Podcast Summary

Podcast: The Gray Area with Sean Illing (Vox)
Episode: If AI can do your classwork, why go to college?
Date: June 30, 2025
Guest: James Walsh, Features Writer at New York Magazine's Intelligencer

Overview

In this episode, Sean Illing interviews James Walsh about the rising prevalence of AI-powered cheating in higher education. Walsh’s recent article documented student and faculty attitudes toward AI tools like ChatGPT, Claude, and Copilot, and explored the increasingly blurred line between legitimate academic assistance and academic dishonesty. The conversation examines not only how students are using these tools—out of convenience, necessity, resignation, or ambition—but also what these changes mean for the future of writing, critical thinking, and the college experience itself.

Key Discussion Points and Insights

The Pervasiveness of AI Cheating

• AI at the Heart of Modern Cheating:

  • Walsh started investigating general cheating but quickly saw AI as central to everything now: “Everybody I'm talking to is in some way cheating. Even if… They don't think it's cheating.” (03:30)
  • The definition of "cheating" itself is being bent and redrawn by the ubiquity of AI.

• Cheating is Both Old and New:

  • Older methods (cheat sheets, looking over shoulders) haven’t disappeared, but AI has "blown the ceiling off" (04:09), making cheating larger in scale and scope.

How Students Use AI

• Common Platforms & Tactics:

  • Most students default to ChatGPT, but also use Claude, Gemini, Copilot, and more (07:39).
  • Uses are wide-ranging: writing and outlining essays, note-taking, summarizing textbooks, creating study guides, analyzing data, and especially coding assignments.
  • Quote: “They're using it for kind of every facet of their education, really.” (07:39)

• Computer Science Paradox:

  • Coding students rely heavily on AI for homework, often failing in-class exams on the same material. Some tech executives even question the point of hiring new coders. (09:37)
  • “If you are depending on AI now, you are just training yourself to be an assistant to an AI platform and you are going to be the most replaceable person in the workforce.” (09:37, Walsh quoting a professor)

• Hands-off Approach:

  • Some students copy-paste assignment prompts into ChatGPT and submit whatever comes back, often without reading it—sometimes turning in text containing 'Trojan horse' phrases like 'broccoli' or 'Dua Lipa' that professors plant to catch AI-generated work. (11:53)

Student Perspectives on Cheating and AI

• A Spectrum of Attitudes:

  • Some students are alarmed at the shift toward AI: one noticed class discussions growing superficial, with students quoting studies never covered in class (15:12).
  • Others feel compelled to use AI to avoid falling behind, considering AI skills necessary for future job markets.
  • Notable Quote: “If they're not using AI, they're at a disadvantage. And not only that, AI is going to be around no matter what for the rest of their lives.” (15:12)

• The New Networkers:

  • Some view college purely transactionally (e.g., Roy Lee): “I'm here to find a cofounder and a wife.” (17:25)

• Justifying the Use:

  • Students like 'Wendy' distinguish copying from "using," saying they use AI for ideas and structure but not full essays, allowing them to work faster (20:03).

• Temptation is Universal:

  • Both Walsh and Illing admit they might have used such tools if they had existed in their student days (23:19, 46:26).

The Blurred Line Between Assistance and Cheating

• Unclear Boundaries:

  • Both host and guest note it's “asking a lot” of students to resist using AI when it's so tempting and efficient, and when everyone else is (22:01).

• “Hackable” Assignments:

  • Many see academic work as something to be "hacked" and optimized, not necessarily learned.

The Professor and Institutional Perspective

• Despair and Fatigue:

  • Most professors, particularly in writing and computer science, are overwhelmed and demoralized. Policing AI usage is nearly futile (29:26).
  • Even when professors know work is AI-generated, they lack solid proof and institutional support—and many just give up (31:24).

• Reframing Assignments:

  • Some professors resort to oral exams or handwritten blue book tests to fight AI use, but recognize these are only partial fixes and can disadvantage some students (33:50).
  • Quote: “I somehow don't think we're going to police our way out of this problem.” (32:07)

• Faculty Use of AI:

  • Many professors now use AI for lesson planning, textbook writing, or even grading, which students often notice and resent (35:18).
  • Raises ethical questions: “You can't really ask students to not use AI … if you're using AI to produce your lectures or write your textbooks or do your lesson planning.” (34:28)

• Administrative Ambivalence:

  • Walsh suggests administrators are optimistic about AI or want to ride the next tech wave, but may not fully grasp the scope of the problem (37:54).
  • Illing is more skeptical: “They seem more comfortable with a degraded education as long as the tuition checks are still cashing.” (39:53)

The End of Writing and Thinking?

