When AI Triggers Our Imposter Syndrome

Photo by Changbok Ko on Unsplash

Several people have spoken to me about not feeling qualified to talk to their students about AI. Such feelings aren’t limited to this emerging technology. For many, the imposter syndrome has become part of what it means to be a faculty member in higher education. We shouldn’t let feelings of being unqualified cause us to veer away from vital conversations with our students. What I’ll share below is quite difficult, but I think it might give others a sense of what some of us struggle with in academia.

My Imposter Syndrome

In the fall of 2001, I started my college education by taking a night class at State Fair Community College. I was just 18, so I blended in well with other students. No one stopped me and asked if I only had a GED or inquired about what I’d been up to since dropping out of high school three years before at age 15. It took me six years to complete my undergraduate degree, largely because I didn’t know how to advocate for myself or what resources I could use to help me. I had to teach myself skills I’d lost and navigate the labyrinth of financial aid forms, class listings, and degree requirements. I never once met with an advisor. If I had, I don’t think I would have told them what I was going through. Part of it was a sense of shame, but I think an even deeper part was a sense that I did not believe I belonged and never would.

In many ways, I’ve lived the entirety of my adult life feeling like an academic imposter. I played the role of pretender all through night school and into graduate school, where I earned my MFA in fiction writing about a world I’d had one foot in that many of my fellow students could not understand. That world taught me how to hustle, giving me skills I used each summer to renovate our house.

The Ubiquity of Imposter Syndrome

It’s hard to say just how much pretending to belong was foundational to my identity, first as a student, and then later on when I started teaching. What was so strange was how many of the people I met in grad school and later as an adjunct and full-time instructor confessed a similar feeling. They all felt like they didn’t belong in the classroom, even though they arrived in academia in more traditional ways. We each had our flavor of imposter syndrome. Occasionally I’d chime in with bits and pieces of my story and my friends and colleagues would do a double-take. Raise an eyebrow.

I think we all forget how many different paths we traveled before arriving in the classroom. Many of us are first-generation students and now first-generation teachers, immigrants learning new languages and customs, many others quietly navigating hidden disabilities, and so many other identities that make our journeys far more complicated and complex than the tweed-wearing, privileged stereotype that stubbornly clings to the term “professor.”

Part of the imposter syndrome caused us to rack up professional credentials and bonafides, thinking doing more will earn our place. We have lines on CVs that often stretch ridiculously long to justify that we belong and that we should be here. We don’t work, we grind. We grind so much that we don’t realize how unhealthy it is to work so hard for so little. But it isn’t higher pay we’re seeking—it's validation. We want the universe to see that we do indeed belong, but that’s never going to happen, at least not the way we imagine. We’re never going to get a cosmic cookie cake with the phrase “You Made It.” Some of us think that cake is tenure and wind up profoundly disappointed upon receiving it, even leaving academia entirely within a few years because we realize how bitter-sweet the taste.

It's this very experience of perpetually feeling like an imposter that I draw on now as I grapple with how to discuss AI with my students. Just as I had to confront my insecurities and admit what I didn't know when I first entered academia, I now must model that same vulnerability and openness as we all navigate this uncharted technological territory alongside our students. My imposter syndrome has, in a strange way, prepared me for this moment.

Confronting AI as an "Imposter"

This fall I will transition to a new role as an Assistant Director of Academic Innovation at the University of Mississippi. I’ll be training faculty in applied artificial intelligence. While I may not have a degree in computer science, what I do have is hard-earned experience in admitting what I don't know, asking questions unabashedly, and figuring things out as I go. I know how to break down complex concepts and make them accessible to others. Most importantly, I'm willing to be an imperfect learner and teacher in front of my students. I know what it means to fail. I know what it means to get something wrong. These are some of the skills I believe are most essential in confronting the rapidly evolving field of generative AI.

If generative AI’s rapid development continues, we’re all going to have to come to terms with being imposters when it comes to talking with our students about it. Trust me, I know this is a big ask to put yourself into a situation that could trigger it. Talking about my past is terrifying even in the context of this essay. Letting someone know you may have arrived in a similar career from such a different journey can be jarring. It opens you up to judgment, even ridicule. You might think it does the same to your students if you revealed to them that no one knows how to use or not use generative AI in education, or what lies beyond with the technology when they enter into their chosen careers. There’s no degree path for this, no number of certs you can rack up to create an illusion of competence that might pass for the expertise we’ve frankly institutionalized in academia. All we are left with is radical honesty in all of its humbling and frightening power.

The good news is that once you get past your initial doubts, you'll remember that you are an expert within your discipline, with years of experience explaining complex concepts to others. The time you've spent adapting to unexpected roles has equipped you with the skills and experience needed to be honest with a group of maturing learners who are still developing their understanding of AI. You can admit that you don't have all the answers when it comes to the latest technological innovations that seem to be popping up all around us. We often feel like imposters because we spend so much time trying to embody what we imagine a smart and capable person would look like in our circumstances. In doing so, we fail to recognize that we have already arrived as that very person. We've worked so hard to create an idolized image of ourselves that we fail to recognize when we stop playing the role of pretender and become the expert.

You don’t have to have a firm stance on generative AI in education or a background in machine learning to talk to your students about the meaning and purpose of why they are there to learn. Writing existed before generative AI. Learning did as well. We know how to talk to our students about what matters. The pandemic has caused these relationships to change and it's harder now to reach certain students than it was even five years ago, but to me, that’s all the more reason we need to lean in and talk to them. This matters because we’re educators in a new era where machines can mimic reasoning. The previous sentence is as absurd as the feelings we have trying to talk to our students about it, but that’s precisely why we must lean into our imposter syndrome, not as a source of shame, but as a springboard for empathy, curiosity, and humility.

By letting our students see that we too are grappling with the implications of this technology, still figuring it out day by day, we can create teachable moments for all of us. Our expertise lies not in having answers, but in being brave enough to ask the questions alongside our students, and in modeling openness our moment demands. It is time to wear our imposter syndrome as a badge of honor and lean into these vital conversations with courage and radical honesty.

Some Recent Interviews and Podcasts

June was a busy month! I was happy to sit down for quite a few interviews about the Beyond ChatGPT series and AI in education:

• Beth McMurtrie from The Chronicle: Professors Ask: Are We Just Grading Robots?

• Susan Lanier-Graham from Every Learner Every Where: Principles for Understanding AI in the Classroom

• Lauren Coffey Inside Higher Education: New ChatGPT Version Aiming at Higher Ed

• Jeffery R. Young EdSurge: Latest AI Announcements Mean Another Big Adjustment for Educators

• Derek Bruff’s Intentional Teaching Podcast: AI's Impact on Learning with Marc Watkins

• Joel Amidon’s Amidon Planet Podcast: AI in Education with Marc Watkins

• Lauren Coffey Inside Higher Education: Murky Guidelines on Using AI Recording Devices in Classrooms