There Are Three Types of AI Users

Remember when AI was going to take away our jobs and leave humans with nothing to do? So far, that doesn’t seem to be happening. Researchers from ActivTrak analyzed the digital activity of more than 10,000 workers and found that when people adopted AI, their work life became more intense, not less. The time that these early adopters spent on email, messaging, and chat apps more than doubled. Their use of business software rose by 94 percent.

Researchers from UC Berkeley’s Haas School of Business found that when using AI, workers started taking on tasks that they had previously outsourced, because activities such as coding and engineering became easier to do. They squeezed in work bursts in the evening, on weekends, in waiting rooms, and whenever else they had a spare moment and AI was handy. They also did a lot more multitasking, supervising a bunch of bots doing different things simultaneously.

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The general pattern that the research points to is that many people don’t use the time they save using AI to do less; they use the time to take on new tasks. AI also seems to shift workers’ expectations, and their boss’s expectations, about how much they should accomplish in a day. Every hour feels more crowded, but also more frazzled. The ActivTrak researchers found that the time people spent on focused, uninterrupted work fell by 9 percent. There’s even a name for this mental state: “AI brain fry.”

In some sense this is normal. Every time some new labor-saving technology is introduced, there are experts (the ones who know a lot about technology but not much about psychology) who predict that people will use the technology to make life easier. Soon we’ll all be enjoying 15-hour workweeks! Instead, many people use the technology to make their life more frenetic and full. Planes, trains, and automobiles are technologies that save time and effort by making travel faster. They also enable people to take a lot more trips.

[Rogé Karma: Three ways to think about AI and jobs]

I’d say that a guiding principle of the emerging AI age is this: When intelligence is plentiful, volition is valuable. The people who are going to make a difference are not the ones who seek relaxation and passively use AI to work less. They are the ones who will seek improvement and actively wrestle with AI to develop their own mental capabilities and accomplish more.

In other words, what will differentiate people is not how smart they are but their relationship to mental effort. Right now, some people have what psychologists call a high need for cognition. They enjoy thinking hard. These are the people who enjoy playing difficult games and reading dense books. On the other end of the spectrum, there are the cognitive misers, the people who find it unpleasant to think hard and take any opportunity not to do it. In the middle are the people who have a medium need for cognition. They will put in the effort when they really care about something, but they don’t intrinsically enjoy it. Need for cognition correlates with intelligence but is not the same thing. We all know a lot of really smart people who don’t like to work hard.

As things stand today, people will have very different experiences with AI.

The Productive Passengers. People with a low need for cognition will tend to use AI to think less. Their great gain is that AI will make them more productive because it makes tasks so easy. Their great loss will be that AI will diminish their mental capacities because it makes tasks so easy.

God seems to have been a puritan. He created us to be the kind of creatures who don’t experience gain without some pain, don’t gain reward without some effort. That’s as true in the world of knowledge work as it is in the world of bodybuilding. Humans learn best when they are in the zone of optimal difficulty, when engaged in tasks that are not so hard as to be overwhelming but not so easy as to require no work.

AI is going to push low-effort people out of the zone of optimal difficulty. One research team led by Nataliya Kosmyna from the MIT Media Lab found that people’s brain connectivity declines by as much as 55 percent when they are using ChatGPT compared with when they are not using it to perform similar tasks. Vivienne Ming, a co-founder of Possibility Sciences, found that when people were using AI, their gamma-wave activity—a sign of cognitive effort—dropped by roughly 40 percent.

This has predictable effects on how much people remember from their AI-assisted work. It has equally predictable effects on their thinking skills. A study by Michael Gerlich from SBS Swiss Business School found “a significant negative correlation between frequent AI tool usage and critical thinking abilities.” At first, AI sucks you in. You really do become more productive when using it. But then it threatens to hollow you out, as you become less capable and less knowledgeable. The saddest cases are people who get used to the AI crutch for a bit and then have it taken away. Researchers led by Grace Liu of Carnegie Mellon University put subjects through that experience and concluded, “After just ~10 minutes of AI-assisted problem solving, people who lost access to the AI performed worse and gave up more frequently than those who never used it.”

