As Machine Learning becomes real, our minds are focusing on what really is human. There has been a flurry of publications, both scholarly and popular, exploring this - some looked at which areas humans can trump the machines, and others at how to organise the human society when we arrive at the age of intelligent machines. We are looking at anywhere between 2030 to 2045 for Singularity to be achieved - the machines become generally intelligent then (instead of the current special purpose intelligence they are now programmed with) - and while some may have a different view on this, no one is doubting their effect on the workplace. Automation is reconfiguring all human work, and by extension human societies. It is time to explore what this really means.
There are some excellent studies that I wrote about earlier which assess what humans can do better than machines. These superior human abilities, as Researchers figure out, fall under three categories - Dexterity (our fingers and bodies are more nimble, so a human dentist can do better jobs than robots), Creativity (who wants Robot poetry) and Negotiations (where relationships play a role). While the message is optimistic, its conclusions are not. In that scale, half of the current occupational categories face the risk of significant automation within the next two decades, and that, without accounting for Singularity! These occupational categories may together count for more than half of the jobs in urban societies, and include many of the popular jobs in hospitality, office work, even in accounting and programming. These studies should serve as a clarion call for a fundamental rethink about education and skills in every country.
In this conversation, Geoff Colvin makes an important point in his new book, Humans Are Underrated. His message is that it is futile to try to figure out what jobs humans can do better than machines, because, with Moores Law in action, machines will always catch up. The right question to ask, Colvin suggests, is which jobs do we prefer humans to do for us. For example, would you prefer a human doctor or an impersonal algorithm? What about teachers? Or Judges? While the whole human society may turn into, without exception, a society of consumers, we may display distinct consumer preferences for humans being in some roles.
This is a different take on the Ability question, one based on emotional, rather than rational, view. Following this, Colvin reaches a similar conclusion like the others studying human ability. In his formulation, human workers of tomorrow will do less of knowledge work and more of relationship work. So, while the Dentists may not be as safe in his world, his emotional abilities of reassuring a frightened patient (I am thinking of myself) would count more than the nimbleness of his fingers. No wonder that top medical schools now require their students to read literature involving complex characters, because they seemed to have decided that relationship skills and understanding the patients are crucial for a successful medical professional.
However, most of the educational establishment is blissfully unaware of this possibility, being wedded, as they were for last half a century, to knowledge work. The policy-makers are also sleepwalking into this automated future, as they continue to follow the models of earlier industrial successes and standards-based education. The Relationship Worker is still a novel term, and have not made its appearance in business conferences yet, though we seem to appreciate it in our personal lives and experiences so much more.
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