Professor of Information Technology,
Director, The MIT Initiative on the Digital Economy
We’re in the early stages of a management revolution. The upheaval is based on our unprecedented ability to collect, measure and digitally record information about human and systems activities, particularly with the finely tuned data sets available through IoT. One of the hallmarks of this new era is the acceleration of data-driven decision making within businesses, which has tripled in just five years, according to a recent study I conducted with Kristina McElheren, a professor at University of Toronto.
Accompanying the progress anticipated in this increasingly digital age, however, will be thorny challenges and broader issues for society at large. This is particularly true as organizations begin to feed the large data sets available from IoT into systems that use machine-learning algorithms—at which point they will begin making predictions and decisions in an increasingly automated way, and at large scale.
Machine-learning and artificial intelligence (AI) technologies have advanced greatly in recent years; the implications range much further than the attention they get for winning competitions with “Go” champions and chess masters. The real significance of these technologies will be found in their ability to automate and augment complex decision making.
MIT Sloan Executive Director of Executive Education Peter Hirst
I recently attended the second annual Internet of Things World Forum in Chicago, IL. In the opening keynote presentation, Wim Elfrink, Cisco’s EVP of Industry Solutions and Chief Globalization Officer, referenced Gartner’s latest version of its“Hype Cycle,” noted that IoT (the Internet of Things) has climbed over the past year to its peak. Yet, on closer inspection, the enviable place IoT is enjoying within this technology-evolution framework is actually named the “peak of inflated expectations,” a precarious high point where individual dazzling success stories of early adopters and visionary speculation are outshining wider market reticence and slow early adoption. In the model, this magical time is usually followed by a “trough of disillusionment,” then — if the market responds favorably to second and third-generation tech — the “slope of enlightenment,” and finally — if wide market adoption takes place — a “plateau of productivity.”
The conference certainly provided many vivid illustrations of success and the potential of IoT, but will this fledgling industry make it through the inevitable coming trough, and climb “high and right” on the chart with predicted tens of billions of connected devices, as was enthusiastically espoused by Elfrink in his opening remarks?