Intelligent Tools

1

When Thomas Edison was inventing “moving pictures” all he could imagine was filming a live performance of the opera. He did not anticipate Gone With The Wind or Jaws. Surprisingly, the craft of cinematography was not obvious beforehand, and took decades to discover.

This happens with all radical new technologies: before they mature, our expectation of how they’ll work is only half right.

Now, considering recent advances in artificial intelligence, I believe we’re finally at the point where we can see what’s working, squint at it, and start to make out the shape of the half we didn’t—and perhaps couldn’t—imagine beforehand.

2

The first and most obvious thing most people imagine when asked to describe “AI” is a humanoid robot, like C-3P0, or perhaps a disembodied personality, like Her.

But perhaps this is the AI equivalent of imagining film would only be used to record live on-stage performances? Sure, it could be part of it, but it’s missing the more important thing.

The reason it’s natural to imagine AI in this way is because we assume machine intelligence follows similar stages of development as human intelligence. So we imagine systems that are capable of having conversations with us and performing a wide variety of simple tasks, like Siri and Alexa, rather than systems that can’t speak but can do one thing really well, like draw illustrations, play a video game, or use gyroscope data from a watch to detect what kind of workout we’re doing.

It’s becoming increasingly clear that the vast majority of useful AI is not about creating an artificial human personality. It is about creating tools that are endowed with intelligence, and capable of performing far more complex tasks than before.

In fact, I think this is so important, so overlooked, and will become so pervasive, that I think it makes sense to classify it as a new revolution in software. When we put it in this context, it makes the future a lot more clear.

3

If you take an expansive view of the history of software, there are two big revolutions that stand out:

1. The shift from command-line interfaces to graphical user interfaces, which enabled many more people to use computers by removing the need to memorize a long list of commands.
2. The shift from single-player computing to globally networked computing, which made computers vastly more useful, and exponentially increased the number of people who wanted to use computers.

Now, considering recent developments in artificial intelligence, I believe we’re entering a third major revolution in software: the shift from simple, direct manipulation of data to tools that are intelligent and capable of complex, unpredictable output. Instead of software that mimics a paintbrush, we now have software that mimics the painter. 

This principle will be extended to all types of software: research, accounting, programming, web design, writing, video editing, truck driving, etc. Anywhere you can train a machine learning model to perform a complex task, someone will perform a machine learning model to perform a complex task.