When Algorithms Make Managers Worse


Here is an excerpt from an article written by Mike Walsh for Harvard Business Review and the HBR Blog Network. To read the complete article, check out the wealth of free resources, obtain subscription information, and receive HBR email alerts, please click here.

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One of the newest dilemmas for leaders in an age of AI is when and how to use algorithms to manage people and teams. AI, algorithms, and automation might allow you to manage more people at scale, but that doesn’t mean they will make you a better leader. In fact, quite the opposite may be true: technology has the potential to bring out the very worst in us.

Without careful consideration, the algorithmic workplace of the future may end up as a data-driven dystopia. There are a million ways that algorithms in the hands of bad managers could do more harm than good: How about using an algorithm to set your work rosters so that the number of hours is just below the legal threshold for full-time employment? Or automatically sending emails to people when they are more than five minutes late to work? Or nudging people to work during the time they normally spend with their families by offering incentives? Or using sensors to monitor warehouse workers and then warning them when they take too long to stack a shelf? Or constantly adjusting the color temperature of your office lighting so that your employee’s circadian system thinks that late afternoon is still morning?

Don’t think these kinds of things would happen? It’s already happening. Amazon, for example, has received two patents for a wristband designed to guide warehouse workers’ movements with the use of vibrations to nudge them into being more efficient. IBM has also applied for a patent for a system that monitors its workforce with sensors that can track pupil dilation and facial expressions and then use data on an employee’s sleep quality and meeting schedule to deploy drones to deliver a jolt of caffeinated liquid so its employees’ workdays are undisturbed by a coffee break.

We have been here before. About a hundred years ago, the world experienced the Scientific Management revolution, or more popularly, Taylorism. U.S. industrial engineer Frederick Winslow Taylor had a lot of ideas about how companies might integrate machines and workers for maximum efficiency, and he wrote them all down in his 1911 book, The Principles of Scientific Management.

Many principles of Taylorism are being revived today with a digital or AI-based twist. Consider this list of ideas taken straight from Taylorism: empirical data collection; process analysis; efficiency; elimination of waste; standardization of best practices; disdain for tradition; mass production and scale; and knowledge transfer between workers and from workers into tools, processes, and documentation. That might sound like a twenty-first-century digital transformation plan, but they are all ideas that Taylor had all those decades ago, and when taken to extremes, or put into practice with little regard for the humans carrying them out, the result is alienation and disengagement.

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Here is a direct link to the complete article.

Mike Walsh is the author of The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You. Walsh is the CEO of Tomorrow, a global consultancy on designing companies for the 21st century.


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