Like many others, I spent the first few weeks of this summer searching ‘internship’ on LinkedIn jobs and Handshake, praying that there would be any position that required zero experience, or whatever vaguely tangible skills my English and film and media studies majors could advertise.
Unlike my similar job searches in years past, this time I noticed a new addition: Quite a few of these listings contained calls for “AI literacy” or “fluency with generative AI tools” as “preferred qualifications.”
It is clear that one’s understanding of and fluency in using AI programs have become a valuable and employable skill, especially for young job seekers entering the workforce.
This has made me wonder: How exactly is Tufts preparing its students for this AI-saturated job landscape?
After throwing our caps, are we going to be thrown into the deep end of a dystopia where bots have usurped our entry-level jobs, rendering our liberal arts degrees in English and film and media studies obsolete? Or will we be the brains quick and adaptable enough to get ahead of them? Moreover, is Tufts adapting quickly enough that it will equip me with the necessary “AI literacy” I need for a career after I graduate in 2028?
Also — what does “AI literacy” even mean?
These are some of the questions I brought to Nick Seaver, director of the Science, Technology & Society program and a member of Tufts’ AI Council.
Turns out, there is not a clear, institutionalized way of navigating AI in the classroom, a reality I have come to understand personally given the diversity of AI policies I’ve had to re-learn for each new class.
“I think making a lot of [these AI policies] devolve to individual faculty is very challenging because faculty are going to try to treat the issue in a way that makes sense to them, and students are encountering four or five or six different versions of this policy in a semester,” Seaver said.
Seaver’s frustration points to a broader structural problem that Tufts’ AI Council was created, in part, to address. But fixing it, he noted, is easier said than done.
“A lot of universities — and Tufts is unfortunately not exempt — have a kind of kindergarten soccer approach to pursuing AI, where every single person chases the ball in exactly the same spot,” Seaver said. “It might be better if we spread out and people took care of different things.”
The AI Council was formed in spring 2026, following recommendations from the AI Task Force that surveys the university population and assesses immediate steps for its AI governance. It aims to represent a holistic view of approaches to AI across Tufts schools, departments and even non-academic units, like the Career Center, Counseling and Mental Health Services, Student Accessibility and Academic Resources Center and the library staff.
Hoping to better understand the role of the AI Council, I spoke with Carie Cardamone, the senior associate director of the Center for the Enhancement of Learning and Teaching as well as the associate chair of Tufts’ AI Council.
“It’s not like the AI Council has some agenda where everybody should use AI to do everything. I get that misconception a lot,” Cardamone said.
“I think [the AI Council is] about [how generative AI] is impacting the way we work. There are a lot of people excited about opportunities with it and are having fun exploring it and would like to understand better how to explore it,” she added.
The survey data that the council is responding to reflects just how divided the student body actually is on the question of AI. Cardamone estimates that around 10% to 15% of students will never touch AI — they simply do not want to. On the other end, roughly 30% have embedded it deeply into their learning, their creative practices and even their personal organization. Other survey participants fall somewhere in between.
This range of attitudes has come with real academic consequences. Last spring, faculty began flagging a troubling pattern: Students were acing their problem sets but failing their exams.
“We saw failure rates across the university, across disciplines that we’d never seen before,” Cardamone said.
The culprit, she suspects, wasn’t students deliberately cheating, but something more subtle. “I think it’s not because students are saying, ‘Hey, do my homework, ChatGPT.’ Maybe some are, but most aren’t,” she said. “They’re like, ‘I’m trying to solve it, and then it’s giving me the better answer.’”
As a result, students presented flawless homework that masked genuine gaps in understanding.
This is precisely the kind of on-the-ground feedback that the AI Council exists to collect, synthesize, distribute and address.
Rebekah Plotkin, the director of the Center for Professional and Workforce Impact and a member of the AI Council, noted that the council’s responsiveness to student and faculty feedback has been one of its defining characteristics. “Everyone on the committee really takes [that feedback] to heart and listens to what people have to say. I found that to be really refreshing. You don’t always get that at other institutions.”
Cardamone broke down three main focuses of the AI Council across the university.
The first is the Generative AI Guidelines, a centralized set of broad, university-wide AI recommendations which were first released in February 2026.
“We very deliberately went after guidelines instead of policies, because with guidelines it allows individual scholars in their area, disciplinary context or clinical context to make their own decisions,” Cardamone said. “The intent of guidelines is to give us a shared framework for talking about [AI], and to use those guidelines to help individual departments or schools come up with their own policies.”
The AI Council aims to be seen as an advisor in this process, not a legislator. “These things are constantly changing … as AI has changed, and as we get feedback from people about how these guidelines are working,” Cardamone said.
The ultimate goal is for each school or department to develop their own more specific AI policies, as has already begun with the Tufts Medical School.
The second focus is curriculum. This semester, Tufts launched two new minors in the Computer Science department: a Minor in the Application of AI and a Minor in AI Development. But the Council’s curricular development goes beyond the technical. There are also other minor programs currently in development that are connecting AI with the social sciences and humanities, including one currently undergoing the approval process within the Science, Technology & Society program.
“The idea is that this minor would help you understand enough technically about AI to have a broad sense of how current systems work, but also to think about the kinds of social critique and analysis stuff you would learn in your other courses [and] how you can apply that to AI,” Seaver, one of the people spearheading this potential minor, said.
The third focus of the council is faculty development. “Faculty feel largely unsupported in AI,” Cardamone explained. “There’s so much going on in the institution, and it’s hard to see where the supports are.”
To address this, the AI Council launched the AI Faculty Fellows program, a new initiative opening to faculty across the university.
“The intent is [that] these faculty aren’t here just to learn about AI, but to help their disciplinary area adapt to AI,” Cardamone said. “In some cases, that may be helping them learn to use new tools or do new cool things with it, or bringing in outside speakers. In other cases, it might be revamping assignments and curriculums to create these AI-free spaces. And both things might be true in the same discipline.”
Which brings me back to my original question: What does “AI literacy” even mean?
Apparently, the definition is not quite settled. “There’s a lot of complex thoughts about what AI literacy should be and how it should be integrated into the curriculum,” Cardamone said.
For Cardamone, shared experiences and conversations are the best path forward. “Can, through these conversations, we come to a shared understanding of what the baseline AI literacy we want across the school is — across all the students, staff and faculty — to be able to do their jobs? To be able to wrestle with the issues that come up when you’re trying to decide: Do I use AI on this task … or this communication I’m having with another human? Where does AI’s role fit in it?”
At the heart of those conversations, Cardamone said, is accountability. “If you use AI to make a decision, whatever that decision is, you are accountable for that decision,” she said. “Whether it’s to share something written by AI or not, whether it’s to do a task in a certain way, all of that still lies with the human.”
And underneath accountability, she said, is something even simpler: trust. “Faculty trusting students, students trusting faculty. Just two people trusting each other that their interaction is really between two humans and not moderated by AI.”
For now, the AI Council is still working out what exactly that looks like in practice. But if Cardamone’s passion for the question is any indication, the conversation around AI at Tufts is well underway.
Part Two of this series will look at what AI literacy actually looks like in practice, including new programming from Tisch Librarians. A piece on Tufts’ new AI minors is coming later in the semester. Stay tuned to see if I will ever get a job.
