Find the Magical Balance: Interview with Dr. Eric Siegel, Author of The AI Playbook

I recently went one-on-one with former Columbia professor Dr. Eric Siegel, author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.

Adam: Thanks again for taking the time to share your advice. First things first, though, I am sure readers would love to learn more about you. How did you get here? What experiences, failures, setbacks, or challenges have been most instrumental to your growth?

Eric: When I was 12 -- in seventh grade in the early 80s -- I had to give an oral report in English class on a topic of my choosing. To stay in my comfort zone, I decided to present on computer programming, which I'd been nimbly executing for a couple years on my Apple ][+.

I wrote some code on the chalkboard, stepped through it, and triumphantly concluded with, "Those are the basics!" My close friend and comrade in arms, Alex, sat in the audience, looking satisfied.

But the teacher himself bemoaned, "Uh... yeah, right," and the rest of the class broke out in laughter.

Since then, I've experienced plenty more such moments, where my enthusiasm about tech is met with a blank look -- as if the coolest thing in the world is, like, arcane or something! It's always a helpful reminder to come back to Earth.

But I never gave up. I've since made something of a career out of bridging the gap between nerd and normie. First, as a professor teaching the computer science "intro for poets" lecture course and later as a business consultant, author, speaker, conference organizer — and in executing machine learning projects, which turn out to only be successful when you bridge that gap.

Adam: What do you hope readers take away from your new book?

Eric: To pursue the concrete value of AI -- or, to be specific, machine learning, which is the central basis for and many mean by AI -- you must drill into the details of precisely how that value will be delivered.

Plus -- and this is the important point -- you will not find it hard to grasp.

How machine learning helps business is not only understandable, it's fascinating. A concrete sense of how it works is simpler than high school algebra, and a hell of a lot more interesting. It totally matters -- it's how data and science improve business operations.

And, machine learning needs you! Once you've ramped up, more than anything, non-data scientists like you are exactly what machine learning projects need. 

In a nutshell, here's what you need to know about each machine learning project: What's predicted, how well, and what's done about it. 

For example, to retain more customers, predict which ones are most likely to cancel and then market to them, reaching out with an offer meant to retain them.

To help guide each ML project, business leaders have got to dig into a bunch of details about these aspects of the project -- but the only math involved is arithmetic. Okay maybe sometimes a bit of algebra.

This kind of data literacy is for everyone -- it's like driver’s education, not auto-mechanic school. I wrote The AI Playbook in order to get any reader up to speed -- painlessly, I promise. 

Adam: What should leaders understand about machine learning and AI?

Eric: While generative AI gets the hottest spotlight right now, there's a preexisting trend that's got much more money thrown at it and is continuing to quickly grow: predictive AI, aka predictive analytics -- that is, enterprise applications of machine learning that improve operational decisions with prediction. This is the kind of AI you turn to for boosting the performance of existing, large-scale processes. It serves to better target marketing, fraud mitigation, financial risk management, logistics, and virtually all kinds of large-scale operations.

Adam: How can leaders most effectively leverage machine learning and AI today?

Eric: In The AI Playbook, I present a six-step practice for ushering machine learning projects from conception to deployment, which I call bizML. To date, there is no established standard practice/playbook/framework well-known to business leaders. In fact, most non-data scientists haven't even come to learn that success with machine learning requires a specialized leadership practice in the first place.

Here's the rarely implemented trick. Each of these steps -- which starts by reverse planning for the final step, deployment -- must be carried out jointly with deep collaboration between data scientists and business leaders who have ramped up on the semi-technical understanding I outlined earlier.

Adam: How will leaders be able to most effectively leverage machine learning and AI two years from now? Five years from now? Ten years from now?

Eric: Ramp up on the semi-technical know-how now -- understand what it means to dive into what's predicted, how well, and what's done about it -- and you will be light years ahead of most business stakeholders when it comes to adopting machine learning. In less than a year, you'll have your first, successfully deployed machine learning initiative under your belt -- a much more rare success than you may realize. Five years from now, recruiters will be doing backflips for you. As for a decade from now, that's a bit far away to imagine -- I do believe that futurism will by then be entirely out of style...

Adam: What do you believe are the defining qualities of an effective leader? How can leaders and aspiring leaders take their leadership skills to the next level?

Eric: When it comes to machine learning, the most common mistake is easily avoided once you become aware of it. Leaders typically relegate all project details to the data scientist rather than getting involved in the particulars. That's a costly error that usually means project failure. Instead, recognize that it’s a business operations improvement project that uses machine learning, rather than a project that's only about the core number crunching itself. The number crunching delivers predictions and your business now needs to integrate those predictions so that they improve operational decisions. This means a change to operations that must be clearly, transparently, and credibly planned for -- in great detail -- from the get-go.

Adam: What are your three best tips applicable to entrepreneurs, executives, and civic leaders? 

Eric: 1) Floss your teeth every day.

2) Take on the ambition of finding joy and serenity without vices (be they substances, certain social activities, TV watching, etc.) -- a very worthy ambition that isn't that hard if you make it a clear intention.

3) Improve the effectiveness of large-scale operations with science. That's machine learning in a nutshell.

Adam: What is the single best piece of advice you have ever received?

Eric: "You're thinking too much" and "you're glossing over the details." These two vital pieces of advice completely contradict one another. To bridge the mammoth gap between tech and business and generate business value, the art is in finding a magical balance between those two messages.


Adam Mendler is an entrepreneur, writer, speaker, educator, and nationally-recognized authority on leadership. Adam is the creator and host of the business and leadership podcast Thirty Minute Mentors, where he goes one on one with America's most successful people - Fortune 500 CEOs, founders of household name companies, Hall of Fame and Olympic gold medal-winning athletes, political and military leaders - for intimate half-hour conversations each week. A top leadership speaker, Adam draws upon his insights building and leading businesses and interviewing hundreds of America's top leaders as a top keynote speaker to businesses, universities, and non-profit organizations. Adam has written extensively on leadership and related topics, having authored over 70 articles published in major media outlets including Forbes, Inc. and HuffPost, and has conducted more than 500 one on one interviews with America’s top leaders through his collective media projects. Adam teaches graduate-level courses on leadership at UCLA and is an advisor to numerous companies and leaders. A Los Angeles native, Adam is a lifelong Angels fan and an avid backgammon player.

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