Algorithmic Management: What Is It (And What’s Next)?

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The growth of the “gig economy” in recent years has revolutionised the way that millions of people work. Proponents argue that the gig economy gives people more flexibility and opportunities and lowers barriers of entry to the labour market, while detractors say that it erodes workplace regulations and standards while encouraging businesses to treat workers as increasingly disposable.

No matter which side of the debate you fall on, it’s clear that the gig economy is here to stay. But with more and more people signing up for these flexible and freelance work arrangements, how can businesses manage them effectively?

Enter “algorithmic management”: the use of algorithms to oversee the efforts of human workers. As algorithmic management becomes more commonplace, it’s important to understand what this practice is, the pros and cons of using it, and what the future holds.

What is algorithmic management?

Algorithmic management, as the name suggests, is the use of computer algorithms and artificial intelligence techniques to manage a team of human employees. By collecting massive quantities of data, in particular data about employee performance, algorithmic management seeks to automate large portions of the managerial decision-making process.

While it’s tough to estimate just how prevalent algorithmic management is, there are a few indications. For example, 40 per cent of human resources departments in international companies are currently using AI applications. Below are just a few ways in which algorithmic management has begun to enter the mainstream:

• The video interviewing software platform HireVue is experimenting with a facial analysis AI that assesses factors such as a candidate’s facial expressions, tone of voice, and use of language. HireVue argues that the new system can speed up the hiring process by 90 per cent, while critics say that it could reinforce existing societal inequalities.
• Workers at Amazon’s warehouse in Melbourne, Australia are managed by algorithms that determine which items need to be picked, moved, stored, and shipped. Employees say they feel pressured to improve their “pick rate,” a metric that calculates how many items are retrieved from…