Editorial
Claims about the potential of AI for the future of work are coming fast and furious. Will AI skyrocket global productivity by 7%? Will a quarter of the workforce be disrupted by generative AI technology? Are companies that replace people with AI doomed?
These aren’t clickbait publications looking to take a sharp point of view on a popular but controversial topic. Nor are they upstart organizations looking to sow disruption into the minds of business leaders. These are established think tanks and publications staffed with renowned experts and journalists.
So, what’s going on? Why are we so obsessed with trying to figure out what will happen next?
Well, partially because it’s fun to know what’s coming next, and partially because it’s scary to not know what’s around the corner. But when it comes to making predictions about technology and its impact on work, you should know that prognosticators have an uneven track record.
Why Do We Get More Wrong Than Right?
Predicting the future is tough work for anyone. After a global pandemic and the slew of fundamental changes that have been taking place in recent years, we’d all be wise to be a little cautious about the reliability of our crystal balls.
But this is about more than just one columnist’s doubts about fantastical predictions. It seems that we’re not learning from history when it comes to the impact of technology. As Bhaskar Chakravorti, dean of global business at The Fletcher School of Tufts University, wrote for The Conversation, the impact of past tech waves on work surprised even the smartest folks when they happened.
While the digital transformation of the '80s and early '90s didn’t amount to the level of productivity gains that had been predicted by many experts at the time, the adoption of the web in the mid-'90s did lead to surges in productivity counter to some pessimists. Still again, the dot-com bubble bursting not long after cratered that productivity, while the pandemic temporarily boosted it. While the IT productivity paradox explains some of that phenomenon, it doesn’t account for it all.
So, why can’t we reliably figure this out? Chakravorti says it’s because social factors — i.e., people — are variables that prognosticators can’t account for accurately. For example, people’s reactions or rejection of generative AI would impact any productivity gains we could hope to predict from adopting this new technology. Regulation and mandates, also driven by people, will also play an important role in curbing or unleashing productivity and usage.
“Finally, given how wrong economists and other experts have been in the past, it is safe to say that many of today’s predictions about AI technology’s impact on work and worker productivity will prove to be wrong as well,” wrote Chakravorti. “Numbers such as 300 million jobs affected or $4.4 trillion annual boosts to the global economy are eye-catching; yet I think people tend to give them greater credibility than warranted.”
Related Article: What Happened to the Promised Future of Work?
Should We Stop Predicting the Future of Work?
If we are continually more often wrong than right when attempting to predict the future of work, why do we keep trying? Shouldn’t we just give it up?
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That may be easier said than done.
For one, we can’t stop predicting the future because we are incapable of not thinking about the future for very long. What we think will happen tomorrow, in five years or in 500 years is an innate part of the human experience.
But beyond our natural inclinations, we also shouldn’t want to stop predicting the future of work, even if we are wrong. Predictions, even incorrect ones, play a valuable role in the world. They challenge us to think beyond the present, something that is difficult to do on a day-to-day basis.
When you hear a dubious claim about how work is going to change, it makes you think about why work isn’t going in that direction. And that gives you valuable insights into how you might think things should or may change, what can and will be improved, how we can expect to progress — even if you don’t believe every clickbait article you read.
Related Article: Let's Spend Less Time Predicting the Future of Work and More Time Building It
Building Instead of Predicting the Future
That nobody knows exactly what will happen with AI should be an exciting prospect for digital workplace leaders. Instead of putting a lot of effort into being right about what the future holds, organizations can focus on building the future they want with the tools of today and tomorrow.
Predictions do play a valuable role in shaping and bringing a new perspective for leaders, even if they aren’t right. And if that perspective helps organizations get a clearer view of the future for themselves and their employees, that can only be a good thing for future-focused work leaders.
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