NEXT: The Labor Force’s Cognitive Divide
Almost as soon as the World Wide Web was unleashed in the early 1990s, commentators began to talk about a “digital divide.” This was a reference to the regional and socioeconomic differences in access, speed and technical capacity for using the Web. Rural areas, for example, were identified as one area where this digital divide was most pronounced (some would say such a divide persistently remains). Globally, parts of the developing world had uneven access to computers and the web. With the arrival of 5G capabilities, there is every reason to expect that the digital divide will remain a chronic condition.
With the ever-growing capabilities of artificial intelligence made possible through deep learning techniques, we are witnessing an emerging “cognitive divide.” This divide will be manifested in three ways.
We are already seeing the outlines of the first. Algorithms already exist that excel at certain cognitive tasks once deemed exclusive to humans. These are repeatable and routinized, but nevertheless complex, cognitive skills. Generally speaking, there is an emerging divide between the so called left-brain skills that can be mimicked by algorithms vs. right brain abilities at which, for the moment, humans excel: emotions, curiosity, wonder, awe, creativity, inquisitiveness.
Second, we will see a widening gap between algorithmic abilities and human abilities. It is not only that algorithms are good at certain left-brain cognitive skills: in some cases they are proving to be vastly superior to humans. The best go-playing algorithms, to take one example, are now significantly better the best human champions. In some areas, artificial intelligence will begin to outperform humans, opening one such gap in cognitive ability. Unless and until artificial general intelligence is developed — and this is far from a certainty — the cognitive strength of AI will come largely from performing discreet, largely left-brain, cognitive tasks. But in performing these tasks, AI will vastly exceed what humans would be able to do.
Third, as I’ve indicated before, I think the future will see a blending or a partnership between human and artificial intelligence (as opposed to a future where AI makes humans redundant). I think a more plausible future is one where we will “think together” with AI to achieve a level and kind of cognition that neither entity can achieve alone. But this “enhanced intelligence” will not be evenly distributed. That is, we are likely to see a split in the labor force between those who have been well-educated to interface with algorithms and those without the benefit of such education and opportunity.
A similar kind of divide is already present. “Automation is splitting the American labor force into two worlds,” reports the New York Times. “There is a small island of highly educated professionals making good wages at corporations like Intel or Boeing, which reap hundreds of thousands of dollars in profit per employee. That island sits in the middle of a sea of less educated workers who are stuck at businesses like hotels, restaurants and nursing homes that generate much smaller profits per employee and stay viable primarily by keeping wages low.” The headline for that article is “Tech Is Splitting the U.S. Work Force in Two.”
What is likely to occur in the near-term future is that employment will involve a split between those augmented by AI and those who are not. Those who have been educated to partner with AI will engage in a kind of cognition that those not so educated will simply not be able to match.
The cognitive divide is far from inevitable, of course. But if historical patterns provide any indication, we should anticipate that inequalities will be a persistent feature of the new cognitive landscape.