AI in the Philosophy Job Market (guest post)
A few weeks ago, I was contacted by a reporter working on a story about the extent to which AI, as a topic of research and an area of specialization demanded by employers, was becoming dominant in philosophy.
Here’s one thing I said to her:
People should be cautious when inferring how much philosophy of AI work is actually happening from how much philosophy of AI work they’re hearing about. AI is relatively new and highly socially significant, and so work on philosophy of AI is bound to get attention, and its novelty means it is likely to be more memorable when thinking about the state of philosophy more generally. Since AI and philosophy is establishing itself as a subdisciplinary field, there is a fair amount of hiring in it, forming research groups of scholars studying it, creating specialist journals for writing about it, establishing prizes to recognize good work in it, and so on. People will hear about these developments, as they’re newsworthy in the profession, but a lot of this activity is just “catch-up,” as AI and philosophy comes to be on a par with other areas of applied philosophy, such as bioethics.
Those were my general impressions.
But what would be more useful were hard numbers related to how AI is shaping the academic job market.
For that, I turned to Charles Lassiter, professor of philosophy at Gonzaga University. Over the years, Professor Lassiter has generously produced many data-based analyses of the philosophy job market published here at Daily Nous, and so I asked if he could look at the growth of AI in philosophy. Once again, he has come through. His analysis is below. Thanks, Charlie!
(A version of this post is also at Professor Lassiter’s site.)
AI in the Philosophy Job Market
by Charles Lassiter
Reactions to AI in academia, the humanities, and philosophy, have been mixed. Anecdotally, some of my friends and colleagues think this is the beginning of the end. It’s not that AI is going to take our jobs as philosophers or humanists; rather, inquiry into the history and values of humanity will slowly be edged out because AI can get us those answers faster and more reliably. But some other of my friends and colleagues argue this is a new day for the humanities. Previously, digital humanists were restricted by what they could build or what some nerds in a lab had already built. With AI, the sky’s the limit. Others still aren’t quite sure what to think except that there are obvious moral issues surrounding AI use and we’re probably better off morally without it.
Pope Leo XIV recently released his encyclical Magnifica Humanitas. He discusses the power and potential of the tool to do both good and ill in the world. We could intensify and centralize the power of the war machine, as the Trump administration attempts with Project Maven. Or, you know, we could make discoveries that support enormous leaps forward in the physical and social sciences and make lives better.
For now, it’s slightly comforting to know that Anthropic and the Vatican are attempting to collaborate on AI and ethics, as reported by National Catholic Reporter. Also, it’s some comfort that AI companies are hiring philosophers to think through difficult moral, metaphysical, and epistemological questions. It’s not all peaches and cream, but I’ll take hope wherever I can find it these days.
Academia and professional philosophy have endured and experienced the ubiquity of AI in many ways. Faculty worry that students are using AIs to write papers, complete discussion board questions, or take quizzes. I’m not sure whether to laugh or cry upon learning that some students use AI to complete reflection assignments. Journal editors are getting AI slop for submissions. But how has it shaped the academic job market thus far?
Using Claude’s Sonnet 4.6, I looked for mentions of AI and a suite of related terms—machine learning, neural networks, NLP, robotics, language model, etc—on PhilJobs between 2013 and 2026. If you’ve had a hunch that AI-related jobs have been taking up more room in PhilJobs, you’re right.
AI jobs in philosophy: the numbers
Table 1 gives the numbers, illustrated in plots 1A and 1B. In terms of percentage of all jobs posted, AI-related positions have increased from roughly 1% in 2013 to 16% in 2025. Put otherwise, roughly 1-in-6 jobs last year mentioned AI in some capacity as part of the specializations.
There was a peak in 2020, which then declined and didn’t recover until 2023. The best explanation for this is two factors. First, OpenAI launched GPT-3 that year, which received quite a bit of attention from popular media in, among other places, The Guardian and in academia, e.g. DailyNous. Second, COVID. In absolute numbers, AI hires remained the same, but 2021 and 2022 had more jobs posted as part of the COVID bounce-back.
Kinds of jobs being advertised
In addition to the number of jobs for AI specializations increasing, they are increasing at the junior level.
Plot 2A shows that, beginning in 2015, junior positions (including tenure-track, fixed-term, and postdoc) make up over half of all positions advertised. 2B shows the same, along with the total for all junior posiitons. This strongly suggests that departments are thinking about AI specializations in philosophy as a long-term investment, training postdocs and hiring tenure-track faculty. Remarkably, given wider trends in hiring, 2016 is the last complete year in which the share of fixed-term positions was higher than that of tenure-track.
Universities leading the hiring
Pivoting from kinds of jobs to departments, which universities are doing the most hiring in AI?
