AI-proof degrees, but not loss-proof: careers like psychology and education show negative financial returns
A college degree has always been sold as the safest path to a stable, well-paying career. But what happens when the numbers tell a different story?
A new report from the Postsecondary Education and Economic Research Center has cast an uncomfortable spotlight on something many people have preferred to ignore: some of the most popular graduate degrees in the United States are, in practice, leaving their holders financially worse off than if they had never gone back to school.
And the paradox gets even more curious when you find out which degrees those are.
Fields like psychology and education, often pointed to as careers that are relatively safe from the advance of artificial intelligence, show up at the top of the list for the worst financial returns after factoring in the cost of graduate school. The research found that graduate degrees in psychology carry a cost-adjusted return of -8%, meaning the estimated change in lifetime earnings, after subtracting the total cost of the program, is negative. Clinical psychology, a specialized branch, does not fare much better, with a -5% adjusted return. Social work and curriculum and instruction also land on the negative returns list.
Yes, you read that right 😬
The idea of choosing an AI-proof career seemed smart, even strategic. But the data tells a very different story, and understanding that story has never been more important than right now, especially for anyone thinking about investing time and money in a graduate program.
The economic context behind this finding
This research did not come out of thin air. Over the past few months, a flood of economic studies has been documenting how the job market is transforming in the age of artificial intelligence. Harvard economists Lawrence Katz and Claudia Goldin identified in September 2025 that the so-called college wage premium, that is, how much more a graduate earns compared to someone without a degree, still exists but has essentially stagnated since the year 2000.
Following that, the Federal Reserve Bank of San Francisco attributed this stagnation mainly to a decline in demand for workers with college degrees. Meanwhile, the World Economic Forum found in early 2026 that AI skills already command a wage premium of 23%, compared to just 8% for a bachelor’s degree on its own. And economist J. Scott Davis of the Federal Reserve Bank of Dallas caused perhaps the biggest splash in February 2026 by demonstrating that AI is simultaneously reducing entry-level hiring and pushing up salaries for experienced workers in the same technology-exposed occupations.
It is in this complex landscape that the report on the return of advanced degrees becomes even more relevant. The question has shifted from whether college is worth it to which graduate program is worth it and for what purpose.
What the report actually says
The study was conducted by researchers Joseph G. Altonji, a professor of economics at Yale, and Zhengren Zhu, a professor at Vassar College. They used administrative data from the Texas Education Research Center to develop causal estimates for 121 specific advanced degrees. What sets this methodology apart is that it goes beyond simple salary comparisons. The researchers accounted for the student’s outside options, meaning the estimated earnings that person would have achieved if they had not pursued the graduate degree.
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The results were, to put it mildly, surprising. Master’s programs in psychology and education appeared repeatedly among those generating the lowest financial returns. In many cases, the investment in the degree simply does not pay for itself within a reasonable time horizon, stretching out to decades for those who manage to recoup what they spent, and that is when they manage at all.
Other popular degrees are not exactly impressive either. Computer science, for example, yields only a 6% return after cost adjustment. Electrical engineering and mechanical engineering sit at 4%, while computer engineering barely reaches 2%.
But hold on, there is an important detail here. Altonji explains that the low marginal returns in engineering make sense when you consider that most students entering these master’s programs already held undergraduate degrees in the same field and were already earning high salaries before graduate school. According to the study, graduates in electrical and computer engineering already earn over $82,000 a year before starting their master’s. In other words, the percentage bump looks small because the baseline is already high.
However, Altonji pointed out something interesting: for those coming from humanities backgrounds, such as English or other majors associated with lower salaries, the percentage gain from pursuing a master’s in a technical field is significantly larger.
The degrees that still pay off — and pay off well
It is not all doom and gloom in the world of advanced degrees. On average, graduate degrees still boost holders’ earnings by about 17%, according to the researchers. And there are cases where the return is impressive.
The medical degree leads by a wide margin, delivering a 173% cost-adjusted return, even considering that the average cost of medical school in the United States runs around $228,959. The law degree follows with a 41% return, and the MBA offers 13%. These are solid returns, though they are nowhere near what medicine delivers.
The most ironic part of this picture is that fields like law and business, frequently cited as vulnerable to AI automation, still show financial returns far above those of careers considered AI-proof. Recent research from Anthropic, published in March 2026, showed that artificial intelligence is already theoretically capable of performing the majority of tasks in fields like engineering, law, and finance. Yet even so, those degrees keep paying well.
This reveals an uncomfortable truth: safety from automation and financial return are completely different variables.
The trap of the AI-proof narrative
Over the past few years, a pretty seductive narrative has taken hold in the career world: given the rapid advance of artificial intelligence, the safest move would be to shift toward professions involving irreplaceable human skills — empathy, active listening, emotional development, and interpersonal relationships. And what are the textbook examples of those professions? Exactly: psychology and education. The logic seemed solid. No language model is going to replace a therapist or a teacher who truly connects with their students, right?
The problem is that this narrative, while it holds some truth when it comes to technological replacement, completely overlooked the economic side of the equation. Not being replaced by AI does not automatically mean your career will pay you well. It just means you will probably keep having a job, which is a good thing of course, but not necessarily enough to justify investing tens of thousands of dollars in a graduate program.
