There is an inevitable chapter in Martin Ford's compelling and well-written new book Rise Of The Robotscalled "White-Collar Jobs At Risk," and it begins with an anecdote I find horrifying.
In October 2009, the Los Angeles Angels beat the Boston Red Socks in the American League playoff, a thrilling win that came with the kind of dramatic subplot that makes sports such an emotional and cathartic experience. A promising Angels pitcher, Nick Adenhart, was killed by a drunk driver a few months earlier, and the team and the city of Los Angeles were carrying his banner through the playoffs. As a one-time sports writer (shameless plug), I know the allure of that kind of narrative, and so it's no surprise that a trove of articles issued forth bandying the idea that the Angels were playing in honor of their fallen teammate. Ford reprints one of these in its entirety. Then he reveals that it was written by a piece of software.
Good writing, like quality coding, straddles the intersection of artistry, technique, and experience, and that dynamism seems to preclude it from automation. The article Ford includes certainly isn't a stylistic triumph, but it is technically proficient, hitting the necessary beats of a piece of news writing, and artistry, after all, is a moving target.
As Ford points out, it may also be a less human summit than we assume. Cognitive computing and genetic programming will soon do to even the most dynamic white collar workers what robots are doing to men and women on the assembly line. And it gets worse, according to Ford. "Indeed, because knowledge-based jobs can be automated using only software, these positions may, in many cases, prove to be more vulnerable than lower-skill jobs that involve physical manipulation."
The road to widespread joblessness and the attendant economic catastrophe it heralds starts with the current Big Data revolution. Ford believes there will be two important consequences to the proliferation of electronic data for knowledge-based occupations. "First, the data captured may, in many cases, lead to direct automation of specific tasks and jobs." Smart algorithms will be able to study the historical record and learn the methods to complete specific tasks, much the way students learn. Ford points to a system patented by Google in 2013 that analyzes personal emails and social media posts in order to "learn" how to generate automated emails and posts from specific users. With enough robust data offering a map, even tasks that seem complex and individualistic (ahem ... writing) are replicable.
The second way big data will impact knowledge-based jobs is by rendering the human analytic and management infrastructure redundant. "Whereas today there is a team of knowledge workers who collect information and present analysis to multiple levels of management, eventually there may be a single manager and a powerful algorithm."
The start-up WorkFusion makes software that analyzes projects, determines which can be automated, which can be crowd-sourced, and which must be done in-house, all of which is typically the work of a project manager. The intelligent software posts to job sites to hire freelancers and then uses the work they do to learn how those jobs might be automated in the future, meaning workers are unwittingly participating in their own obsolescence.
All of this might sound irrelevant to IT workers. After all, increasing reliance on computer systems in the workplace should make IT jobs more secure. Ford stifles that hope with this: The Cloud. He uses the example of IBM's Watson, which gained widespread attention on Jeopardy! and has since been adapted to fields like medical diagnostics. Watson is a consequence of the abundance of data available for analysis, but until 2013 it existed on specialized computers. Then, in November of that year, IBM announced that it was moving the cognitive computer to the cloud.
That may seem innocuous, but Ford argues that "the migration of leading-edge artificial intelligence capability into the cloud is almost certain to be a powerful driver of white-collar automation." Why? Because the system will be widely available to companies without the need of a physical infrastructure, which means fewer jobs for individuals to maintain such an infrastructure. The trend is spreading quickly. You can already rent 10,000 servers from Amazon for about $90 an hour, and an increasing number of business applications are available exclusively on the cloud.
Ford does offer a way forward. In his conception, the answer is a combination of short-term policies and longer-term initiatives, one of which is a radical idea that may gain some purchase among gloomier techno-prophets: a guaranteed income for all citizens. If that stirs up controversy, that's the point. The book is both lucid and bold, and certainly a starting point for robust debate about the future of all workers in an age of advancing robotics and looming artificial intelligence systems. One thing Ford does very effectively is argue that no one will be immune from the new labor realities. Sadly, that includes the humble writer.