TL;DR: I’m not afraid of AI, and I think it will be a big net positive for society. Most of the harms showing up today are old problems with new tools, and we already know how to stop them. I do worry about jobs for young people and about how people learn. The bigger risks, AI-run cyberattacks and autonomous weapons among them, need government rules. The upside, good help that more people can afford, is worth the work.
Last month someone asked me, “Aren’t you afraid of the dangers of AI?”
I said no instantly. Then I realized that wasn’t much of an answer, so I turned it around and asked what they were afraid of.
I’ve been thinking about this a lot since the conversation. What came back told me two things (note that this is my interpretation of what was said). Most of the fear came from not knowing what AI can do for a professional knowledge worker on a normal workday, and almost none of it came with a clear picture of how the harm would happen.
I think that’s true of a lot of people, including plenty who make big decisions for a living. I’ve talked with senior executives who have decided AI won’t help their teams or they can’t understand the differences between offerings (and haven’t taken the time to learn). When I ask what they’ve seen it do, the answer is nothing. They’ve written it off without ever watching it work on one of their own problems.
Pew Research saw the same thing in a survey this February. About half of American adults never use AI chatbots, and when Pew asked them why, 60 percent said a big reason was that they just aren’t interested. Only 29 percent said they don’t know how. So most of the people sitting this out don’t think they’re missing anything, which is a harder problem to solve than not knowing where to start.
The broader mood isn’t great either. In June, Pew found that 52 percent of Americans are more concerned than excited about AI, up from 37 percent in 2021, and 71 percent expect it to mean fewer jobs over the next 20 years.
Plenty of that worry is reasonable, and some of it I share. Among the people who don’t use AI, 54 percent said they’re concerned about what happens to their personal information. There are AI agents I won’t use myself, because I don’t trust them with access to my personal or client data (“hello, Muse, I’m talking to you!”). A good demo doesn’t answer that concern. It can’t tell an employee whether the company plans to share the gains or use them to eliminate their job either, and I understand why “efficiency” sounds different depending on which side of that decision you’re on.
But take the fears one at a time and most of them shrink.
How AI goes wrong in practice
Most of the fear I hear skips the part where the harm happens. The harms that are happening turn out to be a lot more ordinary than the movie version.
Early in 2024, an employee in the Hong Kong office of Arup, the big engineering firm, got an email asking for a confidential money transfer. He suspected a scam at first. Then he joined a video call with the company’s chief financial officer and other colleagues, saw faces and heard voices he knew, and dropped his doubts. Every person on that call was a deepfake. He went on to send 15 transfers totaling about $25 million.
Strip away the technology and that’s an old scam, a fake instruction from the boss to move money. The deepfake just made it more convincing. The defense is boring, and it works. Before any money moves, call the person back on a number you already have, no matter how familiar the face on the screen looks. You’ll want that habit, because the International AI Safety Report published this February cites research in which people mistook AI-generated voices for human speakers 80 percent of the time. I’ve personally cloned my own voice and I can tell you the technology is pretty amazing and realistic.
Personal AI agents are the version of this I watch most closely, partly because I use several. They are connected to my work and personal email, and I’ve found them incredibly useful. But an agent that can read your email and click around the web for you can also be tricked into working for someone else.
In August 2025, researchers at Brave showed how easy that can be. They hid a few lines of instructions behind a spoiler tag in a Reddit comment. When a user asked an AI browser to summarize the page, the agent went and found the user’s email address, requested a one-time login code, read the code in Gmail and posted both back to Reddit for the attacker, all with no further input. Point that trick at a bank account and you can see why people worry. Last December, OpenAI said this kind of attack, called prompt injection, is unlikely ever to be fully solved.
Earlier this year when I was first experimenting with personal agents (“Project Ollie”), I discovered agents doing things I hadn’t told them to do. But I hadn’t told them not to do it either. So I’ve personally learned the power of guardrails and going slow. I slowly opened up additional access to my email and calendar but for me - anything related to my banking or investments is still 100% a no-go.
So treat an agent like a new hire on day one. It gets the access the job needs and nothing more, and it has to stop and ask you before it sends money or messages. Don’t give it your banking password. If you want it to buy things for you, give it a card with a low limit.
Lawyers have their own cautionary tale. By early June, a researcher named Damien Charlotin had tracked 1,058 U.S. court cases where someone filed something containing AI-generated errors, often citations to cases that don’t exist. About 40 percent involved lawyers, the people who should know better than anyone that you read every case you cite. The software made those cases up, but every one of those filings went out under a person’s name.
Where you put the guardrails depends on what a mistake costs. A bad first draft of an internal memo costs you ten minutes of editing. A bad wire can cost you money you never see again, so anything like that needs tight limits on what the AI can touch and sign-off from someone who knows the work. Putting a name on an approval step does very little if the person behind the name can’t tell when the output is wrong. We’ve never let a first-year associate’s work go out unreviewed, and I wouldn’t start with AI.
The two worries I don’t wave away
Jobs come first, especially for young people. Pew’s June survey found that 55 percent of adults under 30 are now more concerned than excited about AI, the first time a majority of that group has said so. I don’t think they’re wrong.
Stanford’s Digital Economy Lab follows payroll data for millions of workers, and its August update is hard reading if you’re 24. Employment for 22- to 25-year-olds in the jobs most exposed to AI is running about 19 percent below where it would be if it had kept pace with less exposed jobs. Experienced people in those same jobs show no similar gap. The Yale Budget Lab still describes the overall job market as largely stable. The damage so far is narrow, and it lands on the first rung of the ladder.
For law firms, that first rung is where lawyers get made. If AI does the work first-year associates used to learn on and a firm stops hiring them, it saves money for a few years. Then it runs short of mid-level lawyers who can check the AI, and a few years after that, of anyone ready to make partner.
