Introduction
ABOUT HALFWAY THROUGH writing this book, I was having lunch with a colleague.
“What are you working on?” she asked me.
This is a standard question for academics—we ask it of each other all the time. I should have been ready for it and had an impressive answer ready at hand.
“Something a bit different. I’m writing a popular science introduction to artificial intelligence.”
She snorted. “Does the world really need yet another popular science introduction to AI? What’s the main idea, then? What’s your new angle?”
I was crestfallen. I needed a clever comeback. So I made a joke.
“It’s the story of AI through failed ideas.”
She looked at me, her smile now faded. “It’s going to be a bloody long book, then.”
* * *
Artificial intelligence (AI) is my life. I fell in love with AI as a student in the mid-1980s, and I remain passionate about it today. I love AI, not because I think it will make me rich (although that would be nice) nor because I believe it will transform our world (although, as we will see in this book, I believe it will do so in many important ways). I love AI because it is the most endlessly fascinating subject I know of. It draws upon and contributes to an astonishing range of disciplines, including philosophy, psychology, cognitive science, neuroscience, logic, statistics, economics, and robotics. And ultimately, of course, AI appeals to fundamental questions about the human condition and our status as Homo sapiens—what it means to be human, and whether humans are unique.
WHAT AI IS (AND ISN’T)
My first main goal in this book is to tell you what AI is—and, perhaps more important, what it is not. You might find this a little surprising, because it may seem obvious to you what AI is all about. Surely, the long-term dream of AI is to build machines that have the full range of capabilities for intelligent action that people have—to build machines that are self-aware, conscious, and autonomous in the same way that people like you and me are. You will probably have encountered this version of the AI dream in science fiction movies, TV shows, and books.
This version of AI may seem intuitive and obvious, but as we will see when we try to understand what it really means, we encounter many difficulties. The truth is we don’t remotely understand what it is we want to create or the mechanisms that create it in people. Moreover, it is by no means the case that there is agreement that this really is the goal of AI. In fact, it is fiercely contentious—there isn’t even any consensus that this kind of AI is feasible, let alone desirable.
For these reasons, this version of AI—the grand dream—is difficult to approach directly, and although it makes for great books, movies, and video games, it isn’t in the mainstream of AI research. Of course, the grand dream raises quite profound philosophical questions—and we will discuss many of these in this book. But beyond these, much of what is written about this version of AI is really nothing more than speculation. Some of it is of the lunatic fringe variety—AI has always attracted crackpots, charlatans, and snake oil salesmen as well as brilliant scientists.
Nevertheless, the public debate on AI, and the seemingly never-ending press fascination with it, is largely fixated on the grand dream and on alarmist dystopian scenarios that have become a weary trope when reporting on AI (AI will take all our jobs; AI will get smarter than we are, and then it will be out of control; superintelligent AI might go wrong and eliminate humanity). Much of what is published about AI in the popular press is ill-informed or irrelevant. Most of it is garbage, from a technical point of view, however entertaining it might be.
In this book, I want to change that narrative. I want to tell you about what AI actually is, what AI researchers actually work on, and how they go about it. The reality of AI for the foreseeable future is very different from the grand dream. It is perhaps less immediately attention grabbing, but it is, as I will show in this book, tremendously exciting in its own right. The mainstream of AI research today is focused around getting machines to do specific tasks that currently require human brains (and also, potentially, human bodies) and for which conventional computing techniques provide no solution. This century has witnessed important advances in this area, which is why AI is so fêted at present. Automated translation tools are one example of an AI technology that was firmly in the realm of science fiction twenty years ago, which has become a practical, everyday reality within the past decade. Such tools have many limitations, but they are successfully used by millions of people across the globe every day. Within the next decade, we will see high-quality real-time spoken-word language translation and augmented reality tools that will change the way we perceive, understand, and relate to the world we live in. Driverless cars are a realistic prospect, and AI looks set to have transformative applications in health care, from which we will all stand to benefit: AI systems have proven to be better than people at recognizing abnormalities such as tumors on x-rays and ultrasound scans, and wearable technology, coupled with AI, has the potential to monitor our health on a continual basis, giving us advance warnings of heart disease, stress, and even dementia. This is the kind of thing that AI researchers actually work on. This is what excites me about AI. And this is what the AI narrative should be about.
To understand what AI today is and why AI is for the most part not concerned with the grand dream, we also need to understand why AI is hard to create. Over the past sixty years, huge amounts of effort (and research funding) have flowed into AI, and yet, sadly, robot butlers are not likely any time soon. So why has AI proved to be so difficult? To understand the answer to this question, we need to understand what computers are and what computers can do, at their most fundamental level. This takes us into the realm of some of the deepest questions in mathematics and the work of one of the greatest minds of the twentieth century: Alan Turing.
THE STORY OF AI
Copyright © 2020 by Michael Wooldridge