the pursuit of intelligence in computer science
Since the dawn of high tech electronics and robotics, we’ve heard an awful lot about artificial intelligence and countless tales about how it may just decide to enslave us all one of these days, or fuse with humanity into an unrecognizable homunculus of men, women, children and machines as in the end of Isaac Asimov’s classic short story The Last Question, which is probably my favorite science fiction tale for it’s amazing scope and it’s bizarre climax. But when we actually drill down to the actual requirements for making machines endowed with the kind of computing abilities we’d call intelligence, we’ll find that the definition of what actually constitutes an objective pattern of cognition we will recognize as intelligent is extremely vague and constantly being rewritten.
An easy way to try and establish whether a computer program is intelligent or not would be to give it one of the many IQ tests we constantly use on ourselves. Surely if it can score a 120 or 140, it would have to qualify as a machine capable of advanced cognition, right? Actually, no. Not even close. Just like you can increase a score on most of the IQ tests in existence by taking them multiple times and training your mind to look for the logical patterns on which the questions are built, a programmer can simply create enough methods for the software to make its way through questions ordinarily designed for humans, with ease. On top of that, the results won’t mean much since the tests aren’t well equipped to measure critical thinking skills and many people whose scores should put them firmly into MENSA territory can have the intellectual depth of an empty saucer and the curiosity of your average dining room table. So to design a truly intelligent machine, you need to program what we would know as insight, creativity and curiosity. That’s much harder than the propositional logic of working memory and stopping logical patterns. Not that the latter should be seen as a picnic either…
But that shouldn’t be an impossible hurdle, say some AI enthusaists. If we modeled the brain with a powerful supercomputer we’d track down how the creative process works in the human mind. Then, you could use this knowledge to build a creative machine, right? If only it were that easy, MIT and CalTech would’ve been making thinking computers by now. Our minds are constantly lit up with activity as we process the barrages of stimuli coming through our senses. And while some parts of our brain are devoted to certain very specific tasks, the actual cognition taking place using the information they collect, or using them to carry out our planned actions, is still kind of a black box. Looking for a creativity cortex might be a fool’s errand and the mechanics of things like artistic talent or aptitude for innovation are really the products of very intricate cognitive processes that are very difficult to accurately pin down in mechanical terms.
This means that while we understand how to give our computers some sense of logic and a very basic grasp on abstract thinking, we wouldn’t really be giving them intelligence until we can figure out what roles creativity, inspiration and curiosity should play in how we talk about intellect. Consider someone like Leonardo DaVinci, a man who’s widely considered to be one of the most brilliant people in history. Sure, he had a terrific grip on logic and scientific fact, but his incredible artistic skills, curiosity in how the human body was put together, and profound creativity when it came to engineering, were just as important at making him a celebrated polymath and one of the symbols of the West’s scientific and cultural accomplishments (fueled in no small part by the knowledge acquired from scholarly Muslim cultures during the Crusades, but that’s another story). Obviously, it would be absurd to challenge computer scientists to cough up a digital DaVinci, but until we come up with a concrete definition of what a well rounded intellect entails, how we define intelligence would be akin to one of the most famous definitions of pornography given by U.S. Supreme Court Justice Potter Stewart. We’ll know it when we see it.
As a side note, I should mention another little note on creativity. Sometimes, when robots are given very basic rules and a lot of room to find their own solutions to certain problems, they come up with answers we could consider somewhat creative under the circumstances. And that makes me wonder if creativity is really what happens when we’re not constrained by rules in how we find a solution and arrive at an approach that seems effective and novel in our situation. In that case, we should be programming machines with fewer rules and giving them some free reign in making decisions, something which classically trained programmers working on business and mass market applications might find antithetical and potentially futile.
I’ll have to come back and reread the rest of this post after I recover from -
many people whose scores should put them firmly into MENSA territory can have the intellectual depth of an empty saucer and the curiosity of your average dining room table
hilarious!
Computer intelligence has and will continue to exceed the calculating capabilities of the human brain. The difference between human and computer intelligence is the ability to draw conclusions without data (imagine) and then act irrationally based on false conclusions. The human ability recognize people, object, ideas, emotions, etc. from the peripheries of experience will not be easily simulated by machines because it can not be programmed until the event has occurred. We often act outside of calculation or consideration.
Arguably, human creativity functions only in given parameters. Our imaginary monsters are always physical descriptions of things that already exist (or could exist). But, our talent is in acting compulsively and discovering accidentally based on what any algorithm would have to label as foolishness. It is compulsive folly, ignorance, gusto, and the likes of which that are special to human intelligence. Could a robot ever decide to take the scenic route?
Computer intelligence has and will continue to exceed the calculating capabilities of the human brain.
Yes, but there’s more to it than just calculation. Common household calculators can put most of us to shame when solving complex equations but we can’t say that they have some sort of intelligence, can we? After all, they’re just following algorithms we programmed so we could use them as a tool.
It is compulsive folly, ignorance, gusto, and the like of which that are special to human intelligence.
You say it like it’s necessarily a bad thing. Sure, compulsion can be a bad thing, but some compulsive decisions lead to avoiding accidents and discovering something great. It’s just when our impulsive decisions turn out to be beneficial, we call them by a different name: serendipity. Without impulse, we’d have no emotions and wouldn’t be human as we define it today.
Yes, I think we will be able to build machines that can think, have consciousness, and eventually outperform humans. The hardest current technical issues to solve are hardware capacity and power efficiency . Currently, with our stone age technology, we stamp out switch arrays linearly as chips. Even with Moore’s law, we will never achieve the required complexity of biological systems developing their switch arrays exponentially through cell division yielding connection potentials comparable to the number of stars in the universe. Moreover, the chemical / electrical nature cells employ requires the sparse energy found in a single apple to calculate all your movements, health management, sensor data fusion, awareness, pattern recognition and layers of parallel problem solving skills for an hour or two. We are similarly a long way from matching this efficiency. Architecturally it is emerging, and through bio-inspired works of Gerald Edelman (ref. Bright Air Brilliant Fire) and much other work, that Theory of Neuronal Group Selection or TNGS will show us how to build these machines to have consciousness. I previously hypothesized that the uncertainty principles of particle physics described by Quantum Mechanics; when introduced as ‘triggers’ in macro-systems (i.e.where micro differences produce macro outcomes), that ‘conciousness’ can be reconsidered as a duality (consciousness comes from the same place outside of this world that sub atomic particles do, that pop in and out of existence), can creep into a mechanical system, into our Newtonian mechanical world. Certainly it looks like our nerve cells are a function of uncertainty like an overheated laptop that starts to have a mind of its own sometimes. I am not so sure of this now, having read Edelmans work, who refutes this idea, but I still hold it as plausible, and certainly philosophically pleasing.