People have long dreamed of the idea of machines having the intelligence and capabilities of humans. From the early Greek myths of Hephaestus and his automatons to the Golem of Eastern European Jewish tradition to well over a hundred years of science fiction stories, novels and movies, our human imaginations have envisioned what it would be like to have sentient, intelligent, human-like machines co-exist with us. In 1920 Karel Čapek's play R.U.R. (Rossum's Universal Robots) first coined the word “robot” and gave us a name to give to the creations of our imaginations. In many ways, the quest for the intelligent machine lead to the development of the modern computer. Ideas by Alan Turing not only formulated the basis of programmable machines, but also the core of the concepts of Artificial Intelligence, with the namesake Turing Test providing a means for evaluating intelligent machines.
Yet, with centuries of technology advancement and the almost exponential increase of computing resources, data, knowledge, and capabilities, we still have not yet achieved the vision of Artificial General Intelligence (AGI) -- machines that can be an equal counterpart of human ability. We’re not even close. We have devices we can talk to that don’t understand what we’re saying. We have cars that will happily drive straight into a wall if that’s what your GPS instructs it to do. Machines are detecting images but not understanding what they are. And we have amazing machines that can beat world champions at chess and Go and multiplayer games, but can’t answer a question as basic as “how long should I cook a 14 pound turkey?” We’ve mastered computing. We’ve wrangled big data. We’re figuring out learning. We have no idea how to achieve general intelligence.
Part of the reason for this disconnect is confusing the various things that we’ve developed as a result of our quest for the intelligent machine from the quest itself. Artificial Intelligence is not a technology. Asking the question whether or not some particular technology is or isn’t AI is missing the point. Artificial intelligence is the journey. It’s the quest for the intelligent machine. All the technologies we’ve developed on the route to that quest are things that are individually useful, but all together, have not yet gotten us to the goal. This is why it’s important to understand that artificial intelligence is not a technology, in much the same way that the Space Race is not a technology.
In order to understand where we currently are or aren’t with AI (depending on how you want to look at things) it’s important to know the roots of modern AI. The term artificial intelligence was coined in 1956 at a Dartmouth University summer conference. John McCarthy, celebrated AI researcher who pulled together the conference himself, said that AI doesn’t have a technology-specific meaning.In his words, “AI is the science and engineering of making intelligent machines.” The creator himself saw AI as not the ends, but the means. AI is not a technology any more so than physics or civil engineering. The challenge is, like all sciences, there must be application to bring concept to reality.
Since the 1950s huge advancements in technology have evolved to help us on our quest towards the goals of artificial intelligence. In the early decades of AI from the 1950s through the 1970s, we created machines that could play games, understand basic logic, could engage in simple conversations, had basic machine translation capabilities, and we even rudimentary neural networks.
After a decline in interest precipitated by the under-delivering of AI over-promises, interest resumed in the late 1980s with widespread adoption of computer desktops on knowledge worker’s desks and the development of expert systems. In the late 1990s IBM’s Deep Blue beat chess grandmaster Garry Kasparov. It seemed we were back on a roll with AI development.
