March/April 2013 (Vol. 30, No. 2) pp. 11-13
0740-7459/13/$31.00 © 2013 IEEE
Published by the IEEE Computer Society
Published by the IEEE Computer Society
From Minecraft to Minds
|The Computability of the Mind|
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As a computer scientist, I take the position that the mind is computable.
This annoys many people.
Well, perhaps "annoy" is too strong a word. Some reject this point of view on an emotional basis. As sentient beings, we often have a visceral reaction to anything that undermines our own sense of specialness in the universe. Such a reaction is not unique to our age of software-intensive systems. As Jonathan Sawday explores in Engines of the Imagination: Renaissance Culture and the Rise of the Machine, "Descartes had denied that reason could ever be produced mechanically"; and even now, "George Dyson has observed [that it] 'is far settled after three hundred and forty years.'" 1
And yet, the rise of scientific thinking and the subsequent realization that many elements of the human body could be understood mechanistically and that the universe could be understood mathematically replaced more magical explanations. The meaning of mind is perhaps the next frontier. Others reject this point of view on cunning theoretical grounds.
Roger Penrose has a particularly beautiful argument that hinges on Godel's theories, as he describes in Shadows of the Mind. 2 John Searle's Chinese room thought experiment similarly attempts to disavow any purely mechanistic manifestations of mind. 3 And yet, I find no compelling evidence to support Penrose's assertion that the mind rises as a consequence of quantum processes that we do not—and cannot—understand. The meaning of mind is, to my reckoning, an emergent property of the interaction of billions upon billions of simpler, understandable, and computable systems, a concept that Marvin Minsky examines at length in Society of Mind. 4
To be clear, I am neither a cognitive scientist nor a philosopher of the mind nor an AI researcher. My only qualification in this domain is that I possess a mind (well, at least I think I do, most of the time, perhaps) and that I self-identify an entity that I represent as "me."
Alan Turing posed the question, "Can machines think?" in his paper "Computing Machinery and Intelligence" in 1950. 5 Our human fascination with the possibility of thinking machines goes much further back, from the golems of Jewish folklore to the Ars Magna of Raymond Lull and even more recently to the Matrix trilogy or Skynet from the Terminator series. On one hand, the possibility of a sentient machine entrances us. Who wouldn't want an assistant/companion/friend like Andrew from Bicentennial Man or Data from the Star Trek universe? On the other hand, this disturbs us at a very deep level. What would such a sentient creation think of us, and would we as a species therefore become irrelevant?
As computing advances and contributes to advancing every element of the human experience, we continue to push back the edges of mystery. That very reality is also disturbing to some, but I ascribe to Feynman's observation that "it does not do harm to the mystery to know a little more about it."
Let us then try to unwrap some of that mystery.
The Computability of the Mind
If one follows the arguments for and against the computability of the mind, one must inevitably confront the meaning of the words "mind" and "computable." Minds are particularly lousy at understanding themselves, thus what mind is and what it is not will likely always be a slippery topic. Immediately, one comes against the issues of free will and consciousness. Some philosophers believe that both are ineffable; others (most notably Daniel Wegner in The Illusion of Conscious Will6) believe that both are just exquisitely beautiful illusions. The nature of qualia—how we feel about seeing the color purple, for example—is a particularly contentious battleground for materialists and nonmaterialists regarding the philosophy of mind.
Ignoring the delicious verbal sparring one gets when you put a staunch materialist and a passionate nonmaterialist in the same room, I think it is fair to observe that once we step back from the event of machine-as-man, we still have some weighty issues to metabolize. Assume for the moment that we can't craft a machine that we would call sentient: Just how close might we get to the illusion of sentience? As we continue to surrender ourselves to computing, we find ourselves slowly, inexorably, and irreversibly moving to that event. Some might say that this is a bit like Zeno's paradox: we will never actually get to the other side of this machine-as-man room. And yet, we continue to advance.
