Despite dramatic advances in technology, most of the world’s economies have been stuck in a long period of slow growth and slow productivity. This is one of the most serious challenges in our 21st century economy. Opinions abound, but there’s little consensus on its causes, and, nobody seems to know what to do about it, or how long it will likely last, – years or decades.
In a recent article in the MIT Sloan Management Review, MIT Research Fellow Michael Schrage proposed a provocative and counterintuitive approach for enhancing innovation and productivity through man-machine collaborations. Schrage’s approach has been more influenced by behavioral economics than by technology or algorithmic advances. Instead of just asking how can people create more valuable innovation?, why not also ask How can innovation create more valuable people? Don’t just leverage advanced technologies, – e.g., bots, software agents, and digital assistants, – to automate away a large portion of the workforce, but also focus on enhancing innovation and productivity by leveraging technology to create higher-performance versions of employees.
“Designing and training smarter algorithms may be cheaper and easier than retraining smart people,” wrote Schrage. “Advocates of autonomous systems and machine learning typically innovate to minimize or marginalize human involvement in business processes. For them, people are part of the problem, not the solution. Organizations that take productivity seriously, however, understand that false dichotomies make poor investments: Smarter machines can – and should – be keys to unlocking greater returns from human capital.”
Earlier this year, the McKinsey Global Institute published A Future that Works: Automation, Employment and Productivity, the results of a two year study of automation technologies and their potential impact on jobs over the next several decades. Most jobs involve a number of different tasks or activities. Some of these activities are more amenable to automation than others. But just because some activities have been automated away, does not imply that the whole job will disappear. To the contrary, automating parts of a job will often increase the productivity and quality of workers by complementing their skills with machines and computers, as well as by enabling them to focus on those aspect of the job that most need their attention.
The McKinsey report estimated that less that 5 percent of all occupations can be entirely automated using existing technologies, but that some of the component tasks of almost all occupations will be automated. The big transformation of the workplace will not be the wholesale replacement of humans by machines, but rather, the large portion of jobs that will be restructured by technology. As the report notes, “humans will still be needed in the workforce: the total productivity gains we estimate will only come about if people work alongside machines. That in turn will fundamentally alter the workplace, requiring a new degree of cooperation between workers and technology.”
We’ve long been leveraging technology to help increase productivity. Think of engineers using CAD tools to develop complex products, or the new generation of robots working alongside humans in manufacturing. Most of us make extensive use of personal productivity tools in our work and daily lives, – as I’m now doing while researching and writing this blog.
But Schrage takes man-machine collaboration to a new level. He proposes using data-driven recommendation engines to help us identify the attributes we need to boost and the weaknesses we need to mitigate. “In other words, use technology to craft a better self rather than build a better agent.”
Continue reading the full, orginal blog by Wladawsky-Berger here.
Read more from Michael Schrage on this topic in his research brief here and in this blog.