A study of physicians who specialize in endoscopy—using flexible probes to examine the inside of the body—found that before they started using AI they located precancerous intestinal lesions in 28.4 percent of colonoscopies. After they started using AI, and then had it taken away, they located lesions in only 22.4 percent of colonoscopies. Their detection skills had seriously declined.

Recently, I found myself driving across an infinity of freeways near Anaheim, California, with GPS leading me through a series of highway exits and entrances. I had the thought we’ve all had: I used to do this using maps! I’m as capable of doing that now as I am of walking across the Pacific Ocean. GPS merely shrivels some navigation skills; AI threatens to shrivel everything within those who let it.

The Reluctant Optimizers. People with a medium need for cognition will understand that AI might hollow them out. That prospect will really bother them. They will resolve, earnestly and with good intentions, to not let themselves fall victim. But in the crowded and stressful rush of everyday life, they will get sucked in. Their resolve will fail and they’ll become overreliant on the bots.

AI is a seductive technology. The MIT Media Lab researchers found that when they asked people to use ChatGPT to write a succession of papers, they relied more and more on AI with each one. Before long, they were mostly cutting and pasting. That’s not just because users got more fatigued as they worked. The technology subtly moved them from one mindset to another. Old-fashioned education institutions are built around a cultivation mentality: You work hard and suffer through some hard tasks, and you become a better thinker and a more knowledgeable person. Modern technology, by contrast, is built around an optimization mentality: You find a machine that makes everything easier, so that you accomplish things as efficiently as possible.

The whole tech industry is organized around optimization. In a 2013 interview with The Guardian, for example, Amit Singhal, Google’s head of search, declared, “We are maniacally focusing on the user to reduce every possible friction point between them, their thoughts, and the information they want to find.” People with a cultivation mindset seek friction; people with an optimization mindset want their life to be frictionless. Modern technology wants to turn you from a mental muscle builder into a mental couch potato.

If you’re going for optimization, you’re looking to maximize output, not excellence. In a survey conducted for the software firm GoTo, 43 percent of workers said they had submitted AI-generated content even though they suspected that it contained errors and was generally of low quality.

Pretty soon, people in this optimizer group are going to suffer from the same sort of hollowing-out process as the low-cognition folks. Curiosity will gradually decline. The MIT developmental psychologist Laura Schulz has found that if a teacher offers instruction on how to use an object, she is unintentionally limiting children’s curiosity about it. But if she deliberately restrains from offering instructions, they become more curious. AI is like the instruction-offering teacher.

General engagement with life will gradually decline. A research team led by Suqing Liu of Shanghai Tech University found that when they let people use AI and then asked them to do another task unaided by AI, the participants’ intrinsic motivation levels dropped by an average of 11 percent, and their sense of boredom increased by 20 percent. Engaging with AI made the first task seem more enjoyable, rendering ordinary work dull by comparison.

People in this group will also become less and less able to stand up to the bot. The technology is asking you to be a competent conversation partner with a highly intelligent but imperfect entity. But what if you’ve never done the work to form your own worldview or build your own knowledge base? You’re going to engage in what the experts call “cognitive surrender.” You’re going to believe everything the bot tells you, head off in whatever direction the bot suggests. Researchers at the University of Pennsylvania’s Wharton School programmed an AI to occasionally give wrong answers. The humans accepted its errors as true 80 percent of the time.

The core problem with optimization is that it will change people’s attitude toward effort itself. Chris Sibben is the head of school at Rivendell, a small private school in Northern Virginia. One day, he showed his students a film that took more than 200 artists more than five years to make. The students were baffled. Why do that? As one student put it, “AI could have done it in five minutes.”

Sibben discerned a stark cultural shift in that observation, which, in an essay for Mere Orthodoxy, he calls “the industrialization of detachment.” He argues that a student who has “wrestled with a hard text, revised an argument under pressure, and failed and tried again is more than informed. He is more solid.” As our friend Kierkegaard would have said, it is only by making passionate commitments that a person builds herself into a self.

