Erik Brynjolfsson is an economist at MIT and co-author, with Andrew McAfee, of The Second Machine Age, a book that asks “what jobs will be left once software has perfected the art of driving cars, translating speech, and other tasks once considered the domain of humans.” The rapidly emerging fields of AI and data science, spawned by the ubiquitous role of data in our society, is producing tools and methods that surpass human ability to manage and analyze data.
You can often hear people say that, just like other technological revolutions, new jobs will be created to replace the old ones. But is this just a rationalization? Maybe the rate of technological change is of a different order in the Information and Big Data age compared to the industrial revolution. A more optimistic outcome than automation leading to mass unemployment is to see these technologies as tools that will allow people to achieve more; for example, working together with cognitive assistants.
So, which way will it be?
For AI and data science professionals, don’t we have a responsibility to use and seek data-based evidence to support our positions on the impact of data science and AI on future employment? Can we find and analyze data on what happens to actual workers being replaced over the past five years? Some researchers estimate that 50 percent of total US employment is in the high-risk category, meaning that associated occupations are potentially automatable. In the first wave, they predict that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labor in production occupations are likely to be substituted by smart-computer capital.
Policymaking will no doubt lag behind the technology. Now is the time to discuss and advocate policies that address (1) innovating our education systems, (2) redefining employment, and (3) investigating alternate economic systems.