Robots and algorithms are getting good at jobs like building cars, writing articles, translating — jobs that once required a human. So what will we humans do for work? Andrew McAfee walks through recent labor data to say: We ain’t seen nothing yet. But then he steps back to look at big history, and comes up with a surprising and even thrilling view of what comes next. (Filmed at TEDxBoston.)
Andrew McAfee is Associate Director and Principal Research Scientist at the MIT Center for Digital Business and co-author of “Race Against the Machine”
MIT Sloan Prof. Thomas Kochan Photograph by Stu Rosner
From Harvard Magazine
An interview with Thomas A. Kochan, Bunker professor of management, MIT’s Sloan School of Management, and co-director of the MIT Institute for Work and Employment Research.
Harvard Magazine:You speak of a fundamental human-capital paradox in the way American employers and workers interact with each other.
Thomas Kochan: American corporations often say human resources are their most important asset. In our national discourse, everyone talks about jobs. Yet as a society we somehow tolerate persistent high unemployment, 30 years of stagnating wages and growing wage inequality, two decades of declining job satisfaction and loss of pension and retirement benefits, and continuous challenges from the consequences of unemployment on family life. If we really valued work and human resources, we would address these problems with the vigor required to solve them. Read More »
There is a fundamental change underway in the way that companies make decisions. Instead of relying on a leader’s gut instincts, an increasing number of companies are embracing a new method that involves data-based analytics. This ‘Big Data’ revolution is occurring mainly because technology enables firms to gather extremely detailed information from and propagate knowledge to their consumers, suppliers, alliance partners, and competitors.
Companies that use this type of ‘data driven decision making’ actually show higher performance. Working with Lorin Hitt and Heekyung Kim, I analyzed 179 large publicly-traded firms and found that the ones that adopted this method are about 5% more productive and profitable than their competitors. Furthermore, the study found a relationship between this method and other performance measures such as asset utilization, return on equity and market value. There is a lot of low-hanging fruit for companies that are able to use Big Data to their advantage. Read More »
Andy McAfee and I have just released a short e-book, Race Against the Machine. In it, we try to reconcile two important facts. 1) Technology continues to progress rapidly. In fact, the past decade has seen the fastest productivity growth since the 1960s, but 2) median wages and employment have both stagnated, leaving millions of people worse off than before. This presents a paradox: if technology and productivity are improving so much why are millions being left behind?
In the book, we document remarkable advances in digital technologies in particular. Innovations like IBM’s Watson, Google’s self-driving car, Apple’s Siri are turning science fiction into reality. Machines are doing more and more tasks that once only humans could do.
In the book (and now film) Moneyball, general manager Billy Beane transforms the Oakland Athletics by recognizing that overlooked players contribute value to a team. He overturns conventional wisdom, indeed upends baseball’s domination by wealthier teams,by using data to measure performance. What he learns can also apply to the economic challenges we face today.
When people think and write about what leads to economic success, they too often focus only on the most visible, highly paid players. In the case of the economy, it is the CEOs. The business press is full of praise for celebrity leaders such as Jack Welch and Steve Jobs. But even when the CEO is not movie-star famous, stories about whether a firm will succeed or fail usually focus on the personality and actions of the person at the top.