Why AI Will Make Our Children More Lonely
The good news, says Scott Galloway, is that AI’s economic impact won’t be the catastrophe that so many are predicting
5 min
Scott Galloway, a founder of companies, board member of others, business-school professor and author, is outspoken in his criticism of today’s Big Tech-driven society. At the recent Wall Street Journal CEO Summit in London, he shared some of his views, along with an array of data points, in a wide-ranging, animated talk with Nikki Waller, coverage chief for life and work at The Wall Street Journal. Edited excerpts follow.
The unreal world
WSJ: How will AI change the home and family lives of people in this room?
GALLOWAY: You’ll get richer, and your kids will get lonelier and more depressed.
Most of the technologies we’re coming up with, or a lot of them, are pouring fuel on this flame of loneliness, where we’re finding reasonable facsimiles of a relationship. Social creates this illusion that you have a lot of friends, but you don’t experience friendship.
A lot of young men are self-selecting out of the real world. They believe they’re learning or investing on a trading app, and that’s just gambling. That’s just addiction. They think that they are having a relationship when they’re on Discord, or sharing information. They feel rejected on dating apps. If you’re a young man in the 50th percentile or below in terms of attractiveness, you have to swipe right or select 200 women and say, “I’m interested,” to get one match. If you match, you need five matches for it to turn into one coffee, because four of the five women who have a much finer filter in terms of selectivity, they’ll kind of melt away.
So most men have to match 1,000 times to get one coffee. And that validates that they are not attractive and not valued in the mating market. I think they’re going to increasingly turn to AI-driven relationships.
We have a series of replacements—fuelled by technology—for relationships, mentorships, the workplace, friendships, romantic relationships. And in the short term it sort of fills a void. But it’s empty calories, and I think you end up more depressed.
We’re mammals, and we’re supposed to be around each other. I worry that there’s a whole cohort of young people, specifically young men, who will withdraw slowly but surely from the world. And the output of that is they become really sh—y citizens. They’re more prone to misogynistic content. They’re less likely to believe in climate change. They don’t develop the skills to read a room and be successful at work. They don’t engage in romantic relationships, so they don’t have kids.
WSJ: How do you solve for this in the workplace if you’re a boss?
GALLOWAY: We need systemic solutions. We’ve taken away wood shop, auto shop, metal shop from high schools, and basically told young men in high school to be more like women. “Be organised, disciplined, sit in your seat.” And the education system is highly biased against men.
I think the labor force is quite biased against women still, especially once they have children. But the educational workforce is biased against men. Boys are twice as likely to be suspended than a woman on a behaviour-adjusted basis, the exact same infraction. A Black boy, five times as likely to be suspended.
What you can do as a CEO is, first, drop the fetishisation of elite colleges. There’s going to be two female graduates from college in the next five years for every male. And create more on ramps into your company for kids who don’t have traditional college certification. In terms of the workforce, I’m sort of the person that makes HR uncomfortable, because the No. 1 source of retention at a company is if the employee has a friend.
I’m a big fan of remote work for caregivers. We should have a new classification of worker: For someone who’s taking care of young children, ageing parents, someone who’s struggling with their own health, remote work is a huge unlock. But for people under the age of 40, I think the office is a feature, not a bug. And that is it’s a fantastic place to find friends, mentors and mates. We don’t like to talk about this, but one out of three relationships begins in the workplace.
Ninety-nine percent of relationships that began at work are consensual. And we talk about and we publicise some abhorrent behaviour, and those people deserve to be in prison. But the people who I find are most righteous about being against workplace relationships are already married. And if you’re going to ask a young person to work 12 hours a day in this competitive economy, where are they supposed to find mates?
Work/life balance
WSJ: Gen Z workers, in their first interviews, are asking about work/life balance. What’s the right way to think about that?
GALLOWAY: Work/life balance is a myth. I’ve taught 5,500 students at NYU, and I do a survey. “Where do you expect to be in five years economically?” And something like 90%-plus of them expect to be in the top 1% economically by the age of 30, right? I get it, it’s great. But it means you’re going to have no life other than work, or very little life. I don’t remember my 20s and 30s other than work. It cost me my hair, it cost me my first marriage, and it was worth it.