Plot 3 gives the rankings, but hiring has varied substantially pre- and post-2020, as seen in Tables 4 and 4B:
The data suggest three major regions for AI-related specializations in philosophy: the US, the Netherlands, and Hong Kong, seen in Plot 5.
One major limitation with respect to the international analyis: PhilJobs is the major source for jobs in academic philosophy in the English-speaking world. Universities outside the English-speaking world sometimes advertise in Philjobs, but I don’t have any data about the non-English advertising base rates.
Hiring in other areas of the world tend to go through government systems or academic post aggregation systems, such as Education Sub Saharan Africa, the pan-European Jobs in Philosophy, and India’s CU. I did not search or analyze these sites (or others like them) because of (i) language barriers and (ii) lacking the relevant specializations for each region to know if my search would be exhaustive. If you have that expertise and are interested in collaborating, please reach out.
Philosophy of technology and AI hiring
Technology isn’t a new topic of discussion in philosophy. Phenomenologists, post-phenomenologists, and feminist philosophers of science focusing on philosophy of technology (and allied areas in STS) have looked at the ways in which technology shapes our understanding of the world and ourselves. How often do we find philosophy of technology and AI ads appearing together?
This turns out to be a difficult question to ask at scale. AI is, of course, a kind of technology. But philosophy of technology and STS are deep traditions in modern and contemporary philosophy, drawing on hermeneutics, critical theory, existentialism, phenomenology, post-phenomenology, and post-colonial studies, and developed by thinkers like Heidegger, Arendt, Hans Jonas, Sandra Harding, Helen Longino, Don Ihde, and Peter-Paul Verbeek. (This, in the Stanford Encyclopedia of Philosophy, is referred to as “humanities philosophy of technology.”) Because of this uncertainty, it is worthwhile to make a small detour to discuss it here and in the rest of this report.
Two distinct sources of measurement uncertainty appear in these plots, and they work differently.
AI job counts (all previous plots)
The AI job counts carry two kinds of residual error after the false-positive and false-negative audits:
Residual false positives (~11%, 95% CI 6–19%). Some ads in the AI set are not genuinely AI-related. The audit identified and removed 27 confirmed false positives (15 Wake Forest, 3 Minerva, 9 individual cases), but the sampled audit estimated roughly 11% of the remaining set may still be spurious — concentrated in earlier years (2013–2018) when keyword matching was less precise. This means the AI counts are likely slightly inflated, particularly before 2019.
Residual false negatives (~2%, 95% CI 1–4%). A small number of genuine AI ads were not caught by the scraper — primarily ads using terms like algorithmic fairness, explainability, or trustworthy AI that were not in the original keyword list. The supplementary scrape recovered 32 confirmed cases, but roughly 100–280 additional AI ads likely exist across the full study period. This means the counts are also slightly conservative as a second-order effect.
These two errors partially offset each other. The net effect is that the AI trend line should be treated as carrying approximately ±10–15% uncertainty in any given year, with the directional trend being robust across the full period.
Phil-tech / STS job counts (Plot 6A)
The phil-tech counts carry a different and larger source of uncertainty, represented by the green ribbon in Plot 6A.
The scraper identifies phil-tech jobs using explicit keyword matching. The confirmed count (solid green line) includes only jobs whose full page text matched a phil-tech term — this is a 100%-precision lower bound, meaning every job on that line is genuinely a phil-tech position, but the line undercounts the true total.
To estimate how many jobs were missed, a random sample of 50 non-flagged jobs per year was fetched and checked manually. The fraction of that sample that turned out to be phil-tech (the sample hit rate) was used to project how many jobs across all non-flagged ads were also likely phil-tech. A 95% Wilson confidence interval on that sample hit rate was then propagated through the projection to produce lower and upper bounds on the estimated true count.
The green ribbon spans those bounds, expressed as a share of all philosophy ads. Its width reflects two things: the sample size used to estimate the miss rate (50 jobs per year, which is small), and the underlying variability in the hit rate from year to year. In years where the sample hit rate was 0% (e.g., 2013–2014), the lower bound collapses to the confirmed count while the upper bound remains wide — this is the Wilson interval’s correct behavior when a small sample turns up zero hits, since zero hits does not mean zero true positives.
How to read the comparison between phil-tech and AI in Plot 6A: If the AI line lies above the top of the green band, AI hiring is unambiguously higher than phil-tech. If the AI line lies within the band, the true phil-tech count could plausibly match or exceed AI in that year. If the AI line lies below the solid green line, phil-tech is definitively larger even before accounting for missed ads.