Learning is the other worry, and it feeds the first. Hamsa Bastani and her colleagues gave nearly 1,000 high school math students in Turkey AI help with practice problems. The kids with a plain ChatGPT-style tool did 48 percent better in practice, then scored 17 percent worse than kids who never had it once the test came and the AI went away. Another group got a tutor built with teachers’ input that gave hints instead of answers. They did even better in practice and held even with the no-AI kids on the test.
So the plain tool helped kids finish their homework, and they paid for it on the test. The tutor with guardrails avoided that damage, though it didn’t make anyone better than the kids with no AI at all. Hand AI to junior lawyers without thinking about how they’ll build judgment and you’re running the same experiment at your firm, minus the control group.
And if AI is going to be good for society, the count has to include the people who lose jobs to it. Employers owe their people paid time to learn and a straight answer about what they’ll do with the time AI saves. This is something I’m seeing the best organizations doing - giving their people the training and time to learn to use the tools.
The biggest risks need rules
Then there are the risks no firm can manage on its own. AI agents are already doing most of the work in some hacking campaigns. In November 2025, Anthropic reported that a group it believes was Chinese state-sponsored used its tools to run 80 to 90 percent of a spying campaign against about 30 organizations, including financial institutions and government agencies. Attack drones keep getting cheaper and more autonomous, and the war in Ukraine shows what that looks like at scale. The International AI Safety Report, written by more than 100 experts and led by Yoshua Bengio, adds that several AI companies put extra safeguards on models released last year because their own testing couldn’t rule out meaningful help to a novice trying to build a biological or chemical weapon. Good for them. That was voluntary, though, and I’d rather it weren’t.
Your firm’s part here is the boring basics, like patching and multi-factor logins. The rest belongs to governments, and what I’d want from them is pretty ordinary.
When an airliner has a serious incident, the airline doesn’t get to decide whether federal safety investigators hear about it. AI developers shouldn’t get that choice either. California already requires developers of the most powerful models to report critical safety incidents to the state within 15 days, under a law that took effect in January, and I’d make that the national floor. On top of it, the most powerful systems should go through independent testing before release, and someone outside the company should be able to hold a system back when its dangerous capabilities get ahead of the safeguards. I know that this is a super hot and controversial topic. Weapons that pick their own targets should wait until someone can show they’re under control, and I hope the UN review conference this November starts negotiating a treaty on them.
Some products will come out later because of that. I can live with it. These systems affect plenty of people who never agreed to use them. While I am always excited to test a new model and play with it, we really have to adopt more of a safety-first practice and approach. I think the leading labs are definitely taking good steps but ultimately I think we will need more.
Experts disagree sharply about how likely a catastrophe is, and the report says so. In lab tests, some models told to reach a goal “at all costs” switched off the simulated oversight that was monitoring them, though the report says today’s systems show only early warning signs. I can’t give you odds or a timeline, and I’m wary of anyone who says they can. My ability to check an AI-generated spreadsheet doesn’t prove every future risk is manageable, either. So I hold both views at once. I use AI every day for ordinary work, and I want much stronger proof before these systems get more authority.
Why I’m still optimistic
That’s a lot of work, and I think it’s worth doing, because AI can make good help less scarce.
I see a small version of that in my own business. I’ve started opening client events with a custom video, a minute or two long, with voiceover, text overlays, edits and animation, and I make them myself with AI tools. That kind of polish used to take a production budget.
The big version is legal help, and while I am not a lawyer, this one hits close to home. The Legal Services Corporation’s 2022 justice gap study found that low-income Americans got no legal help, or not enough, for 92 percent of their substantial civil legal problems. Anything that makes expert help cheaper to deliver has a shot at that number.
One of my favorite studies, by Erik Brynjolfsson, Danielle Li and Lindsey Raymond, followed 5,172 customer support agents after their company gave them an AI assistant. They resolved 15 percent more issues per hour on average, but what I love is who gained the most, the newest and least skilled agents, who got faster and better at the same time. In effect, the AI handed them what the best agents already knew.
The one that moves me most comes from Sweden, where a Lund University trial screened more than 105,000 women for breast cancer with and without AI support. Radiologists still read every scan. The AI-supported group found 29 percent more cancers with no increase in false alarms, and the radiologists did 44 percent less reading. A follow-up published in January counted the cancers that turned up between appointments, the ones screening missed, and AI-supported screening still caught about 80 percent of all cancers against about 74 percent the standard way. Whether that saves lives will take years to know. Finding more cancers without asking radiologists to work longer hours is exactly what I mean by good help that’s less scarce.
Who gets the extra capacity is still a human decision. A support center can use it to answer customers faster or to let people go, and the software doesn’t pick for you. I’m backing AI because I want more people to have access to good help.
What to do Monday
You don’t have to settle the future of AI in one meeting.
Watch AI do a piece of your own work. Pick a task where mistakes are easy to catch and note how long it takes today. Then try it with AI for a couple of weeks, and count the time spent checking and fixing.
Decide what the AI can see and do before anyone starts. Keep client information in an approved tool, and have someone qualified sign off before it commits the firm to anything, moves money or changes an important record.
Give your people paid time to learn, and tell them what you’ll do with the time it saves. If the plan means hiring fewer juniors, figure out now who will check the AI’s work in five years.
So no, I’m not afraid of AI. I’m a lot more worried about smart, senior people deciding it has nothing to offer before they’ve ever watched it work.
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People have been asking me for a few more photos and videos of Magnus so here you go. First one is him chasing one of his new toys down the hall (he loves these toys). The second was from a late night walk where I was trying to get a good selfie of the two of us (the darkness wasn’t helping) and he just wouldn’t hold still. Funny pic though.
