Are you afraid of losing your job to AI? It is hotly debated whether AI is making jobs scarcer right now. But whatever may be the case today, it is not crazy to have this fear for the future. Jamie Dimon, CEO of JPMorgan Chase & Co. already has told us he expects to hire more AIs and fewer bankers.
With this risk in mind, I thought I would write a simple guide on how to protect and support your career prospects. There are no absolute guarantees, but you can improve your odds in the labor market. The same steps will also benefit society by allocating your labor more efficiently and minimizing the time you might spend on the dole.
Principle one: Look for messy jobs.
Economist Luis Garicano, writing with Jin Li and Yanhui Wu, has a forthcoming book called Messy Jobs: The Work That AI Cannot Reach. They suggest looking for jobs that are hard to describe and involve many components. Maybe today you’re trying to solve a personnel problem on the company floor, running a fundraiser the next day, and after that helping the marketing team develop a campaign. What exactly is your job, anyway?
That’s a messy job. The nature of what you do changes all the time, and it changes with circumstances. Much of the value you add comes from ideas and performance on the spot, rather than mastering a regularized task in advance. The opposite of a messy job is when you sit at a computer terminal and repeat the same action every day.
Messy jobs will be pretty well-protected from AI competition, and in fact, AI will enhance their productivity.
Principle two: Be wary of work from home.
Work from home is tempting because you economize on your commute, your own furniture might be more comfortable than the office, and you can put the dog out when needed. My own job includes plenty of work from home (fortunately, it is very messy).
A recent study looked at the job troubles experienced by young and entry-level workers. In industries in which hiring has slowed, both AI exposure and work from home were common factors. Yet when the researchers tried to disentangle those two effects, they found that work from home was the more important of the two.
So make sure you are showing up every day and noticed. That means you will be more trusted, easier to monitor, and people will develop a better sense of your talents. That, in turn, will help ensure your future.
Principle three: Be proficient with AI tools.
This obvious point bears repeating. You are your own enemy if you go around constantly complaining about AI, even though there are some genuine complaints you might levy. It is best to complain from a position of love and dedication. Learn how to use agents, how to prompt effectively, and how to integrate AI into the workflows of your organization. Keep up with what is new in the AI field. Don’t stop at Writing this memo used to take me four hours; now it takes 10 minutes. That is fine, but over the longer haul it will not suffice to keep your job, at least not at your current wage and working conditions.
Founder and venture capitalist Auren Hoffman put it succinctly: “Revenue per employee is going up 3–10x this decade. Productivity is not going to land on a senior director who refuses to learn new tools. It is landing on a 23-year-old with AI.”
Except you do not need to be a 23-year-old. If you are a 53-year-old with a very good working knowledge of your current institution, you too can lead the way. Part of the point of AI is that you can do a lot of work with it without being a technical expert.
Principle four: Work in the biomedical sector.
I am not saying each of these points works for everyone. You may not want to work in the biomedical sector. But if you’re considering that field, it should become all the more salient and desirable to you.
The AIs are going to come up with a lot more ideas for new drugs, new treatments, and new medical devices. But most of those ideas will not work, so someone is going to have to test them, verify them, explain them to patients, and yes, also to assume legal liability for them.
Not all of the follow-up work can be done by digital AI simulations. Robots are very far from taking over our labs, even though we will automate particular functions. Medicines still need to be tested on humans, and the demand for clinical trials will skyrocket. The healthcare sector will have to spend a lot more time working with regulators and trying to persuade them. Even if some of those functions can be done by AIs, I predict we will not always let AIs take the lead role.
It would not surprise me if, several decades from now, the healthcare sector were over 30 percent of the U.S. economy (currently it is slightly below 20 percent). There could be a lot of automation and still the number of jobs in the sector is likely to grow.
Principle five: Run experiments.
This is a more general version of the healthcare point. AI will generate so many new ideas and hypotheses, including for drugs and medical devices, but not only. Become a tester. Test new battery designs, new educational techniques, or new methods of conserving valued wildlife.
The demand for experiments will rise sharply, and most of those cannot be done by robots, at least not anytime soon.
Principle six: Gather data.
AI is a marvelous tool, but it relies on knowing lots about the world. That can stem from reading the internet, watching videos of people folding clothes, and hearing recordings of voices, among many other ways of absorbing information.
The more powerful the AI, the higher the returns from feeding it data, because it will make smart and useful inferences from those data. But most data in our world have never been put into AI models. Just consider corporate records, historical archives, referee reports for failed scientific papers, accounts of lab procedures, and much more. Most of that remains virgin territory.
The next few decades will bring an immense investment in feeding more data into the AIs. So there will be new jobs in gathering environmental data, job safety data, construction site data, corporate and management data, public health data, agricultural data, education data, and much more. Those jobs could be yours.
Principle seven: Get a hands-on job in the energy sector.
This one is simple. AI needs compute, and compute needs energy. By no means will all energy jobs be secure from AI encroachment, but how about grid work, field maintenance, physically building out new and better energy systems, and regulatory affairs? Expect significant job growth in all of those areas.
The bottom line is there will not be mass unemployment. Nor are your career prospects doomed.
Oh, here are two other suggestions, though they do not apply to most of you. Be the next Taylor Swift, or the next Victor Wembanyama. You can’t just walk into those jobs and apply, but the future will bring many more entertainers, athletes, and stand-up comedians. There will be more leisure time, more economic output, and thus more money to spend. Just as we prefer human chess players to their computer counterparts, so are we likely to continue to look to humans in the arts as well.
As for opinion columnists, we will have to see.