton at the University of Toronto was one of the first researchers to devise a breakthrough idea for training deep neural networks. He’s often referred to as one of the father’s of deep learning because his approach led to the creation of the Restricted Boltzmann Machine, (RBM) and the Deep Belief Network (DBN). He was also significantly involved in Google’s large scale image recognition DBN. See a video of his “Introduction to Deep Learning & Deep Belief Nets”