What happens if she has never put in that work and has never become a self? Sibben argues that the comment “AI could have done it in five minutes” is not really about speed. “It is a moral revaluation. It assumes that what matters is the output, not the ordeal; the image, not the seeing; the product, not the person becoming capable of making it.” AI “offers competence without apprenticeship. Fluency without understanding,” he concludes. “A student who internalizes that pattern does not become lazier; he becomes less formed, less present, less able to bear the weight of difficulty without reaching for a prompt.”

The Mental Marathoners. Now we get to the high-need-for-cognition people and how they will fare in the coming age: kind of like marathoners, I suspect. The automobile is a perfectly good technology for traveling 26.2 miles. There is no practical reason that any person should train themselves to run that distance. But some people do. They want to put in the effort because they want to accomplish things—they want to expand their capacities.

High-need-for-cognition people are like this when it comes to thinking. You’re probably among them if you enjoy the following kind of situation: You’ve been working on a project for a while. You have no idea how you’re going to complete it. The deadline is looming and the anxiety is high. Yet you have utter confidence that you are going to figure this out. Intellectually, you know you have failed in the past and you may in fact fail this time. But simultaneously, you know deep in your bones that you will figure it out. You search and brainstorm and then, as if by magic, one day the answer pops into your mind, and at this point, the learning curve turns exponential. Some people hate the stress stirred up by that situation, but it’s what mental marathoners live for.

A team of scholars led by John Cacioppo of the University of Chicago reviewed more than 100 studies on people with a high need for cognition. They tend to have a lot of task-related thoughts. They engage in stimulating conversations. They tend to have a high need for closure and control. Once they arrive at a conclusion, it can be very hard to push them off of it, even as counterevidence builds.

In the age of AI, I suspect that the mental marathoners are going to work really hard to resist AI entropy. They are going to feel a strong desire to be original. In this age, cultural output will feel ever more familiar, as writing, songs, and movies become syntheses of what has already been produced. Marathoners are going to want to produce work, by contrast, that feels personal, that reflects their unique self. They’re going to want to find ways to use AI to increase their agency, rather than diminish it. Already, techniques have been discovered to help people do that:

• Ask for hints, not answers: People who ask AI to directly answer their questions suffer severe declines in motivation and ability. But people who ask AI for background thinking or clarifications do not.
• Start with a blank page: Before you go to the bot, start with a blank piece of paper and write up your own analysis and conclusions. Then ask AI to challenge your thinking, not produce it.
• Rotate tasks: Every time you do a task with AI, follow it with a task that doesn’t involve AI. That will keep your creative-effort muscles alive.
• Redesign the bots: General chatbot use undermines learning. But as the writer Alberto Romero notes, AI tutors actually improve learning and motivation. That’s because although chatbots mostly answer questions, tutors lead students on structured learning journeys. It should be possible to redesign the normal bots so that they function less like encyclopedias and more like personal trainers whose jobs are designed to build mental muscles, rather than replace them.
• Make a sharp distinction between rote work and creative work: Let AI write functional emails. Don’t let it write your essays or your memos. Shame people who do.
• Ask for thinkers, not thinking: My favorite trick when using Claude is to never ask it to think through a problem for me. I ask it to summarize the thinkers who have already addressed a given problem. If I’m trying to understand child development, I ask it to imagine a debate between Jean Piaget and Erik Erikson. What would these two great psychologists say to each other about the problem I’m wrestling with? Then I ask it what books by these thinkers I should read if I want to understand their work. I get much better results from AI when I treat it as a brilliant librarian rather than as an oracle.

You may have noticed that the future I’m describing here is one of extreme cognitive polarization. Some people will use AI to think more. Other people, maybe most people, will use AI to think less. If you thought that economic inequality or political polarization were bad, cognitive polarization will be truly terrible, dividing society into what might begin to look like two different species. The high-need-for-cognition people will get more and more productive, happier and happier; the rest will fall into a kind of mental underclass.

This future is not inevitable. So far, I’ve been treating the need for cognition as some sort of ingrained trait. But although willpower has some hereditary basis, it is also extremely sensitive to context. If AI has a tendency to undermine volition, humans can reform institutions to help build it up.

