What skills can’t be automated?

The day is fast coming when machines will surpass human abilities in all but six skills.

This sobering (or exhilarating) prediction comes from MIT researchers Erik Brynjolfsson and Andrew McAfee, related in their book Race Against the Machine.  Their report, covered by  the Financial Times this week, suggests that what’s already happened to manufacturing is now spreading to sales and will shorty arrive at management.  At some point, like ever more erosive austerity, the burden will bring displaced workers to the streets.  But it won’t change the long-term trajectory of displacement.

The six skills that the authors argue will remain under human purvey are statistical insight, managing group dynamics, good writing, framing and solving open-ended problems, persuasion, and human nurturing.  To this, the FT adds “decision-making”, although I disagree.  It’s easy to make decisions:

IF (this OR that) THEN do OR don’t;

Instead, as the primate exhibit at Brookfield Zoo observes, being human is about enumerating and making choices.

On reflection, there are other qualities that I would also change or replace, arriving at:  creative expression, intuitive reasoning, negotiation, framing and solving open-ended problems, nurturing, and framing choices.

I was thinking about this in the context of CamStent’s first-ever shareholder meeting on Monday.  It’s a real milestone for our young company, and humbling to look around the room at our Board, shareholders, scientists, and management group.   It takes diverse skills, selected from experience and organized around a purpose, to complete  the things we’ve accomplished in the past two years. It’s remarkable.

Can those skills be automated?  Not today, probably not in my lifetime, perhaps never.  I like to think that there is a unique way of processing information, coloring it with emotion and desire, thinking and choosing, organizing and acting, that can’t be reduced to deterministic algorithms and pattern recognition.  The deep search and combinatorial approaches of ever-faster machines can, indeed, solve ever wider problems.

One might argue whether entrepreneurship is relevant in the coming age of machines. But if it is, then it still needs at least six, and perhaps dozens, of  human skills can’t be replaced by computational horsepower alone.   In the jobs at the end of the universe, we’ll still need to strive for symbiosis, not dominance, with our machines.