Aren’t they supposed to know stuff?

You might have seen this clip of Bill Gates explaining the Internet to David Letterman in 1995.

Or this one where Mark Zuckerberg explains the concept of “Thefacebook.com” to CNBC.

Both of these are fascinating time capsules – showing that as new technologies went mainstream, even the creators of groundbreaking technology didn’t truly know where would go.

And they are not alone. Thomas Watson Chairman of IBM in the 1940s (and the reason IBM’s AI initiative was called Watson) once predicted that there would be no more than 5 computers in the world. Henry Ford predicted that there would be an endless supply of fuel from fruit, and Steve Ballmer famously said that the iPhone would be an abject failure.

Why is this? After all, these leaders were among the most knowledgeable people about their domains in existence, and even they couldn’t figure it out. I think the answer to these questions says something about expertise and what we often get wrong about it.

I’ll admit I’m a bit worried about how this edition of the newsletter might be interpreted, so I want to state something important upfront. This is not one of those articles where the author claims officially recognized expertise is useless – rather its aimed at pointing out how spotting real expertise is more difficult than ever, why that’s a problem, and offers some thoughts on what to do about it.

The point here is that no one is an expert on everything, and no one ever has been. Even Leonardo DaVinci, probably the most famous polymath of all, would have been stumped if you wanted to talk poetry.

So, two things are true at the same time. We are all experts at something, and no one is an expert at everything. Not recognizing that costs us every single day.

Why did the scarecrow win an award? He was out standing in his field!

If I asked you to name an expert at your workplace, you might name your top software engineer or the woman who invented the widget you sell. Are they experts? Yes. Are they the only experts in your company? Absolutely not.

We tend to attribute expertise to two things at the workplace – easily measurable job-specific skills: “he has this PhD,” or easily measurable accomplishments: “She invented this.” But expertise is everywhere. The great middle manager who has spent 20 years in the field and deeply studied management practice? An expert. Every human working in your organization has some measure of expertise in something, and much of that expertise is untapped every day.

If we as teams and organizations can find, recognize, and celebrate our expertise, we can innovate more, build more cohesive teams, and increase engagement.

Why don’t scientists trust atoms? Because they make up everything!

The reason for this is, at its heart, simple. Rather than relying on true expertise, you are now making impactful decisions on the counsel of people who don’t really know what they are talking about. If I want to know where to aim my rocket to Mars, I’ll ask Einstein. But I won’t ask him to operate on my appendix.

Does this really happen? It does, and not just when we start listening to Elon Musk about our work-from-home policies (or the myriad of other things he pontificates about on X). There is even a pretty cool term for it that dates back to the early 1800s – ultracrepidarianism. People often step into new domains without realizing or acknowledging that their expertise doesn’t immediately translate. And in many cases, their status and confidence cause others to overly trust them. The result? Drowning out the true expertise and a bunch of bad decisions.

There is a new type of “expert” on the block—generative AI. A while back, I did a small experiment that I alluded to in a previous blog post. I presented a group of people with 200 words written by AI on a topic they were experts in and asked them to grade it. Then, I presented them with 200 words written on a topic they were not experts in and asked them to grade that. The grades in the second case were significantly higher.

There are several reasons for this, but in part, it’s ultracrepidarianism at work. AI has status, and it has confidence – and that confidence never slips, no matter how “uncertain” it is. So if we are not experts ourselves, we are likely to overtrust it.

That’s potentially dangerous – especially if it’s drowning out the voices of the real experts. This is something we go into in a lot more detail in our Thrive with AI program. For individuals, we look at how to make sure that you treat AI with appropriate skepticism, and we also look at how teams should be structured so they don’t fall victim to it.

Back to Bill

So why do these really smart technology company leaders not know where their technology is going? Of course, it is inherently difficult, but I’d also submit it because it is outside their area of expertise. These people often began as experts in a technology field and then became experts in assembling teams that could build their solutions at scale. They are not experts in how their solutions will be adopted, adapted, used, and misused in society over time.

Being a great forecaster involves thinking in terms of probabilities, balancing humility and confidence, curiosity, and skepticism, learning lessons without overlearning them, being fine with being wrong, and being an expert in their specific domain while having a beginner’s mindset. Perhaps most critically, it involves self-awareness about what they do not know in adjacent domains that may affect their judgment. It’s rare to find anyone with these attributes, and very few of them run major companies.

So, I think it’s time for us all to look deeper at expertise. Be open to the fact that we live in a world where expertise is missed, and false expertise abounds. If we can fix that, we can all get a bit smarter.