The issues of the computability of the mind enter the public consciousness largely through books and movies (Wikipedia offers a list of interesting examples: http://en.wikipedia.org/wiki/List_of_fictional_robots_and_androids). From the outside, such creations do look quite magical and very much noncomputable. However, if we peel back the layers of behavior at every level, as a computer scientist, I see algorithms, programs, and systems behind the mystery.
We swim in an ocean of algorithms, each operating as an invisible hand that observes and manipulates some small corner of our world. As I drive to the nearest Starbucks, algorithms control the brakes on my car. When I make a call on my mobile phone, a Viterbi algorithm facilitates a clear connection. When my smartphone suggests a route to take, it's typically using some variation of the A* algorithm.
When explaining algorithms to a nontechnical audience, I often use the example of a Japanese tea ceremony. This ritual, when done with intent, is both sacred and purely algorithmic: in the ceremony, the preparing, pouring, and acceptance of the tea is the manifestation of a finite set of steps that eventually halts.
I suggest that the history of many software-intensive products is a history of algorithms. Similarly, the history of many software-intensive industries is a history of architecture and systems.
Consider recent advances in filmmaking special effects. In the earliest days of 3D graphics, the hard problem was just rendering, but then Blinn's work on ray-tracing algorithms changed all that and opened the floodgates to innovation. Next came—in roughly this order—breakthroughs in algorithms for textured surfaces, basic motion, and then, fluids and fractals. Once these came together, artificial creatures and landscapes rapidly spread across the movie landscape, from the avatars in Tron to many of the landscapes in Indiana Jones. Next came breakthroughs in swarms (for example, the battles in The Lord of the Rings), hair and fur (Scully in Monsters, Inc.), then virtual clothing (Rose's scarf in Titanic), and now photorealistic human skin and faces.
These algorithms begat companies such as Industrial Light and Magic and Digital Domain, which could build systems around these algorithms to develop, deploy, and evolve economically viable solutions.
It's now possible to tell compelling stories in ways that would have previously been economically impossible or too dangerous. In his time, Cecil B. DeMille could afford large casts, but have you ever seen the cost of a few thousand well-equipped ogres at today's prices? The liability policies alone would be staggering, not to mention the thousands of sheep and cattle you'd need to feed them. And I think it's fair to say that Mr. Schwarzenegger's lawyers would never allow him to do most of his own stunts. A CGI instance of Arnold can endure take after take of virtual slaughter without the least wear and tear on its bits.
It's fascinating and delightful to hear the news that a school in Sweden has introduced compulsory classes on Minecraft. 7 Carnegie Mellon's Center for Computational Thinking has a similar mission, with a focus first on scientific research and then on its implications on public life.
That algorithms have entered the public arena is inevitable and desirable. As more of our lives become controlled by the algorithms in our software-intensive systems, we are well served to understand the nature of what controlled us. For computer professionals, it's our responsibility to devise algorithms that serve users. To that end, I'm reminded of a story about Steve Jobs in the early days of the Macintosh, in which he berated a programmer about a particular routine that was only slightly inefficient. Jobs observed that if you multiply a one-second savings in time by the millions of people who would endure that delay, it adds up to a significant human cost. Even small things, at scale, have huge implications.
As Turing has shown, one of the more amazing things about computing is that it's universal. Given enough time, a Turing-complete machine could serve as a calculator or a simulation of a mind. Is it possible—is it probable—for us to move from the kinds of programming found in Minecraft to the computability of the mind?
Someone—perhaps someone not yet born—might answer that question more decisively than I ever could. In the meantime, consider this an opportunity to explore the possibility. Engage your noncomputing family or friends on the computability of the mind and observe where that dialogue might lead with regard to the limits of our software-intensive systems. Let it serve as an inspiration to where we might take this technology in the advancement of the human experience.
Grady Booch is an IBM Fellow and one of the UML's original authors. He's currently developing Computing: The Human Experience, a major transmedia project for public broadcast. Contact him at email@example.com.