You can have it all. You just can’t have it all at once. If you expect to be in the top 10% economically, much less the top 1%, buck up. Two-decades-plus of nothing but work. That’s my experience.
The AI future
WSJ: What career advice would you give a young adult right now regarding AI?
GALLOWAY: I’m an AI optimist. But everything in the media on AI is total catastrophising. It’s, “This is the nuclear bomb.”
I’m like, “That’s not that helpful.” Anytime there’s a new technology it goes through the same arc. There’s some catastrophising, there’s some job destruction, and then the economy grows and there’s more jobs.
Automation destroyed a lot of jobs on the shop floor, the manufacturing floor. But we didn’t anticipate heated seats or car stereos, and we created more jobs. I think AI is going to be enormously accretive for society and our economy.
If I were a young person, think about which industry does it disrupt, which industry will have the greatest reshuffling of value? Think about targeting disruption.
I’m not sure people thought processing power would disrupt cable television. But it did, in the form of Netflix.
Netflix’s rise is directly correlated to increase in bandwidth and processing power, because your cable bill kept going up faster than inflation such that you could have Food Networks 3 and 4. So for $12 a month I can get a reasonable facsimile of what was costing me $120 a month.
So what’s next? What does AI kill or disrupt? And where would I invest my human capital as a young person?
The most disruptable industry in the world—as a function of prices increasing faster than inflation relative to the underlying innovation or lack thereof—is, hands down, U.S. healthcare.
I haven’t had health insurance in five years. And when I tell people I don’t have health insurance, it’s like, “You’re a bad citizen. You’re not a good dad.” No, health insurance is nothing but a transfer of wealth from the poor who can’t absorb a big shock to the rich who can.
That is ripe for AI to come in and look at you and say, “You know what? You’re better off taking 4% of your salary, putting into the 401(k), using it if you have a healthcare crisis, but not buying insurance.”
There’s going to be so many little AI-driven healthcare companies that go after the American healthcare complex.
AI for me, if I were 22, 25, 30, and wanted to invest my human capital, I would think, “Where is the real action going to be? A reshuffling of shareholder value?” It’s going to be AI-driven startups in the healthcare space.
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Could fears of an AI apocalypse be distracting us from the dangers already here? Experts debate whether regulation should focus on speculative existential threats or present-day harms, including cyberattacks, weapons and unsafe autonomous agents. Read more via the link in bio.
5 min
There is ample and alarming evidence that artificial intelligence can help humans do bad things, such as committing cyberattacks, building weapons and even killing themselves or others. The Hugging Face hacking episode—and a growing list of others by poorly constrained swarms of agents—indicate just how powerful and potentially dangerous AI has quickly become.
Yet many inside the U.S. AI industry insist far worse is coming, on account of the imminent arrival of AI with superhuman and self-improving abilities.
Plenty of experts, including many who study AI harms for a living, are skeptical. The so-called doomers’ assertion that AI might decide to wipe out all of humanity—or even “just” topple human civilization—is contingent on it achieving a pace of development not yet seen.
And if the assumptions behind this global-doomsday scenario are wrong, it could lead us to curb or regulate AI in ways that don’t address its real harms.
At the center of this debate is the claim that current AI systems might take over the job of training their next versions, a process called “recursive self-improvement.” Think of it like evolution on steroids—billions of years happening at light speed within vast AI supercomputers. Anthropic Chief Executive Dario Amodei recently proposed a global agreement to slow down the pace of releasing new AI models, with the goal of delaying the arrival of recursive self-improvement.
“I don’t think we’re anywhere near ‘artificial general intelligence,’” says Melanie Mitchell, a professor at the nonprofit research group Santa Fe Institute who studies AI. She said AI is making impressive strides but thinks claims by engineers that they’ve achieved recursive self-improvement don’t stand up to scrutiny.
She is hardly alone. A recent paper by two dozen academics at Princeton, Stanford and other institutions found that even the most cutting-edge AIs are incapable of doing the original research required to advance the AI frontier.
Two of the authors involved in that paper also threw cold water on the idea that the Hugging Face swarm hack by OpenAI agents occurred because of a breakthrough in intelligence. The attack succeeded primarily because of a lack of basic technical guardrails, not an unmanageable explosion in AI capability, they wrote.
Yann LeCun, former chief AI scientist at Meta, posted that this analysis was “a welcome dose of sanity in an otherwise insane debate.”
