5 Ideas to Save Human Skills in the Age of AI

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Matt Beane is an assistant professor in the Department of Technology Management at UC Santa Barbara and a Digital Fellow with Stanford’s Digital Economy Lab. Her research focuses on building skills in a world full of smart technology, often requiring fieldwork to investigate robotics and AI at work. Published on Management Science Quarterly again Harvard Business Review and speak on the TED stage. Matt also helped found and fund Humatics, an MIT-based, full-stack IoT startup.

Below, Matt shares five key insights from his new book,The Skills Code: How to Preserve Human Power in the Age of Smart Machines. Listen to the audio version—read by Matt—on the Next Big Idea app.

1. A 160,000-year-old school hidden in plain sight

Consider Athens, 507 BC. 12-year-old Meneos begins his second year tutoring Stephanos, a master sculptor. Today, he goes to the carpenter’s workshop to look for wood. Then a coppersmith for pins and bases. He puts it all back together and keeps it organized as the old boys finish scaffolding the new piece. Throughout the day, he hauls blocks of marble around the workshop, guided by the older boys, who take lectures from Stephanos. The sun is setting, everyone is cleaning up.

He was always watching. Noticing marble remains and curved tools. Listening as they tell stories and share ideas. Asking a question or two while doing his job. Next year, if he’s working hard, he’ll be splitting marble, keeping tools organized and sharp, and learning about the next jobs in the apprenticeship chain—turning out blocks, negotiating supplies, talking to customers. Six years later, he will be filming his first solo project on the outskirts of the city, with students looking up to him. And six years later, he will be recording his first solo work in his studio on the outskirts of the city, with new students looking up to him. All this is true, in his way: we have one of his masterpieces, a marble statue of Orestes and Electra, signed “Menelaos, pupil of Stephanos.”

When it comes to skill—skills we can rely on under pressure—this bond between experts and novices has been the foundation of skill development for thousands of years. In fact, the archaeological evidence is very clear that it has been around as long as we have had language: about 160,000 years.

2. Skill code

Over the past twelve years of my research, I have discovered the hidden code that makes expert-novice relationships stronger. When I say “code,” I’m talking about something like the DNA of how we learn our most important skills. That collaborative relationship between professionals and novices is the core of the three C’s that people need to develop skills:challenge,complexityagainconnection. Work within your limits, engage with the bigger picture, and build bonds of trust and respect. Like the four amino acids of genes, the three Cs are the basic building blocks for learning important skills. Look back, and you will find them focused on the story of Menelaos. You will find them in your own journey of success and in the way you have helped others build their expertise.

“Work within your limits, engage with the bigger picture, and build bonds of trust and respect.”

just asto knowgenetics was just the beginning of genetics, so it’s just the beginning of ability. Challenge, complexity, and communication must occur in some healthy, sometimes contradictory, ways to produce reliable skill. Sometimes, this follows a specific sequence that we are used to—that map to our beliefs about how skill development occurs. But our world is changing. New trends emerge, others die, and one size does not fit all people, professions, or organizations. Knowing this skill code empowers us not only to recreate a 160,000-year-old school, but to identify and maintain healthy skill building in any way we can in this dizzying modern world.

3. We are breaking the best school we have

If we don’t put the Skill Code information to use right now, our brand is in serious trouble; we treat smart technology in ways that subtly diminish human ability.

In millions of workplaces, we block the ability to learn new skills because we separate younger workers from older workers (beginners to experts) by putting technology between them. In a grail-like quest to improve productivity, we disrupt parts of the skill code, taking for granted the necessary stacks of challenge, complexity, and communication that can help us build the skill we need to function. with smart machines.

Let’s visit Kristen in the OR to see how this plays out. Six months after his open surgery, he wheeled a prostate patient into the operating room where a four-armed, thousand-pound robot was waiting. The surgeon attaches the robot to the patient. Then the two of them went through the scrubber and head to control the remote from fifteen meters to do all the work “remotely.”

Just Kirstenwatchesas he goes he changes the robot’s arms, retracts and manipulates the muscles. Like most smart technologies, the robot allows him to do the work himself, so he does it. You know Kristen needs some practice; you want to give him control. But you also know that he will drink and make a lot of mistakes. So, he never tried. There is no chance that you are a better surgeon after this procedure. I have high-quality data on this problem from all sectors of the global economy, and the same for hundreds of millions of us around the world. This is a multi-billion dollar problem.

4. Learning from the shadows

Code of Skillsit is not a “sky is falling” book. I bring good news from the front lines. I have gone to great lengths to find people who defy the odds and get great results. As we face the erosion of the bond between experts and novices, some people are finding a new way from which all of us and our organizations can learn.

Take Beth, another surgical resident who—on paper—is in the same position as Kristen. They were in the same top hospital. He came from the same medical school with the same courses. He had the same surgeon, the same patients, and the same formal training in robotic surgery. But right from the start, I could tell that Beth didn’t feel as overwhelmed, bored, or stuck in the learning curve as Kristen did. That’s because he wasn’t there; every time he went into the OR, the attendants would let him work ten to fifty times as long as Kristen. When Kristen looked like a baby calf learning to walk, Beth was beautiful.

“People like Beth are finding ways around the law to build capacity.”

Beth was a rebel, but with a reason: talent. The approved method of learning robotic surgery did not work. People like Beth are finding legalistic ways to build skills anyway. In his case, this means watching tons of surgeries on YouTube and operating on patients with limited or no supervision… still discouraged? I called this “shadow learning” for a reason.

But at a higher level, shadow learning results in employees who can be shamed or fired as a result. Ityou haveworking for the benefit of the risk. Their tactics—and the skill code that underlies them—are critical to the road ahead.

5. Reworking the skill code

We need to go further than simply dismantling to protect the Code of Skills. Smart technology can—and in many areas, must—be part of the talent solution. You might be tempted to conclude that we are living in a “John Henry” age, where it is productivity versus human skill. However, my findings show that we can overcome this problem: in many cases, we can achieve new, amazing results by augmenting the skill code with smart technology.

Technologyitselfit does not cause the problems we experience with skill.We are herethose who find a deal with our increasingly intelligent tools:give us an advanced techno product, and we’ll sacrifice the expert-novice bond.We must note that such an agreement is voluntary.

To supercharge skill development at levels never seen in the history of our species, we need a new, open, accessible, world-class infrastructure to ensure healthy challenge, complexity, and connectivity. Humans alone cannot do such a complex thing. We need the best of human and non-human intelligence to make that vision manifest.

Right now, we can have programs that train us for more productive results. For example, turning to ChatGPT for help with a promotional email. We may write the initial information, and the system will respond, “I need to ask you a few questions to make sure this is for sale. Also, do you want to get better at this by the time the email is done or get an introduction to an expert on this? That will only take a few minutes.” No one is in the loop. It’s just an AI-powered engine with two goals: get the user the desired results and nudge them toward more skill.

Thoreau wrote, “Love must be a light, as it is a flame.” I know we both love humanity, and I hope this insight will shed some light on how to save the human skill in the age of intelligent machines and light a flame for you to get out there and do something about it.

This article appeared in Next Big Idea Club magazine and is reprinted with permission.

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