Creativity and AI

Brain - origin_544928According to folklore, good things (and bad things) tend to come in threes. I was reminded of this last week, when I read three things that all served to reinforce a particular idea.

The first was my Kindle version of “Waking Up”, by neuroscientist Sam Harris, a guide to spirituality without religion. In this he relates the search for the nature of consciousness and explains the illusion we have of a sense of self. Along the way, he illustrates his arguments with cases of brain injury (and brain surgery) that suggest there is no evidence for a soul, nor anywhere for it to reside. In cases where the two hemispheres of the brain are surgically disconnected from one another (callosotomy), those positing the necessity for a soul would seem to need there to be two in the one skull.

“Waking Up” is about far more than the physiology of the brain, but I was struck by some of the examples given of the distinct differences in the way the left and right hemispheres perform, particularly when the very next book I read – “Imagine – How Creativity Works” by Jonah Lehrer – tackled this subject head on (so to speak). It’s too bad this book, and its author are at the centre of a literary scandal, because it really is a good read.

Having just read Harris on the clear differences in the modus operandi of the left and right halves of our brains, I was intrigued by the experiments Lehrer was relating that appeared to show that insights, inspirations or epiphanies tend to arise in the right brain only after the left brain has quit working on a problem as intractable. To illustrate this, researchers had scanned the cerebral activity of people working on a particular class of riddles. For example: “Marsha and Marjorie were born on the same day of the same month of the same year to the same mother and the same father and yet they are not twins. How is that possible?” After wrestling with such a problem analytically, and failing, only then did subjects “get the penny to drop”, and when it did the insight coincided with a burst of activity in the right brain. Researchers watching the scanners could even predict when someone was going to hit upon a solution. (In this case, the answer is “They’re from a set of triplets.”)

Finally, an e-mail arrived alerting me to the arrival of my soft copy of this week’s New Scientist. In it, I spotted a link to an article by Douglas Heaven from August 2013 that I’d previously missed. The article takes the left brain, right brain comparison up a level of abstraction. “Not Like Us: Artificial Minds We Can’t Understand“. I’m not sure if non-subscribers can follow this link, but the parallel between it and the two other works I found very interesting to contemplate.

Years ago, when I was still studying computer science and then working as a software engineer, I used to follow the efforts in Artificial Intelligence of such academic masters of the subject as Donald Michie at Edinburgh University. By 2013, the year Heaven’s article was published, the attempt to emulate human-like thought by an analytical/algorithmic approaches had all but fizzled out. Yes, we’ve seen such as Deep Blue doing extraordinarily well at chess, but so what? A seven-year old could cope with a simple change to the move rules in chess, but such a change would stump a super-computer grandmaster until it was re-programmed.

On the other hand, Bayesian inference applied to sufficiently large data sets (so-called Big Data) can allow intelligent choices to be made in ways that defy human explanation. Recent successes along these lines were summed up by Dr Nello Cristianini at Bristol University. “We haven’t found the solution to intelligence – we kind of gave up.” But that was the breakthrough. “As soon as we gave up the attempt to produce mental, psychological qualities we started finding success.”

To me, this is an uncanny parallel with our left brain, right brain dichotomy. Perhaps the right brain works in a similarly occult way to the techniques we’re developing for the analysis of big data. Either way, we’re heading into a future where systems will either aid or make decisions based on calculations we simply cannot follow. How mercurial we would seem if most of our decisions were based on right brain insights that we couldn’t explain. At present it’s more of an irritant – Amazon, for example, predicting what we may be interested in buying next. But, per Heaven’s article, what if health officials start making decisions on your eligibility or otherwise for a transplant, based on judgements about you that no-one can follow. That’s a slippery slope to come back to in another post.

(photo credit: IsaacMao via photopin cc)

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