Futurist Mike Bechtel visited Des Moines Tuesday to speak at an event hosted by Holmes Murphy and Bankers Trust Co.
Bechtel recently left his role as chief futurist for the business consulting firm Deloitte. He held it since 2019. At Deloitte, he and his team worked to make sense of what is new in technology. He also serves as an adjunct professor teaching corporate innovation at University of Notre Dame.
Bechtel sat down with the Business Record after his prepared remarks for a conversation on AI, today’s workforce challenges and the environmental impacts of tech.
This interview has been lightly edited and condensed.
What does this generation of new workers need to consider when they’re looking for a job?
I often find myself saying, “Take it from a geek.” Tech comes last. And what I mean by that is there’s an unhealthy tendency in the technology community to start with the solution instead of the problem. And, the proverbial hammer, everybody gets excited to and attracted by the shiny hammer. But what really matters, and I think what has mattered for most of history is the rusty nail. The problem worth solving. My first piece of advice to today’s students and graduates is lead with need, because a problem worth solving or an itch in need of scratching, that is a relatively stable, enduring thing that you can focus your energies on, both your computer science chops, but also everything else you can bring to the table. I think if you skip that step and jump straight to tech and ideas and building, the odds of the stuff that you’re building and lining up with enduring needs is practically nil.
When I see computer science graduates struggling, and hear this higher order gnashing of teeth around was STEM a mistake or something, I think that critical thinking, problem solving, analytical thinking, those all matter more than ever. I think what’s coming under pressure is the rote memorization and mastery of arcane computer languages and to connect to the prior point, obsession with the details of the hammer, that matters less than ever. Memorizing anything is not a golden ticket anymore.
How do you know when you’ve got a great startup to invest in?
I was a venture capitalist from 2013 to 2019. I realized real quick that the technical sophistication of a startup is about 1/12 of what ultimately drives its success or failure. What did we ultimately look for? The idea was that we found that startups who had at least one customer, the work to take them from one to 1,000 was dramatically easier than the work to take them from zero to one. Because if somebody somewhere is willing to pull out their wallet and exchange even one hard-earned dollar for your thing, there’s a demonstration of utility there, whereas up until that moment, it’s just ideas. We would often say, if you can put together one or five or 10 customers, come on back, and we’re suddenly dramatically more interested, because it’s a sign that the flywheel is moving.
We found companies that sell a whole lot of a little thing, we found that they had an easier time and a richer trajectory than companies that sold smaller numbers of giant things. And it came down to a whole variety of business basics, but one was concentration risk. It’s hard to sleep at night when you have three marquee clients, each paying you a million bucks. That’s a lot of gnashing of teeth. And “I hope Jerry’s feeling good.” Compare that with selling an app, it’s like, “Ah, we lost 100,000 customers last week, but we gained another 106,000.” There’s more data. You’ve got three customers. You don’t really know what’s working or not. It’s three data points. When you’ve got 300,000 customers, [you can see] “Wow, they really prefer the bird to be red versus blue in that game, make it red.” So selling a lot of a little, as I called it, was a big one. Also, we talked to 4,000 startups in my time as an investor, and the No. 1 correlated thing with their success was the degree to which they were playing to win versus to avoid losing.
Data centers use a lot of land, energy and water. Are you worried about that?
Conservation of natural resources is of paramount concern. We don’t want to sully the planet. One of my favorite memories as a parent of little kids, back when they were little, was watching WALL-E. Clearly, we don’t want that energy. Something that occurred to me, and this is an analogy that helps me, what we’re building with AI, it’s society’s brain. What I’m coming to believe, is that what we’re building with AI is this higher level of emergence that says, “Yeah, people are smart, but wait until you see this systematized aggregation of everything we know and can know in one thing.” Here’s where I’ll finally answer the question: If we believe that what we’re doing with AI is building a brain, an outsourced brain for society, the human brain is about 3% of the human body’s weight. It uses 20% of the human body’s electricity. Thinking is expensive, even for us. So many of our calories go to our noggin. I feel like it stands to reason that society’s brain would use a fair share of society’s energy. Now, can it be allowed to do so in a destructive and WALL-E, scorched earth way? Heck no. But can we use it as the long-awaited business justification for getting small-scale fusion reactors working, getting wind and solar permitted and regulated and through the red tape fiasco? Yes and yes. So AI is human brains. Brains take a lot of energy, and let’s use that need as a case to get all the exciting energy innovations out of red tape land and into tomorrow.
We’ve talked about workforce and college, but what about younger students? How do we educate them about AI?
I do think AI conversance and AI fluency are and will be table stakes, much like, my generation it was, can you work a personal computer? To think that people’s resumes just 20 years ago would include skills like personal computing, Microsoft Word. Some still do, but those sorts of AI conversions or AI fluency skills both clearly become table stakes. People are going to need to say, “I can engineer a prompt.” Great, but I’ve got this belief that prompt engineering, it’s exactly how an engineer would describe critical thinking, the humanities, the liberal arts. Imagine you’re an engineer, and all you’ve ever done is engineer stuff. And you’re presented with this wild and wooly world of creative prompting. I think the real educational opportunity is in liberal arts, humanities, classics and first principles, arithmetic, science. Said another way, I think there’s going to be a huge return to breadth and renaissance. Dot connectors are going to have such a better time than dot perfectors in this next 25 years, because when it’s time to jump into the rabbit hole, light up the robot, but when it’s time to pull back and be like, “What if that’s going to be the human’s job?,” and the humans best equipped to do that are the people conversant in my experience and belief, arts and letters, humanities, critical thinking, the classics.