The Characteristics of Algorithmic Leaders

Algorithmic leaders:

• Focus on future customers, not existing ones

• Seek to be ‘less wrong’ with time, rather than always being right

• Humanize and complexify, rather than standardize and simplify

• Are guided by user empowerment, rather than mere regulatory compliance

• Ask whether they have the right approach, rather than whether they are getting results

• Manage by principles, rather than processes

• Believe they should automate and elevate, rather than automate and decimate

• Transform for purpose, not just profit

public places; they hung out on Snapchat and Instagram. This has huge implications as companies start to think about how to serve the customers of 2030.

Most of us recognize that algorithms are only as good as the data they are built with. What does great data look like? How can we know it when we see it?

We’ve gone through a major shift in our understanding of data. If you go back 20 years, people saw data as a cost. Even today, you probably get notes from your IT manager saying ‘You’ve got way too much email; go in and delete some of it immediately!’ It is only recently that we all realized that data is valuable. Now, we want to keep everything, so there are these giant stores of data everywhere, and we seem to believe that at some point we’ll be able to sprinkle pixie dust on it and something amazing will happen. But when you look at the people doing interesting things with data and artificial intelligence, in many cases they are mostly teaching us about data collection. It’s not about having massive amounts of data. It’s about having the exact right sets of data to answer specific questions.

In a recent article you wrote that “technology has the potential to bring out the very worst in us.” Please explain.

Without careful consideration, the workplace of the future could end up as a data-driven dystopia. There are a million ways that algorithms in the hands of bad managers — and bad people in general — 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 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?

Some of this is already happening. Amazon 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. And IBM has applied for a patent for a system that monitors its workforce with sensors that can track pupil dilation and facial expressions and deploy drones to deliver a jolt of caffeinated liquid, so employees’ workdays are undisturbed by coffee breaks. Many principles of Taylorism are being revived today with a digital or Ai-based twist. And just as with Taylorism, reliance on algorithmic management may end up creating unease in the workplace and broader social unrest.

In the book, you encourage leaders to think like computers. What’s wrong with thinking like a human?

I actually encourage people to embrace computational thinking, which is slightly different. Computational thinking is about approaching problems and making decisions in a structured way that allows you to ultimately leverage technology, data and even automation to be more effective.

Getting kids prepared for the algorithmic age is not about teaching them how to use Twitter or Instagram; they already know about such things better than us. It’s not even about teaching them programming. What we actually need to do is teach kids to be ready to engage with the world and to approach decisions and problems in a way that leverages technology to make people more effective.

Whether you’re a programmer or an executive, this kind of thinking is invaluable. The rockstars of the 21st century will be leaders who can master both an understanding of human complexity and a flair for computational thinking. Machines will get dramatically better at extracting insights from data, spotting patterns and even making decisions on our behalf. But only humans will have the unique ability to imagine innovative ways to use machine intelligence to create experiences, transform organizations and reinvent the world.

Futurist Mike Walsh is the author of The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You (Page Two Books, 2019). Based in Sydney, Australia, he is the CEO of Tomorrow, a consultancy that designs organizations for the 21st century, with clients from the Fortune 500. Each week he interviews provocative thinkers, innovators and troublemakers on his podcast, Between Worlds.

Without careful consideration, the workplace of the future could end up as a data-driven dystopia.