OpenAI and Anthropic didn’t respond to several requests for comment.
The people who disagree with the doomers still consider AI to be dangerous, and point out that such systems don’t have to be particularly capable to be powerful. Some argue that AI should undergo regular evaluation by outsiders and that the companies that make it should be held responsible when their systems do harm. AI should also be treated the same as airplanes and elevators, and should be designed to do the least harm possible, they say.
“If you believe that technology is powerful enough to create novel, dangerous viruses, or to essentially take over the whole planet for some reason, then it must also be strong enough to create cures for cancer, to cure aging, to fix socio-economic or political problems,” says Christopher Canal, CEO of EquiStamp, a company that helps companies and governments evaluate AIs.
AI has shown an ability to rapidly advance because it is matching the abilities of humans who are constantly feeding it their knowledge. Sometimes it can recombine that knowledge and exceed what people have been capable of, through a kind of post-training known as reinforcement learning, as we’ve seen in mathematics.
Today’s LLMs are “models of knowledge” rather than actually intelligent, wrote Yi Ma, professor of AI at Hong Kong University.
Researchers at universities and commercial AI research labs in China wrote in a recent paper that autonomous, self-improving AI is likely to be a long way off, due to the sheer number of breakthroughs required. They also argue that humans will probably remain in the loop, supervising that process—and gating how fast it can occur.
Vals AI, a company that evaluates today’s AI models, maintains an RSI Index that benchmarks whether models can “do the research that builds the next model.” So far, no publicly released model is even close.
Yet Rayan Krishnan, CEO of Vals AI, says his team projects models will exceed humans’ ability to improve the next generation of AIs by August 2027, or sooner, and at that point could start building their successors all on their own.
“Once we get to recursive self-improvement, the fear is that all bets are off,” he says. “You could end up with a ‘fast takeoff’ situation, where the models quickly acquire skills and eclipse humans across every possible domain.”
In a reply to the resignation tweet heard round the world from Jacob Coxon, another Anthropic engineer declared his belief that those odds were at least 10% over the next decade. Many others in the industry chimed in to say they thought the percentage was even higher.
Some who argue the end is nigh say they calculate their personal p(doom) based on a chain of conditional probabilities—a bit like the Drake equation for calculating the likelihood of intelligent alien life. Since all those probabilities are based on speculation, estimates range from 0% to nearly 100%. Many land around 10%.
“The weird thing is that if you go back and look at the predictions on this over the last 10 years or more, it’s always been 10%—it’s just a nice round number,” says Mitchell. “I think it’s all vibes, and there’s no actual evidence or calculation.”
One argument against worrying about superintelligent AI is that the world is full of unlikely humanity-ending disasters, and trying to avert them all can make it impossible to prioritize, says Canal.
This has led AI experts and the policymakers who listen to them to propose remedies that don’t get at its real and present dangers.
AI companies’ proposals to “pace the frontier” aren’t addressing the problem in the right way, argues Stuart Russell, a computer-science professor at the University of California, Berkeley, and the president of the International Association for Safe and Ethical Artificial Intelligence.
“It’s like saying we’re driving toward the cliff at 60 miles per hour and we’re going to drive toward it at 40 miles per hour instead, and everything will be OK,” he says.
Russell and his peers have proposed that AI companies should have to meet the same standards that govern other areas of everyday life, from air travel and buildings to food and drugs. They highlight the “behavioral red lines” AI should not be allowed to cross. Breaking into other computer systems, stealing information or advising terrorists on how to build biological weapons are all illegal for a human to do, and should be illegal for companies’ AIs as well, he argues.
The challenge for AI companies in such a proposal, he adds, is that it would be a de facto ban on today’s advanced AI systems, since the companies behind them don’t know how to make them respect such boundaries all of the time.
Others have proposed something like the Food and Drug Administration, but for AI, but setting up a new agency has so far been a nonstarter in Congress. And some prominent voices in tech have said such a structure would give up America’s AI edge to China.
Given the bipartisan groundswell of support for curbing AI companies and their creations, however, that may soon change.
“The tech industry has had this mantra for decades that regulation is bad,” says Russell. “They don’t accept the liability for any harm, and they hide behind free speech. That, I think, has to change.”
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