Keeping the Humanities Human

As artificial intelligence has upended the way in which students read, learn and write, as well as how teachers evaluate and mark, professors and leaders at institutions of higher learning appear to have been largely left to their own devices to figure out how to teach in a profoundly transformed landscape.

Many faculty members in the hard sciences and social sciences have pointed to the “productivity boost” AI can offer, and the research potential unlocked by its ability to process and analyze vast amounts of data. AI’s most enthusiastic proponents have boasted that the technology may help cure cancer and “accelerate” climate action.

Yet in fields most explicitly associated with the production of critical thought – what is collectively referred to as the “arts” or the “humanities” – most scholars tend to see AI as less a boon than a unique threat, one that extends far beyond homework cheating and casts doubt on the future of higher education itself in nothing less than a ever-encroaching machine-dominated future.

American degrees, for example, often cost up to hundreds of thousands of dollars and result in decades of accumulated debt, with recent years seeing nothing less than a freefall in public confidence in US higher education. To some extent this has been exacerbated by Donald Trump and his MAGA base’s assault on hitherto liberal bastions like Harvard, but the backlash against elitists in their perceived ivory towers has been building for years prior to the president’s ascendancy. Now, with the potential for AI to increasingly substitute independent thought, a pressing question becomes even more urgent: what exactly is a university education for?

So how are academics in the humanities or adjacent fields seeking to adapt at a time of dizzying technological advancement with few standards and little guidance?

By and large, they seem to have the view that reliance on artificial intelligence is fundamentally antithetical to the development of human intelligence they are tasked with guiding. They frequently describe desperately trying to prevent students from turning to AI as a replacement for thought, at a time when technology is threatening to upend not only their education, but everything from the stock market to social relations to the very nature of war itself.

Most professors described the experience of contending with technology in despairing terms. But beyond this they still have an obligation to engage with their students not in the world they wish for but is. One option is to talk about AI with their students not under the framework of cheating or academic honesty but in terms that are frankly existential: What is it doing to us as a species?

AI criticism – or “doomerism”, as the technology’s proponents view it – has been mounting across sectors. But when it comes to its impact on students, early studies point to potentially catastrophic effects on cognitive abilities and critical thinking skills. The reality is that already many students have been left essentially incapable of reading and analyzing, synthesizing data – ‘connecting the dots’ in a way their predecessors could a mere generation ago. The possibility exists that colleges and universities rushing to embrace the technology are really preparing to “self-lobotomize” because students will rely in the tech to provide all their answers, or at least most of them, obviating the need to form one’s own theories, hypotheses and ultimately, conclusions.

Some universities have even begun to require every freshman to take a class in generative AI, competitively pitching themselves as the first “AI fluent” university, pledging to embed AI “across every major”.

Really?

It’s just like trying to pin jello against the wall. No one – institutions or governments - knows what that means, other than repeating generic talking points and catchphrases. In the case of literature, for example, don’t these tools actually seem to mitigate against the educational goals academics have for students?

That’s the crux of what many professors in the humanities fear: that technology that may well be a cutting-edge tool in other fields could spell the end of their own.

No less an advocate for AI unchained than Alex Karp, Palantir’s co-founder and CEO, stoked those anxieties when he said in a recent interview that AI will “destroy humanity's jobs”. Or will the opposite hold true? Will studying the humanities is going to be more important than ever, as the opposing camp suggests?

A number of tech and finance companies have recently said that they are looking to hire humanities majors for their creativity and critical thinking skills. Indeed, enrollment data at some universities suggests that the long-struggling humanities might have begun to see a resurgence in the age of AI, with early signs pointing to a reversal in decades-long decline in English majors in favor of Stem ones.

Some caution that while the humanities will survive – it will be as a province of the few.

When he predicted the end of the humanities, Karp assured that there would be “more than enough jobs” for those with vocational training. Indeed, several professors spoke about concerns that AI will exacerbate a widening divide in global higher education and that small numbers of elite students will have access to a more traditional, largely tech-free liberal arts education, while everyone else has a generic, soulless form of vocational training administered via AI instructions. Education bifurcation?

Many professors talked about keeping the technology out of the classroom as a battle already lost. As many as 92% of students in the U.S, have reported resorting to the technology in their schoolwork, recent surveys show, and the numbers are rapidly increasing even as growing numbers express concerns about the technology’s accuracy and the integrity of using it. Reliance on AI among faculty is also on the rise, with observers pointing to the dystopian possibility that the college experience may soon be reduced to AI systems grading AI-generated homework – “a conversation between two robots”.

Some universities (and many schools) globally have adopted AI detection software to catch artificially generated work; others prohibit faculty from directly accusing students of having used AI – as they can often be wrong as we have seen in very controversial and public cases where the line between human thinking and machine learning has become so blurred nothing can be definitively proven.

In the case of the humanities, it raises another profound question: if there are few original thoughts and ideas as well as many oft-repeated phrases and familiar-sounding arguments at what point does a student’s use of such verbiage become plagiarism or AI generated? That an AI and a human could independently come up with oft repeated sentences is no longer a rarity: it’s become a near certainty.