Two different conditional values are relevant in looking at AI and phil tech ads: the likelihood of an ad mentioning phil tech given that it mentions AI and the likelihood of an ad mentioning AI given that it mentions phil tech. The former is interpreted to indicate how often AI-focused positions are looking for philosophers of technology. Table A (below, appendix) indicates that this value is roughly 14% over all years. The latter is interpreted to indicated how often phil tech positions are looking to engage AI. Plot 6D shows that these values are consistently higher than 14% beginning in 2018. Table 7 shows the (non-conditional) overlap values across two periods: 2013-2019 and 2020-2026, the cutoff (as mentioned previously) defined by when LLMs, and specifically GPT-3, came to be highly visible.
Conclusions
What are the takeaways? The least controversial and most obvious is that the relevance for AI as an area of research in contemporary philosophy has grown significantly in the last 13 years and doesn’t indicate any slow-downs.
Less obviously, hiring to date doesn’t seem to engage with historical and non-analytic traditions in philosophy, as indicated in the analyses of STS and philosophy of technology in AI ads. This is further substantiated by the data in the appendix on AOS. This, I think, hamstrings future work. Global and historical philosophical traditions are abundant with conceptual resources for thinking about our future with AI which we ignore at our professional and social peril. At a time when the costs of AI become hourly clearer, philosophers’ collective contributions are vital–or at least they stand to be.
Finally, the data are about philosophers investigating AI. There is little, if any, data on philosophers using AI in their work. Digital humanists as a whole are capitalizing on the upswell of AI, but how many among these are philosophers? I mentioned at the start that I used Claude’s Sonnet 4.6, but even that has been for data collection and analysis, not necessarily for doing philosophy in some more traditional sense. But the history of philosophy is chock-full with examples of new technologies (material and conceptual) changing how philosophy is done: writing, the printing press, probability theory, modal calculi, personal computers, the Internet, email. One might reasonably wonder if AI’s impact will not be only on what philosophers talk about but also how they do philosophy.
Appendix: AI and AOS
“For now, it’s slightly comforting to know that Anthropic and the Vatican are attempting to collaborate on AI and ethics, as reported by National Catholic Reporter.”
Yeah, the Vatican has an amazing moral track record: they have always been committed to facts, champion diversity, have no grain of Euro-centrism, always pay taxes, don’t own much more than they need, only fight holy wars, and, of course, love children!
How is whether one “champions diversity” relevant to their moral track record?
The Vatican is a male-dominated institution that still does not allow women to be ordained. Women are thus excluded from positions of authority within the Catholic church. This is an institutionalized degradation of women–and only the tip of the iceberg. If you believe that the Catholic church’s sexism is morally irrelevant, you should try to look beyond your anti-woke bubble. We should agree that diversity is a value when it comes to having access to public office–no matter what you think about affirmative action! No woman can become a Catholic priest, a bishop, a cardinal, or Pope per virtue of their gender. Do you believe that such an institution is a just ethical guide for a global technology like AI? I do not think so. It seems to reproduce many of the Silicon Valley’s power structures. So, good luck with being saved by the Pope. That he is back in the public eye, is, at best, a sign of the time–and not a good one!
I reject non-cognitivism in ethics, but when I read comments such as these two from EuroAmerican, I can understand why non-cognitivism in ethics is taken so seriously. Pope Leo requests that the world be morally careful with AI, especially in relation to worker displacement and unemployment. EuroAmerican responds by bringing up Catholic pedophilia scandals, holy wars, and women’s ordination.
People listen to the Pope because they attribute moral authority to him. I question the justification of this authority by pointing to the churches problematic moral track record. The Pope is neither an expert on AI nor on economy nor on worker’s rights (questionable record too!). If you believe that such criticism is irrelevant, how should we assess the moral authority of a figure like the Pope? Put differently, blind trust is not very philosophical…
Geez. Can you be a bit more open minded?
Not all people who listen to what the pope and crew say about AI listen to it because of the pope’s moral authority. In fact they might be atheists who, thank heavens to mercy, had never been habituated to listening to any monotheistic religious authorities in their entire lives. They nevertheless might be profoundly grateful that the pope and his crew address these issues.
But as far as pope encyclicals on AI go, I recommend you first read the previous pope’s encyclical produced a few weeks before he died. It’s less hedged.
Well, one might think that goals like improving equality of opportunity and equality of outcomes are morally worthy, for one thing, so that someone who doesn’t have those goals, or whose actions stymie them, is morally deficient in that respect. Perhaps you disagree, but it’s not difficult to see why others might think such considerations bear on someone’s moral “track record.”
Sorry, my above comment was overly brief and opaque. The point was that one might reasonably think championing diversity serves, or is a part of what it is to even have, some goals taken to be morally worthy. I should have made that clearer.
it might be worth searching the philos-l archive in addition to philjobs.
