Artificial Intelligence Will Kill 47 Percent Of Jobs In The Next 10 Years And Women Will Be Needed More Than Ever

Posted on February 8, 2017 by Lioness Staff

IMG_4735Have you heard the riddle about the boy and his father who are in a car accident? The father dies at the scene, and the boy is rushed to the hospital in critical condition. Upon entering the operating room to attend to the boy’s injuries, the surgeon immediately responds, “I can’t operate on this patient. He’s my son.” How is this possible?

When I first heard this riddle a few decades ago, it was a known stumper and often revealed the implicit gender biases of the stumped. If you haven’t figured it out by now, the surgeon, naturally, is the boy’s mother. It took my six-year-old daughter all of five minutes to deduce the answer herself when I recently posed the riddle to her. As the child of two working parents—and one who’s own doctor and dentist are both female—she found the answer obvious. To me, that was a relief. She’s growing up with a much more level playing field—in her mind at least.

To many older generations, however, a female surgeon is still not so automatically obvious, and the statistics seem to justify their assumption. According to a 2014 report of the Association of American Medical Colleges, women account for only 22 percent of full-time surgery faculty and only 1 percent of all surgery department chairs, despite comprising 47 percent of medical students and 46 percent of medical residents. There are similar statistics in many other fields that indicate the disparity in female leadership roles. Women hold roughly 26 percent of U.S. college presidencies, only 19 percent of U.S. Congressional seats, and a staggering low 4.2 percent of CEO positions in the Fortune 500.

Most recently, U.S. presidential candidate Hilary Clinton failed in her attempt to shatter in her words, “that highest and hardest glass ceiling”—the one that has so far kept a woman from occupying the oval office. It’s the same one that led my daughter, who hasn’t yet bumped up against such barriers, to see a school poster featuring the portraits of all 43 U.S. presidents and 47 vice presidents and ask me in perplexed earnestness, “Why are there no girls?”

Political pundits have blamed Clinton’s loss to President-elect Donald Trump, at least in part, on his ability to rally support among Americans—particularly white males—who mourn and fear the loss of jobs, status, and stature to illegal immigrants and foreign trading partners.

There’s a much more powerful force at play than China, Mexico, or illegal immigration, however. It’s one that will obliterate tens of millions more U.S. jobs than any trade deal ever could and one that can’t be contained by any wall. That force is advancing technology. Ironically, however, that force will likely give females a boost in assuming more leadership positions and closing the gender gap. That’s because technology will exacerbate the need for the kind of social and emotional intelligence and related collaboration and leadership skills and temperaments that women on average exhibit and master much more easily than men.

Advancing technology such as artificial intelligence, deep machine learning, the Internet of Things, nanotechnology, advanced robotics, and biotechnology are highly likely to automate and thus displace 47 percent of U.S. jobs in the next 10-15 years, according to researchers at Oxford University. That statistic includes, manufacturing, service, and professional jobs.

One effect of this, as my co-author Edward D. Hess and I explain in our book Humility Is the New Smart: Rethinking Human Excellence in the Smart Machine Age (Berrett-Koehler, 2017) is that to add value to any organization or client, humans will need to complement technology through critical, creative, and innovative thinking and emotionally engaging with other humans. Humans will need to be problem solvers and team players who listen to and empathize and collaborate with other humans. They will need to have the humility to experiment, learn iteratively, and adapt to environments that are volatile, uncertain, complex, and ambiguous. To lead others, they will need to embody and role model these human attributes.

It’s beyond the scope of this article/post to delve into the exact reasons why due to nature or nurture women tend to be better at the kind of social, emotional, and collaboration skills that increasingly will be required in leadership roles. Scientific data indicates that, generally, they just are. For example, women on average score higher than men on measures of emotional intelligence, including the ability to empathize with others, and lower than men on rates of narcissism. With respect to teams, researchers at MIT and Carnegie Mellon have found that there’s something called “collective intelligence” that explains a group’s effectiveness, and this “c factor” isn’t at all correlated with the cognitive abilities of the group’s individual members. It correlates instead with (1) the level of “social sensitivity” of group members (how well they perceive each other’s emotions); (2) the equality in distribution of conversational turn-taking; and (3) the proportion of females in the group (the reason being women, on average, exhibit more social sensitivity and turn-taking).

Artificial intelligence in particular—deep learning or machine learning—will transform our economy and our work lives in the very near future. Our best chance of staying relevant professionally is to excel at those skills that are uniquely human: to engage emotionally with others and to think critically, creatively and innovatively. Many of those activities play to women’s strengths, and we’ll likely start to see the effects of that throughout the professional landscape over the next decade. Whether it’s in running big corporations, hospitals, or the White House, technology may well help women shatter the hardest glass ceilings once and for all.

Katherine Ludwig is co-author with Edward D. Hess of Humility Is the NewSmart: Rethinking Human Excellence in the Smart Machine Age (Oakland, CA: Berrett-Koehler, 2017).

 

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