There is another important point here that often gets lost in discussions about careers and artificial intelligence: even if psychologists and teachers are not replaced by AI, they will be profoundly impacted by it. AI-based therapeutic support tools already exist and are becoming increasingly sophisticated. Intelligent educational platforms already personalize learning in real time. This does not mean the human professional will disappear, but it does mean that those who do not know how to work alongside these tools will be at a competitive disadvantage, regardless of whether they have a master’s degree tucked away in a drawer.
The job market is already signaling change
Another piece of data that fills out the picture painted by this report comes from a trend that is picking up steam among younger workers. Gen Z, which is entering the workforce right in the middle of this transition, is already being pushed to break away from traditional career norms. While the percentage of Americans with a graduate degree grew from 31% in 1993 to 42% in 2022, according to the U.S. Census, a growing number of young people are simply skipping college altogether.
The unemployment rate among recent graduates recently surpassed the overall unemployment rate for all workers, according to data from the Federal Reserve Bank of New York. That statistic alone is alarming. It suggests that the degree, at least in the early stages of a career, is not working as the protective shield everyone always believed it was.
And this phenomenon is not limited to those who only completed their undergraduate degree. Professionals who invested in graduate programs in fields with historically lower salaries are finding that the market simply does not value that extra credential the way they expected. The blue-collar work revolution, with skilled trades and hands-on professions gaining more space and recognition, is the other side of the same coin.
Degrees, debt, and the math that does not add up
There is a structural issue that needs to be put on the table clearly: the current model of advanced education in the United States, and in much of the Western world, was built in a context where a degree automatically translated into access to higher-paying positions. That model worked reasonably well for decades but started showing cracks as university costs skyrocketed and the job market began valuing practical, demonstrable skills over formal credentials.
In the specific case of psychology and education, the problem is even more pronounced for a structural reason: a huge share of jobs in these fields is concentrated in the public sector or in nonprofit organizations, which historically pay less than the private sector and operate on rigid pay scales. A teacher with a master’s degree in the public school system may earn a bit more than a colleague without the title, but rarely enough to cover the cost and time invested in the program.
On the other hand, a professional in corporate learning or an organizational psychologist working with large companies may have a very different reality, which highlights the importance of understanding not just which degree you pursue, but which segment of the market you plan to work in with it.
As Altonji himself said when interviewed: if you are thinking about going to graduate school, you need to seek out information about the earning potential upon leaving that program, as well as the types of occupations and jobs it leads to. It sounds simple, but it is an analysis that a lot of people just skip.
The motivation is not always financial
It is fair to acknowledge that financial return is not the only reason to enroll in a graduate program. Many students pursue a master’s or doctorate to make a career transition, deepen their knowledge in a field they are passionate about, or simply meet professional requirements that demand the credential. And all of that is perfectly legitimate.
The problem arises when the decision to invest in an advanced degree is made based on incorrect assumptions about the expected return. When someone enters a master’s program in psychology believing that credential will significantly transform their salary trajectory, and the market simply does not deliver that outcome, frustration is inevitable. The report serves as a wake-up call to make that decision with real data in hand, not with inflated expectations.
The Brazilian context in the same conversation
Although the study refers to the American context, the Brazilian landscape shares important similarities. Graduate programs in Brazil cost less compared to American programs, especially at public federal universities, where many master’s and doctoral programs are tuition-free. But the time invested, the lost opportunity of being out of the workforce during that period, and the salary limitations in psychology and education careers in Brazil are equally relevant questions for anyone weighing this path here.
Public school teacher pay scales in Brazil, for example, offer modest bumps for those with master’s and doctoral degrees. The differential exists, but it often does not compensate for the years dedicated to the program, especially when you factor in the opportunity cost of not working full time during that period. The math has to be done carefully, considering each person’s specific situation.
What this means in practice for anyone making a decision
The big shift in thinking that this report triggers is simple but powerful: before entering any advanced degree program, the question that needs answering is not just whether you like the field or whether it resists AI automation. The central question is whether the financial and time investment that degree requires will translate into enough return to make sense within your specific trajectory.
This involves a few practical steps:
- Research actual salaries of professionals with that degree in the segment where you plan to work
- Calculate the total cost of the program, including time spent out of the workforce
- Understand the realistic growth opportunities within the career after completion
- Assess whether the degree is a real competitive advantage or just a bureaucratic requirement that does not significantly change your salary position
- Consider whether alternative paths, such as shorter certifications or specializations, might offer a better return on the time and money invested
The difference between pursuing a graduate degree because it opens doors that would otherwise stay closed and pursuing one because it is a formal requirement that in practice does not change your paycheck is enormous. In the first case, the investment can make a lot of sense even if the direct financial return is modest. In the second case, the calculation gets a lot more complicated. The key is to tell these two scenarios apart before signing the contract with the university, not after.
A conversation that goes beyond individual choice
The report also raises a broader discussion about how society needs to rethink the way it values and compensates essential professions like psychology and education. If these careers are recognized as fundamental to collective well-being and as resistant to replacement by artificial intelligence, but at the same time do not offer a financial return that justifies the investment in advanced training, there is a systemic problem that goes far beyond any one student’s choice.
This is a conversation that needs to happen in universities, in public policy, and in the organizations that hire these professionals. Because until this equation is solved, a lot of people will keep making career decisions with incomplete information and paying a steep price for it. 💡
The age of artificial intelligence is not just redefining which jobs exist. It is redefining the value of every educational path. And the sooner this conversation becomes part of the decision-making process for anyone entering college or thinking about going back, the better off everyone will be.