Professors these days resort to oral interrogations, handwritten notebooks and class participation for grading purposes. Some require students to submit transparency statements describing their work process. Others have reportedly injected random words like “edamame” and “Jean-luc Picard” into assignments to confuse learning models – exposing students who did not even read the prompts before cutting and pasting them into AI engines.

Many professors would likely be frustrated at having to sift through students’ artificially generated homework, for it creates hours of additional labor (likely borne by Teaching Assistants who have to spend time cross-checking traditional references and – ironically –using AI as an investigatory tool as the means to catch another AI. It’s easy to see how bonds of trust between the educators and those being educated begin to break down.

In an attempt at compromise some will allow students to use AI for research – to a point. A compromise might be that while AI has helped make students’ presentations richer and more interesting – and that they may use it to prepare, they still have to speak from minimal notes and stand in front of a photo of a text they annotated by hand. He also assigns written responses to texts only after the class has discussed them. They could in theory use their phones to record the conversation, feed a transcript into a chatbot and produce a paper that way but that is more trouble, I think, than the average student would take.

Many university administrations are embracing AI for instruction, research and evaluation. In some cases, AI has even guided decisions about which programs to cut at times of austerity in the education sector.

More than a dozen universities have partnered with OpenAI on a $50m USD initiative that the company has said will theoretically accelerate research progress and catalyze a new generation of institutions equipped to harness the transformative power of AI. California State University has joined several of the world’s largest tech companies to create what they deem ‘an AI-powered higher education system’, as the university put it. Multiple universities have introduced AI majors and masters.

All of these plans are lofty but actually offer little guidance on what professors are supposed to do with students who can’t read more than a couple of paragraphs at a time or turn in essays generated in seconds by a machine. Necessity being the proverbial mother of invention, left largely to themselves, some are trying to articulate clearer lines around AI use and organize a more coordinated effort against its encroaching dominance.

Last year, the American Association of University Professors, which represents 55,000 faculty members nationwide, published a report warning that universities were adopting the technology “uncritically” and with little transparency, which is diplomatic speak for ‘there are no standards or guidelines.’ Given that institutions of higher learning are, at their core being run like businesses, more and more university unions have begun incorporating protections against AI in their staff contracts so as to establish oversight mechanisms and give faculty greater input – as protection for their intellectual property from feeding machines that may eventually replace their membership.

But much of the organizing against AI remains ad hoc and via word of mouth, with faculty-led initiatives like the website Against AI, which offers resources to those trying to shield students from the intellectual ravages of outsourcing elements of their education to a machine. While their administrators, trustees and bosses unrelentingly hype AI educators are throwing around assignment ideas to mitigate AI use – ranging from oral exams to requirements students submit photographic evidence of their notes, to analog (re. old-fashioned) journals.

In all of this uncertainty there exists an opportunity to get students to think critically about technology and its role in ever-evolving human society. For example, if an academic professional suspects someone has used AI, they can talk to the students about it, treating the incident not so much as the reason for punitive action but rather as an opportunity for growth, restorative justice and enhanced authenticity in student-instructor relationships. Students can also be made aware through dialogue and discussion that while AI in particular and technology in general has undoubted benefits there is also the reality that tech companies are trying to make them “helpless” without their product. Taken to extremes, these tools are being made available (or even given away) in an effort to addict an entire generation.

So, in a sense, there is a discussion to be had about deciding to be human and by so doing see if students can find a middle ground. The movement towards technological reliance is by no means a uniform phenomenon. There is mounting discomfort from students against the technology – and technology’s dominance in their lives overall. They may even resent being seen as guinea pigs in this giant social experiment and that something is being stolen from people.

Those who are rejecting AI are often driven by environmental concerns, and suspicion of companies they view as partly responsible for shrinking democracies and a more violent world.

In America, for instance, that has spurred activism. The University of Michigan recently announced plans to contribute $850m toward a datacenter to provide AI infrastructure in collaboration with the Los Alamos National Laboratory – at a time when it is cutting funds for arts and humanities research and on the heels of anti-war protests on campus. A spokesperson for the university said that the planned facility would be smaller and consume less energy than a “typical datacenter”.

As pushback grows, so does an emphasis on those intrinsically human qualities that differentiate people from machines – the very qualities a humanistic education seeks to nurture. While it would be defeatism, this idea that there’s no stopping technology and resistance is futile, everything will be crushed in its path. That needs to change … We can decide that we want to be human.

But that means struggling with the eternal question of what it means to be human.

Perhaps in the end all that can be done when it comes to teaching in the age of AI is that educators can plant seeds and hope. Maybe this calls for a transformation in the profession itself: in the long-term teachers and educators might find ways to align their subject matter so that it can help their students become happier human beings, who are able to take a walk, appreciate the environment and cultures in which they live, to experience and describe things for themselves.

Maybe that's the next phase of the Human Adventure.