Instead, according to the researchers, AI is a general-purpose technology whose application might be better compared to the drawn-out adoption of electricity or the internet than to nuclear weapons--though they concede this is in some ways a flawed analogy. The core point, Kapoor says, is that we need to start differentiating between the rapid development of AI methods--the flashy and impressive displays of what AI can do in the lab--and what comes from the actual applications of AI, which in historical examples of other technologies lag behind by decades. "Much of the discussion of AI's societal impacts ignores this process of adoption," Kapoor told me, "and expects societal impacts to occur at the speed of technological development." In other words, the adoption of useful artificial intelligence, in his view, will be less of a tsunami and more of a trickle. In the essay, the pair make some other bracing arguments: terms like "superintelligence" are so incoherent and speculative that we shouldn't use them; AI won't automate everything but will birth a category of human labor that monitors, verifies, and supervises AI; and we should focus more on AI's likelihood to worsen current problems in society than the possibility of it creating new ones.

The collaboration of the human brain and machines, so far in our world is best observed in the way prosthetic body parts work. The people working to improve prosthetic are truly changing lives for the better, for those of us who might have lost body parts. Highly admirable is the recent development where prosthetic parts can be controlled by the brain. A brief overview of how prosthetic work: electrodes are used to sense muscle impulses by the connected limp or other body part, which signals the prosthetic to work accordingly. The recent advance in prosthetic, through remapping nerves are letting the brain control the limps.

Next time you're driving down the road or walking down the street, pause to consider how you read your surroundings. How you pay extra attention to the kid kicking a soccer ball around her front lawn and the slightly wobbly, nervous looking cyclist. You make these calls by drawing on a lifetime of social and cultural experience so ingrained you hardly need to think about it. But imagine you're an autonomous car trying to do the same thing, without that accumulated knowledge or the shared humanity that lets you read others' nuanced behavioral cues. Treating every pedestrian, cyclist, and vehicle as an obstacle to be avoided might keep you from hitting anything, but it could just as easily keep you from getting anywhere.