The New, Unreasonable Power of Tiny Knowledge

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Nobody wants to be called “a jack of all trades, a master of none.” But perhaps AI turns that old saw on its head.

Here’s an example to show how AI has changed how we approach learning and skill acquisition. I spent the last few years learning the R statistical/programming language and used it for occasional analytics projects. With the dramatic rise in machine learning algorithms, Python seems to have become table stakes for anyone doing serious analytics. So here we go again … another stinkin’ language to learn. But to my surprise -- I only needed a day or so to learn what I need. I have friends, Mr. Chat, Ms. Perplexity, and Dr. Claude, who sit on the edge of their virtual seats, just waiting for me to give them work. Why learn loops, advanced charts and graphs, statistics, and all the rest when AI will do the work for me? Sure, they make mistakes but even then, I can feed the error messages back to them and wind up with some slick code on the other end. So, a day’s worth of Python study + AI equals six months of hard training.

That’s just one skill set. What about financial analysis? Upload a screenshot of financials and get a reasonably good financial statement analysis. Want to summarize an employee or customer survey but don’t know how to do sentiment analysis? Just ask Chat: “Here’s the data; tell me how my customers feel about our new model X widget.” Worried about that new telecom contract? Feed it into the machine, even if your legal expertise extends no further than Boston Legal reruns. What matters is that you have just a little knowledge -- to know that a process or skill exists so that you can ask the right questions. Caveat: Since AIs occasionally hallucinate (though less frequently nowadays), a dash of common sense helps as well.

Ever since humans have walked upright, people have prized deep expertise more than broad knowledge.  If you are having heart surgery tomorrow morning, you don’t really want a balanced human being as your surgeon. You want Dr. Scalpel. His only friends are his scalpel and sutures, whom he calls slicey and stitchy. His idea of work-life balance is holding the surgical robot's arm with his left hand while controlling it with his right. OK, you get the point. But will it always be this way? As AI gets better, will the deep knowledge versus broad exposure value mix change?

All of us can think of past scenarios where AI would have made a whopping difference. I once worked for a wholesale grocer in Memphis. The buyers invited a high-profile pro football player from Pittsburgh to present a new peanut butter brand that he was sponsoring. He shared the market evaluation survey, showing outstanding potential sales. So the buyers ordered thousands of cases, filled warehouses with them, and … there they sat for months, running up inventory costs and ultimately had to be sold at a loss. What went wrong? Bad survey? No. The survey was good but it included only people from Pittsburgh. Roll forward to now and imagine asking an AI “We are contemplating the following deal ….. We feel confident this will be profitable based on a survey …. Please suggest any possible negatives that we have not considered.” Since the AI has read billions of documents and trillions of conversations around the world, there’s a good chance it would flag a narrow geographic market evaluation as a possible failure point.

Of course, everyone needs a set of deep dive skills for the foreseeable future. But long term there will be one single, irreducible skill -- the intelligent, creative use of AI to get things done. If AGI (artificial general intelligence, where computers are as smart as anyone on the planet across all domains) is here in 3-5 years, then ASI (artificial super intelligence) will be here 3-5 years after that, perhaps sooner. Remember the old tale about John Henry versus the steam-powered drill? He beat the machine once, then died. Be different. Take AI to a bar, have a couple of beers, and shake hands with your new partner.

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