How AI can bridge diversity gaps
This year in Davos, naturally climate change and sustainability were on the agenda, but special attention was also paid to automation and its social impact.
An Oxford study already in 2013 predicted a 47 percent displacement of jobs due to automation. One of the debates in Davos this year was about the fact that a quarter of working women will have to change jobs in this age of computerization of the labor market.
The numbers for working men are not very different from those for women. These developments however offer an opportunity to close the existing inequality between working men and women – the so called “gender gap”.
While just about everyone is now finally convinced such a gender gap exists, new technological developments such as artificial intelligence – and subsets such as machine learning, deep learning and robotics – offer opportunities to correct that inequality. Both men and women will be confronted with the displacement of certain types of jobs. Many already are. Jobs that can easily be automated such as work in call centers, customer service, recruitment, jobs in factories (if not already automated), and all sorts of other “repetitive” activities will all soon be taken over by an “AI”.
This will happen gradually, and if we better guide the transformation for (working) women, they will be able to gain a competitive advantage with which the existing inequality may be rectified. At Davos subsequently there was again the appeal to continue to encourage women to choose STEM studies, of significance since they now account for only 35% of the student population. This does not only apply to women, but also to other groups that are underrepresented.
It’s a hopeful message from Davos, but one that seems a bit like “greenwashing” if you consider the diversity and inclusiveness of the entire forum itself. Of Davos 2,821 participants, only 24 percent of them were women. In the case of CEOs of companies that are part of the Fortune Global 500, only 14 are women, less than 3%. Less than 0.01% are women of color. Perhaps now that technological developments are bringing more and more appreciation for the qualities of neurodiverse people, this group at least will reach equality faster and more successfully. But diversity at large (gender, cultural, ethnically etc.) should be finally addressed as an utter necessary condition for growth.
It is to be appreciated that diversity and inclusiveness were again on Davos’ agenda, but simple calls for change do not lead to the desired result. The fact is that, regardless of which “under-represented” group is involved, the discussion is almost always about the opportunities of such a group to adapt to the norm and to make the shift to learn to work within the existing system. Perhaps we should stop thinking in these terms and create a truly inclusive environment for everyone.
We should focus on creating an environment where everyone feels appreciated for who he / she / ** is and where each is given the opportunity to make a crucial contribution to the growth of an organization. So let us hope that next year everybody at Davos will be talking about embracing differences and learning from them, adaptation by the “typicals” instead of the “a-typicals” and very importantly on how AI and technological innovations can help bridge any gap by transforming and adapting to the changes of an age of automation.