The Art of Crafting Natural Intelligence

Posted: March 6, 2011 in ConsumerResearch, Google, InfoLit, Knowledge-ABLE, Learning, QueryFormation, SocialMedia, taxonomy, TechHistory

"When you use more than 5% of your brain, you don't want to be on Earth."

I’ve probably teared up more at an unfair hockey fight and I’ve had more emotionally-engulfing movie goings. But as far as a life philosophy that plays out on screen, no self-contained cinematic mythology holds my candles quite like Albert Brooks’ Defending Your Life.

For most of the story Brooks’ day of judgement is about to play out in the purgatorial trappings of a Disneyesque  lodging and office complex. Is the protagonist to advance on the eternal enlightenment path to some higher plain? Will he shuffle back on the next tram for a return date with “the little brains” on earth? That swipe at us live inhabitants is a line delivered by Rip Torn, Brooks’ defense attorney who testifies to a 53% utilization of his own cranial capacity. Us little brains use 2-3% — the remainder of our mind-shafts are crowded out by lethargy and fear.

When One Framework is Worth a Thousand Taxonomies

I’ve wondered what fears could be confronted and ultimately shed so that I could soar perhaps from 2-3% up to 5-6?  In that spirit I’ve recently stumbled across a framework called Bloom’s Taxonomy. Like the defense lawyer slam at our low-performing mental capacities and fear-mongering, Bloom said that 80-90% of our highest brain function in the lowest realm of sense-making. He calls this “knowledge.” Knowledge is accessed through the following retention portals:

remembering, memorizing, recognizing, recalling identification, recalling information, who, what, where, when, how, describing

Kinda oafish, no? It’s deciphering 101. It’s on or it’s off. X=Y or fuggedaboutit.

The pattern-matching of keywords is not the face that launched a thousand ships but the probability gag that seated a thousand monkeys at their typewriters in order to write the great American novel or the great American Internet start-up — what ever cashes out higher.  Just Ask Jeeves! These are the well-trodden grounds of that cloistered chamber you and I have come to know as web search. Its premise is still tuned to exact match good enough-ness. That’s because we can be sold nouns even more easily than the notion our mental blanks are being filled in my omnipotent language engineers. We frugal consumers cave to deals on things — not to actions about ideas. Nouns are the merchandise — not the verbs that help us to backorder our understanding of what we actually do with our bill of goods. Unless we’re potential suspects in a case, no one is interested in our trail ‘o stuff — unless they can sell it to us again.

The next order of mental processing is to isolate noun phrases from their predicates. That means getting the search engine to distinguish actors from their actions, reducing outcomes to a range of questions we’re ready to answer — or at least lower our surprise should they arise. That kind of conditional logic exists in our mental reflexes whether we’ve had our morning shower or coffee.

It’s interesting that in the pecking order of brain function the inverted pyramid of journalism ranks somewhere in the custodial closet of the ivy-coated shrines of higher learning. Not incidentally these are the unremarkable terms on which IBM’s Watson, the question answering machine, beat its human Jeopardy contestants to the buzzer. It took a fact base so bottomless it would turn baseless in the gear shafts of the most fervently applied quiz show savant. Watson’s algorithmic swagger chewed through mounds of trivia like a smoldering ash heap of documentation fertilizer.

Elementary School My Dear Watson

The conquest prompted one of the IBM partisans to reflect in the New York Times on finding Watson more meaningful work:

“I have been in medical education for 40 years and we’re still a very memory-based curriculum,” said Dr. Herbert Chase, a professor of clinical medicine at Columbia University… The power of Watson- like tools will cause us to reconsider what it is we want students to do.”

At the same time Watson’s next gig as a physician’s assistant begs a more immediate question: how do we humans need raise our learning games to Bloom’s next levels of comprehension, application, analysis and synthesis? How do we aid and abet the healthy transfer of between us inquiring pea brains?

Knowing a lot about an academic discipline is at best, tangential to teaching it. Having a natural understanding of a subject can be an unnatural fit for passing that understanding along to others. Assuming that academics are better at publishing papers and attending conferences than in educating students, the question falls to the insatiable learners among us: how do we teach ourselves on a level beyond the aspirations of Watson’s parents? How do we convince supple, young minds that a healthy dose of skepticism about humans is only the first of a storehouse of rational and instinctive reasons to doubt the merits and intentions of question answering machines?

The current cover story of the Atlantic Monthly offers up Mind Versus Machine. Here science writer Brian Christian serves in the oppositional role of the two Jeopardy adversaries to Watson. The objective of the annual Turing Test is for AI (“artificial intelligence”) programmers to convince a sequestered panel via screen text that a machine could out-human its creator in a range of topics spanning from “celebrity gossip” to “heavy-duty philosophy.” The advice Christian was given when cramming for this contest?

“Be yourself.”

Gee, and I thought I knew how to body surf with the more cryptic sharks!

Five minutes of IM messages later Christian was crowned the winner of the Most Human Human Award — chiefly for two reasons:

  1. His dominating volleys (he’s not waiting on Alex Trebek to pounce, pry, or provocate)
  2. His insights into how the bottom feeder knowledge spoon-fed to his AI adversary highlights natural human intelligence in the experiential realm:

One of my best friends was a barista in high school. Over the course of a day, she would make countless subtle adjustments to the espresso being made, to account for everything from the freshness of the beans to the temperature of the machine to the barometric pressure’s effect on the steam volume, meanwhile manipulating the machine with an octopus’s dexterity and bantering with all manner of customers on whatever topics came up. Then she went to college and landed her first “real” job: rigidly procedural data entry. She thought longingly back to her barista days—when her job actually made demands of her intelligence.

That’s a lesson well worth reteaching ourselves the next time we find ourselves needing to justify more question/answer sessions scheduled in the upper eschelons of Bloom’s taxonomy.

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