“Machines should work, people should think.”
The “IBM Polyanna Principle”
This slogan seems to come from an IBM ad from the 1960s, but it may be much older. It’s based on a vision of the future where robots do the heavy lifting and humans have time to dream up new ideas. In many ways, it describes the world we live in today. In other ways, it’s as much of a cartoon as “The Jetsons”.
The problem with automation is that it doesn’t stop just at physical work. Today’s machines do the thinking for us – or at least make it easier for a small cadre of professionals to view the “big picture”. Are humans becoming redundant? Is there a place for people and work in a world already heavily tilted towards capital and the machines it can buy?
We have talked at great length about the ill-defined “skills gap” which supposedly plagues the workforce. It’s incredibly hard to pin down in terms of skills. The problem appears to be much more closely related to the growth of small companies unwilling to give workers time to learn highly specific skills on the job. A breakdown of loyalty on both ends of the paycheck coupled with a need to run fast and light, lean and mean, is certainly the genesis of the problem.
Through all of this, however, there has been an assumption that “automation” as a concept means “robots”. The modern GM Hamtramck facility in Detroit, as an example, has built over 4 million cars since it opened 30 years ago – but employs only 1,600 people. Mainly, robots build the cars while people tend the robots.
Often neglected is the information side of automation, which is to say data analysis, information sharing technology, and of course the internet. Just 20 years ago many people were employed shuffling paper back and forth between workstations in large corporations. Large teams of quality assurance analysts poured over data now gathered with the flick of a scanner and analyzed by machine in real time.
Don’t just blame the robots.
The next phase, already coming at us, is where executives themselves are easily replaced by software. Analyst Nigel Rayner of Gartner, a company that produces such systems, says, “Many of the things executives do today will be automated.” Every job is threatened to be replaced by automation, and the more expensive the worker the better the payback. A team well versed in the code can easily gain the “big picture” faster than anyone in a plush corner office.
What, then, is the future of work? David Autor, an economist at MIT, sees a changing but vital role for workers made of flesh and not silicon. “Tasks that cannot be substituted by computerization are generally complemented by it,” he wrote. “This point is as fundamental as it is overlooked.” His argument is that the flexibility of humans is the key characteristic that makes them invaluable.
Back in Detroit, Camille Nicita is the CEO of Gongos, another company which advises companies on how to automate these systems, sees a distinct role for humans who are augmented, not replaced, software. People will be there to “Go beyond analysis and translate that data in a way that informs business decisions through synthesis and the power of great narrative.” If that sounds more like what a writer does than a traditional analyst, I know of someone who would like to talk to you (me).
But it is this “augmentation” which defines the “skills gap” at both ends of the spectrum. On the one hand, potential employees add the most value to a company when they are able to think strategically and act according to a long range plan. On the other hand, employers are largely unable to define their own needs strategically – let alone be in a position to evaluate a potential employee’s ability in this regard.
The classic “HR screen” set up to handle thousands of resumes is what makes a real breakthrough in augmentation difficult. It ultimately defines the skills gap for the same reason.
How will companies break out and start making the future of employment? That is the critical piece that is missing from the great puzzle that is our new economy. Until they do, clear direction for educators and workers alike on the mythical “skills gap” is very hard to find. Given that, it will be with us until what we really mean by “skills” is much better defined.