Architects of Intelligence summary

It’s hard not to be impressed when we see an AI beating the best human players at chess, Go, or shogi. But as monumental as that is, it doesn’t mean we’re any closer to achieving any kind of general intelligence. AI is still only good at completing specific, narrow tasks.

Take AlphaZero. It was trained through deep learning to play deterministic, two-player, and fully observable board games, like chess and Go. Despite AlphaZero’s skill in these games, it would be utterly useless if asked to learn to play any other type of game – like, say, poker.

Over the years, different machine learning techniques have fallen in and out of favor. This phenomenon is exactly what happened with the concept of deep learning. The technique emerged as early as the 1950s but was dismissed as useless by the 1960s – yet today it’s once again the dominant machine learning method.

Deep learning will undoubtedly play a role in the AI of the future, but its limitations mean that it can’t be the only technique we use to create AGI. Rather, the development of AGI may require researchers to combine several different machine learning methods to create a hybrid system.

In the recent past, there’s been a lot of talk about AI’s potential to reinforce the biases and stereotypes humans might unintentionally program into them. Lots of academic researchers understand the problem of bias when it comes to AI and are modifying algorithms to respond to it. But, this could be flipped and used to our advantage: we could use AI to eliminate biases.

It’s much more difficult to zero in on and correct biases in ourselves. But, as computer scientist Fei-Fei Li points out, when we see our own biases reflected back at us through technology, we can find ways to correct them. And so, eliminating bias is just one example of AI’s ability to improve people’s lives.

Walk into any hospital or care facility in America today and you’re likely to find a lot of stressed-out doctors and nurses. These days, healthcare professionals work long shifts, have tight schedules, and are highly susceptible to burnout and stress.

Not only that, rushed doctors and nurses mean patients are receiving lower-quality care than they otherwise would. In fact, the current third-leading cause of death in American hospitals is physician error. 

It’s no secret that humanity’s destructive capabilities have increased greatly over time, from the bows and arrows of the medieval age to the specialized bombs and drones most militaries use today.

These days, even average citizens have access to drones they could potentially weaponize with small bombs. Fortunately, though, this sort of weapon isn’t scalable. Each drone can only hold one bomb, and be piloted by a single person, meaning its destructive capabilities are limited. 

Imagine that, in ten years, you never have to work another day in your life. Does that sound like a utopia or a nightmare?

Whatever your answer, the growing presence and skill of AI – especially when it comes to efficiently completing repetitive tasks – may mean that many jobs will soon be automated. A few commonly-cited examples of the people who could soon be out of a job are cashiers, truck drivers, accountants, and factory workers. 

Without a doubt, the rise of AI has brought with it a whole host of concerns. But perhaps none has been as well-publicized as the threat posed by humanlike AGI. What happens if robots eclipse humanity, becoming faster, smarter, and stronger than all of us?

A world dominated by robot overlords is still probably a strictly science-fiction scenario. But according to philosopher Nick Bostrom and a few other researchers, it’s worthwhile to consider how the mission to create AGI could end up going very wrong.