• The Donut Hole at the Center of Academia:

  • Both Walsh and Illing repeatedly warn about the difference between spell check/calculators and ideas-synthesizing AI: “We're a long way from spell check.” (50:00, Illing)

• Writing as Thinking:

  • The hosts underscore that writing is not just output—it's “thinking” itself. If you don’t write, you don’t learn to think. “For me at least, I don't even know what I think until I write.” (48:08, Illing)
  • Walsh fears if he had used AI in college, he "doubt[s] I would be who I am and do what I do." (46:26)

• Moral Panic or Real Revolution?

  • Both consider whether they're just 'old men yelling at clouds,' but land on the side that this is a unique, more profound change than previous technological disruptions (50:04).

Broader Social Implications

• Toward a Post-Literate Society?

  • Walsh considers the possibility of a “post literate world”—expressing concern about its consequences, including for democracy (52:35).
  • “I do not believe there's a model of liberal democracy that works in a post literate society.” (54:28, Illing)

• Exacerbating or Easing Inequality?

  • AI can help students with language barriers or learning challenges, but also risks making writing and critical thinking a luxury for the privileged (55:32).
  • “Writing will be an anachronistic elective, like basket weaving… only for people who go to this certain school or can afford certain school.” (55:32, Walsh)

Notable Quotes & Memorable Moments

• On the scale of AI Cheating:
  “The floor of cheating is still there. It's just that the ceiling's been blown off.”
  — James Walsh (04:09)

• On the transactional nature of elite college:
  “I'm here to find a cofounder and a wife.”
  — Roy Lee, relayed by Walsh (17:25)

• On justifying AI use:
  “She was nostalgic for the act of actually writing, but felt as if she wasn't cheating by outsourcing the deep thinking that essays are meant to provoke, you know, outsourcing that to an AI.”
  — James Walsh (20:03)

• On learning as a casualty:
  “If I start doing this now, I am going to lose something. Some part of my brain is not going to flex and work. And that is really scary.”
  — James Walsh (22:19)

• On professors' despair and institutional rot:
  "It is very easy to spot when someone hasn't authored their own work. ... But knowing and proving are very different things."
  — Sean Illing (31:24)

• On the AI-powered future:
  "We're a long way from spell check."
  — Sean Illing (50:00)

• On the dangers of post-literacy:
  "I do not believe there's a model of liberal democracy that works in a post literate society."
  — Sean Illing (54:28)

Timestamps for Important Segments

• 01:03 — Opening question: What's the point of college if no one's actually doing the work?
• 03:30 — Why Walsh got into reporting on AI cheating
• 07:13 — Overview of AI tools and how students use them
• 09:37 — Computer science, AI use, and job market consequences
• 11:31 — Copy-pasting prompts, professors’ countermeasures
• 15:12 — Student perspectives: alarm, resignation, and normalization
• 17:25 — Roy Lee: the new transactional college model
• 20:03 — Wendy: the line between AI assistance and cheating
• 22:19 — Walsh's personal temptation and fear of cognitive atrophy
• 29:26 — Professor perspectives: from despair to adaptation
• 33:50 — Move to orals, blue books, and what is lost
• 34:28 — Faculty use of AI for materials and grading
• 37:54 — University administration and collective denial
• 46:26 — Walsh's reflection: Would he have become a writer if this existed?
• 48:08 — Illing: "Writing is thinking"
• 50:00 — Calculator-for-words vs. literacy
• 52:35 — Post-literate society fears and democracy
• 55:32 — AI’s effect on inequality

Conclusion & Takeaways

The normalization of AI-generated content is accelerating the transformation of higher education—from how students learn to how faculty teach and evaluate. The line between thinking and outsourcing is eroding, and both students and professors are scrambling to adapt. Whether this marks the start of a creative new era, the end of writing as foundational to thought, or simply a temporary moral panic remains to be seen. But the anxieties, contradictions, and existential questions aired here highlight how unprepared higher education—and perhaps society at large—is for the speed and depth of the AI revolution.