Recently, I gave a keynote speech at a conference in Sao Paulo, Brazil—from MIT campus via a live telepresence robot. The mode of delivery was fitting, as the topic of my talk was the Internet of Things, or, more specifically, what I call the Human Face of the Internet of Things.
Working at MIT, I can’t help but be amazed by the latest and greatest technology innovations, many invented right here. It’s important to note, however, that my fascination with these wonders of ingenuity is tempered by what I hear from thousands of business executives who participate in our executive education programs at MIT Sloan School of Management. Some are thrilled by the possibilities afforded by the increasing digitization of work. Others are anxious about staying professionally relevant. None doubt the scale and significance of the technology-led business transformation that keeps gaining momentum globally.
With this in mind, along with other organizations concerned with the future of the human workforce, MIT Sloan Executive Education became one of the founding members of the Internet of Things Talent Consortium. This group’s goal is to be a resource that organizations in any sector can use to create and grow the workforce needed to drive IoT-enabled digital transformation, and we are happy to be part of that.
Keeping up with the robots
The future of work is a topic of deep interest and enthusiastic discussion at MIT. Leading researchers in many fields—from economics and sociology to computer science and robotics—are exploring ways for humans to continue contributing to the labor force, even as more and more aspects of labor become automated or digitized. Of course, the introduction of new technologies that affect work and society is not new, but the pace at which this is happening is ever increasing. This means that the further you fall behind, the harder it is to catch up.
Consider what happens with the introduction of a new technology or invention that creates an advantage for those who adopt it. Maybe historically that was motorized transportation; or the typewriter, telephone or desktop computer, the Internet, or currently the latest AI tools. Adopting this innovation confers an advantage to the adopter, for example, an increase in productivity. The nature of that increase is a “step function”—a fixed amount of improvement for each new technology adopted.
Staying ahead of the curve
In the past, new technologies came one at a time, and there was plenty of time for a late adopter to catch up. But fast-forward to today and the innovations are coming along so thick and fast that these discrete steps have merged into a continuous and exponential curve. If you are familiar with “Moore’s Law,” it says that the power of computers doubles every eighteen months or so, which gives rise to a similar exponential shape.
In the past, there may have actually been advantages to not being an early adopter. Fast followers (or even slow ones) could learn from the experience of early adopters and wait until (in many cases) the costs of implementing the innovation decreased. Now, however, because its gradient is always increasing, if you fall off the curve even for a little while, you’ll inevitably have a much harder time catching up. Thus, change is no longer a project but instead has to become a state of being. Being able to learn and adapt—constantly and forever. Moreover, to be a leader, it is not even enough to stay “on the curve,” you have to get ahead of the curve, constantly. While this might seem like it’s all about technology, it’s not—the human dimensions are actually key.
My MIT Sloan colleague Thomas Malone, a professor of management, calls this phenomenon “superminds.” In his book that came out last year, Professor Malone explores the different ways groups of people make decisions, and how new forms of artificial intelligence, especially machine learning, can help. Malone predicts that AI, robotics, and automation will destroy many jobs—including those of high-skilled knowledge workers—while at the same time creating new ones. He believes that by investing in the right kinds of AI, organizations can help keep workers productive and happy—and make sure our “superminds” are actually smarter than our regular brains.
For all of us humans, the good news is that we evolved and survived to be highly adaptable, capable of learning as individuals, and also working in concert with each other and the tools that we invent. Which means that whatever your function or profession may be, you need to embrace every opportunity you can to learn—to understand the implications and possibilities, and also the risks.
Strengthening “soft” skills
So, what are the skills and capabilities we need? Of course, there are the technical skills. But what we are seeing in our classrooms and out in the business world is that the so-called “soft” skills—organizational and collaboration skills, which are, in fact, so human—often make the difference between success and failure in these technology-driven arenas.
All these human skills are not new and they don’t necessarily require specialized technical education, although that often helps. What is needed, at a minimum, is an understanding and appreciation of the technological context. It is more important than ever to be curious about the impacts of technology for professionals and the nature of professional work, and the roles and responsibilities that different professions might take on in helping shape the future.