This is all so troubling. May I please be allowed a moment to hearken (sp?) back to a previous post here at DN for some guidance: I think that, just as it’s, albeit somewhat controversially apparently, appropriate and right to grieve the role that AI has played in undermining the thrill of learning in our students, it is likewise appropriate to step back for a moment and grieve the role that AI has played begun swallowing, as it were, the real estate in the wider philosophy job market. By analogy, in the older days, freshly minted PhDs might ‘shop’ at a job market in a way akin to a small town with mom-and-pop style offerings that represented a wide array of subdisdiplines. Some people would apply for the ancient philosophy jobs, some working in metaphysics would apply for those jobs, the ethicists would cast their hat in the ring for the ethics jobs, language for language, epistemology for epistemology, etc. But just as, let’s say, when a Wal-Mart moves to town it begins to swallow up these mom and pop shops, likewise, AI seems to be doing a similar kind of swallowing in terms of the market: rather than to inherit a simple and efficient ‘mapping’ job market wise that takes us from our specialisation to a job in that specialistion, the mapping now (thanks to Walmart-style AI) takes us from our specialism to a job that includes AI in the title. As the great Crantor of Soli once spoke against the Stoics, there is a time for the coolness of reason but also a kind of measured grief is admirable as a form of philosophical consolation as we lose what was good about the past.
I’m afraid this grieving is not very solution oriented, Crantor of Soli. We can all grant that grieving and weeping and turning inwards is appropriate sometimes. But we also need to buckle down, put on our hard hats, grit our teeth and learn to adapt strategically in the environment that (for good luck or bad) we find ourselves. I’m afraid that this means, in this case, learning to ‘throw a bone’ to AI in one’s thematic publication choices, at least sometimes, enough to be able to put AOS or AOC on the application and point to evidence of publications. Then of course one can always move back to whatever they want after they get the job, when it comes to their own research preferences (modulo whatever , say, AI teaching based constraints are in a contract – in some cases, there are none).
The fact well over a quarter of philosophy job ads this year so far are in philosophy of AI and technology is mad. Surely plenty of external funding for these posts explains a lot of it, but I have also heard from a senior philosopher in the UK that his department is looking for a hire in these fields because of the demand from the students to take a “Philosophy and AI” course. Is this something that others can relate to?
The demand from students to take a Philosophy of AI course doesnt explain why almost all the ads are looking for research specialization in it. You dont need research specialization in a specific topic at the intersection of three or four different philosophical fields (philosophy of tech, mind, ethics, and aesthetics, arguably), for people to be able to teach a course on it.
I don’t care for this trend, but generally students wanting to take classes in a topic seems like a perfectly good reason to hire in an area.
‘Global and historical philosophical traditions are abundant with conceptual resources for thinking about our future with AI which we ignore at our professional and social peril. At a time when the costs of AI become hourly clearer, philosophers’ collective contributions are vital–or at least they stand to be.’
Well said. I think AI is one of those areas that benefits from every branch of philosophy. It’s easy to bludgeon things like philosophy of mind, language, metaphysics, ethics, mathematics, philosophy of science, political philosophy, etc. under one Philosophy of AI label, but the work being done still relies on these deeper traditions and I expect will require all of these AI x Philosophy Sub-discipline specialists (who don’t *only* work on AI).
Right now the missing piece (in my view), is just getting more of these traditions to do the interdisciplinary work / training needed to bridge this. Technical specialists are not really doing it (though there have been a handful of attempts).
Philosophy ethicists are all over this topic, but outside of ethics there is still a fledgling amount of Philosophy of AI work compared to what is needed.
I think it would behoove us to see this less as AI is taking over Philosophy and more like AI is one of the most pressing sociotechnical issues of our time and it’s going to require experts from every subfield to direct it’s future. We (philosophers) ignore it at our peril.
The people putting together Philosophy of AI ads only vaguely know what they want (which in my experience, is true of *any* job ad, it’s best to treat job ads as aspirational wishes, not checklists).
If someone thinks Philosophy of AI needs a legal philosopher, metaphysician or a Kant scholar, go be that person (if you’re willing). The need is there, the hiring committee just might not realize it until they meet you.
At a glance, there are more AI jobs this year than aesthetics jobs in the last ten years combined. Which I think is really too bad.
The boom is going to shape not just the jobs landscape, but the research landscape, too. All these people will need to publish on the subject, and will be training students and grad students, etc. And they, in turn, will all be pushing their new AOS, too. Which means that even if it’s all just a fad, a couple of boom years will have transformed the research landscape for a long time to come. Which, again, I think is really too bad.