Right now, our education system is built around content and intelligence. In elementary school, it downloads content onto student brains. Then it uses high school to pick out smart people and segregate them off into elite colleges. In the age of AI, schools will have to shift their orientation to focus on volition. When we are surrounded by machines that know a lot about a lot of subjects, what really distinguishes people is their desire to work hard and put knowledge to creative effect. What really matters, therefore, is not brainpower but the willingness to run the mental marathons that produce high-quality results.

The crucial task before us is to cultivate people’s desire to seek out cognitive complexity. Not to go all Joseph Campbell on you, but the essential challenge is: How do we train people to see their life as a hero’s journey in which they take on difficult missions that they may fail at and that will certainly involve pain and suffering? How do we form people so they have an explorer’s heart, a willingness to endure, an ability to struggle on, even when their body and mind are telling them to give up, to reach new destinations and figure stuff out?

It seems to me that in the age of AI, every school and organization is going to have to find its own answers to these questions. They are going to spend a lot more time asking their charges: “What is it that you truly want most in the depth of your heart? What out there in the world is truly worth wanting? How do we cultivate your highest desires?” In our current culture, everybody tells you to find your passion, but nobody tells you how. Schools and organizations are going to have to teach that.

That’s complicated, because we don’t have direct control over our desires. You can’t will yourself to be more curious any more than you can will yourself to like the taste of goose liver. But the good news is: We can indirectly influence our desires by putting ourselves in situations that either arouse or depress them.

Many of our schools do a decent job of crushing students’ desire for mental effort. Every minute that a kid sits bored in a classroom crushes their desire. Extrinsic rewards, such as grades, do so because extrinsic desires tend to crowd out intrinsic ones. Grade inflation crushes desire by making everything too easy. Many of our systems have been created by rationalists to focus on the declarative level of the mind, the part that learns facts and considers arguments; they are often oblivious to the damage they are doing in the dark forests, the deeper levels of the mind where motivations emerge.

Fortunately, schools and organizations can also inflame desire. The most straightforward theory of motivation is known as self-determination theory, founded by Edward Deci and Richard Ryan. People feel motivated when they are put in situations that give them autonomy (I’m in control of my choices), competence (I’m developing my skills), and relatedness (people here care about me). In my experience, motivation increases with admiration, such as when students are confronted with great people or great works of art. Motivation also increases with apprenticeships, such as when a mentor not only teaches a person how to engineer, but also how to be the kind of person who loves engineering.

[Read: America is headed toward the infinite workweek]

My core belief about this whole age is that artificial intelligence will reveal what it means to be human by disclosing what AI can’t do. Before AI, many people believed that reason and intelligence were the qualities that define humanity. They are what make us different from the animals. But soon there will be entities that are much smarter than us; so that can’t be what defines humanity.

What AI can’t do is hunger for things. Yes, a few reward-like mechanisms are in the thin layer of the models built through reinforcement learning, but the models are overwhelmingly about predicting, not desiring. AI can’t hunger, in the first place, because it doesn’t have biological needs—the needs that push living things to grow and explore. More important, AI doesn’t have a self. A bot doesn’t have a past person that it used to be or a future person that it wishes to become. A bot does not have a structure of cares and an order of loves, as a person does. A bot doesn’t have a personal history, a particular set of wounds, joys, and exhilarations experienced in regions deeper than rational calculation, and it doesn’t have a succession of dreams and hopes, which emerge from those regions as well.

Despite what the rationalists used to tell us, life is not mostly about solving problems. Any computer can do that. Life is a pilgrimage, a journey—it’s going somewhere, growing from experience, expanding yourself, reaching for some possibility that you do not yet possess. The defining human features therefore are propulsions—the drives that push us to take on mental effort and overcome difficulty—and aspirations: knowing where you want to go, what purpose you serve, what kind of person you’d like to be.

If we can help people learn to want more, hunger more, they’ll be willing to undertake the mental effort to do hard things, and we’ll avoid the cognitive polarization that is staring us in the face. If we can educate people to be clear and wholehearted about what they truly love, then AI will do the calculating and the synthesizing, but humans will still define what matters, what is worth exploring, what missions we go on, and where we end up. That would produce a bot-filled society in which human dignity is preserved, and perhaps even enhanced.

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