What does the future of work look like? How are emerging technologies, such as artificial intelligence (AI) and automation, creating opportunities for new types of jobs and demand for new types of skills? Where should industry leaders invest to foster competition, increase productivity, and create a more inclusive workplace? And what can policymakers do to ensure that the next generation of employees have the education and training to succeed?
These are pressing questions for our global economy and they are especially urgent here in Brazil. In the aftermath of a severe economic crisis and recession, Latin America’s largest and most industrialized economy is facing a slow and uneven recovery. More than 10% of the country’s workforce is unemployed, and a quarter of the unemployed population is between the ages of 18-24. Meanwhile, about 13 million Brazilians work less than they could or would like to.
The digital age is impacting all aspects of life, including the future of work. Technological innovations have the potential to transform the workplace and enhance productivity, but it will take proactive and thoughtful discussion to harness these innovations for social benefit.
To explore this further, MIT Sloan Experts is hosting the #MITSloanBrazil Twitter chat on August 21 at 9 a.m. ET (10 a.m. São Paulo) to discuss the topics and themes of the upcoming Future of Work Conference in Brazil.
The conference, which will bring together leading experts from business and academia, aims to highlight the ways in which artificial intelligence, automation and the changing economy are affecting the future of work. This issue is crucial in Brazil, where 12 percent of the country’s workforce is unemployed.
Join us on Twitter on August 21 at 9 a.m. ET (10 a.m. São Paulo) and follow along using the hashtag #MITSloanBrazil. Your comments and questions are encouraged! Simply include #MITSloanBrazil in your Tweets.
The path to skill around the globe has been the same for thousands of years: train under an expert and take on small, easy tasks before progressing to riskier, harder ones. But right now, we’re handling AI in a way that blocks that path — and sacrificing learning in our quest for productivity, says organizational ethnographer Matt Beane. What can be done? Beane shares a vision that flips the current story into one of distributed, machine-enhanced mentorship that takes full advantage of AI’s amazing capabilities while enhancing our skills at the same time.
Matt Beane is a Research Affiliate with MIT’s Institute for the Digital Economy.
Thomas W. Malone is the Patrick J. McGovern (1959) Professor of Management, a Professor of Information Technology
From Management Today
We often overestimate the potential for AI because it’s easy to imagine computers as smart as people. Science fiction is full of them. But it’s much harder to create such machines than to imagine them.
All of today’s most advanced AI programs are only capable of specialised intelligence —doing particular tasks like recognising faces, playing Jeopardy, or driving cars. But any normal human five-year old has far more general intelligence — the ability to learn and do many different tasks — than even the most advanced computers today. Experts on average predict that human-level artificial general intelligence is about 20 years in the future, but that’s what they’ve been predicting for the last 60 years.
On the other hand, we often underestimate the potential for using computers to provide hyperconnectivity — connecting people to other people (and machines) at massive scales and in rich new ways. In fact, it’s probably easier to create massively connected groups of people and computers (like the Internet and social networks) than to imagine what these ‘superminds’ will actually do.
Superminds – such as hierarchies, markets and communities – are composed of people and computers doing things together that neither can do alone. For example, superminds use machines to do complex calculations but people to decide which programmes to run in the first place and what to do when things go wrong.
While we agree about the seismic changes afoot, we don’t believe this is the right way to think about it. Approaching the challenge this way assumes society has to be passive about how tomorrow’s technologies are designed and implemented. The truth is there is no absolute law that determines the shape and consequences of innovation. We can all influence where it takes us.
Thus, the question society should be asking is: “How can we direct the development of future technologies so that robots complement rather than replace us?”
The Japanese have an apt phrase for this: “giving wisdom to the machines.” And the wisdom comes from workers and an integrated approach to technology design, as our research shows.