College Bound Mentor Podcast

Episode: "AI Did My Homework"
Guests: Dr. Lyra Stein, Dr. Nathalie Moon, Stephanie Silberstein
Date: June 18, 2025
Hosts: Lisa Bleich, Abby Power

Episode Overview

This episode dives deep into the role of AI—especially tools like ChatGPT—in the college classroom from the perspective of three experienced professors in psychology, statistics, and theater. The discussion centers on how students and faculty are using AI, the challenges and opportunities it brings, ethical concerns, and the future of learning and critical thinking in the AI era. The episode blends insight, practical examples, policy perspectives, and a candid look at where education goes from here.

Key Discussion Points and Insights

Prevalence and Evolution of AI Use Among Students

• Widespread Usage, Shifting Attitudes
  • Early on, students were reluctant to admit using AI, fearing it was considered cheating, but stigma is fading.
  • “I frequently survey my students … they're using it very frequently and they are somewhat hesitant to admit it because they think that it's considered cheating.” (Dr. Lyra Stein, 03:18)
  • AI is now students' go-to for a wide range of academic tasks—even when simpler resources like Google or Wikipedia might suffice.
  • “It's where they go first for so many questions, it's hard to convince them otherwise.” (Dr. Nathalie Moon, 05:22)
• AI as Ubiquitous Advice (“AI vs. Mentor”)
  • Example: A student's parent consults ChatGPT for her child's summer plans, contrasting its answer with that of a human mentor. (06:02)

Discipline-Specific Experiences and Strategies

• Humanities (Acting & Theater)
  • AI use is less about essay writing and more about supplementing or reflecting on creative assignments.
  • “Sometimes I'm reading the papers and I'm craving AI, like, oh, please run this through some sort of program…” (Stephanie Silberstein, 08:11)
  • There's value and danger: AI can help clarify ideas, but can also short-circuit genuine, personal reflection.
• Psychology & Social Sciences
  • Assignments now often require students to use AI and then critique its output, emphasizing critical evaluation.
  • “They have to work on critically evaluating the output … they'll be using [AI] after they graduate.” (Dr. Lyra Stein, 03:18; 11:12)
• Statistics
  • Students rely heavily, sometimes too heavily, on AI even for tasks where domain knowledge or static resources would work better.
  • Innovative classroom exercises using AI as a simulated “client” for students to practice consulting skills.
  • “They got super into it, they loved it … it can be incredibly useful as a safe space to develop those skills.” (Dr. Nathalie Moon, 16:25)

Impact on Critical Thinking and Learning

• Concerns About Over-reliance and Skill Development
  • Faculty worry AI becomes a crutch, impeding the internalization of foundational skills.
  • “It's hard to convince the student that it's important to do it on their own. I don't know that that's resonating with them.” (Dr. Nathalie Moon, 10:07)
  • Assignments now aim to ensure students compare their own thinking with AI outputs.
    • “They really have to think about the output, that they have to grapple with it.” (Dr. Lyra Stein, 11:12)
• New Approaches in Teaching
  • Some instructors redesign courses to emphasize application, group discussion, and critical analysis over rote memorization.
  • “I tell them at the beginning you won't have to memorize anything because out in the real world…you won't have to memorize.” (Dr. Lyra Stein, 32:04)

Ethical and Institutional Challenges

• Detection, Plagiarism, and Policy
  • Many universities ban submitting student work to AI-checkers, citing low accuracy and intellectual property concerns.
  • “We're not allowed to use it for grading…or to run student work through third party software to try and detect if they used AI…” (Dr. Nathalie Moon, 23:26)
  • Policies on AI use are instructor-dependent and sometimes confusing for students.
• Plagiarism Standards Are Evolving
  • Students are taught to cite AI when it substantially shapes their work.
  • “If you use it to generate ideas, that is when you need to cite it.” (Dr. Lyra Stein, 25:53)
  • Ethical and equity questions arise: Is AI worse than a private tutor, or just another tool? (Stephanie Silberstein, 26:54)

Psychological and Social Ramifications

• Attachment to AI
  • Some students admit to stronger connections with AI than with real people.
  • “Some of their friends would rather talk to ChatGPT than go out, meet people in person.” (Dr. Lyra Stein, 20:09)
• AI in Personal Life
  • AI as surrogate “co-parent” and advisor—blurred boundaries between tech assistance and human interaction. (Stephanie Silberstein, 21:33)

Faculty Adaptation and Division

• Varied Willingness to Adapt
  • Some professors embrace AI, redesigning classes, others resist or revert to in-class, pen-and-paper assessments.
  • “I assume they're all using it for everything.” (Dr. Lyra Stein, 40:10)
  • Active adaptation involves integrating AI critically, rather than trying to police its use.

Notable Quotes & Memorable Moments

• On Student Use and Transparency
  • “At this point, I assume they're all using it for everything.” (Dr. Lyra Stein, 00:05 & 40:10)
• On Teaching with AI in Mind
  • “You have to show me that you're thinking critically about the output. And I really think that's the future of what we need to teach students.” (Dr. Lyra Stein, 42:42)
• On AI Bias
  • “AI is very biased. As a psychologist...all of its output is biased to make me feel good about myself.” (Dr. Lyra Stein, 43:40)
• On AI and Authenticity
  • “But I hope that it's one of those visceral reactions you have where humanity, you know, can show through.” (Stephanie Silberstein, 37:16)
• On Motivation and Relationships
  • “That professor was able to align [students’] motivation in the direction that I think is productive for them.” (Dr. Nathalie Moon, 30:09)
• On AI’s Nature
  • "But they're not people. We talk to them, we interact with them as if they're people…But these are probabilistic models, they're not deterministic." (Dr. Nathalie Moon, 47:00)
• On the Future of Teaching
  • “I have found life is much easier when I don't try to detect that they're using it...I want to simulate what you need to know in the workplace place, which is communication, critical thinking.” (Dr. Lyra Stein, 41:00)
• On AI’s Limitations
  • “ChatGPT will lie to you...it'll gaslight you.” (Abby Power, 49:13)
• On Equity
  • “They can all use it as a tutor and they all use the free version. So there's no inequity in terms of being able to hire a tutor or not.” (Dr. Lyra Stein, 28:30)

Timestamps for Important Segments

• 03:18 – 06:49: Professors discuss firsthand experiences and shifting student attitudes toward classroom AI.
• 06:49 – 08:57: Humanities perspective; wrestling with benefits and risks of AI in creative disciplines.
• 09:24 – 11:12: AI as crutch vs. skill-building; instructors’ concerns about critical thinking.
• 11:12 – 12:49: Assignment design to force direct comparison and critique of AI outputs.
• 14:54 – 17:38: Using AI for classroom simulation; "AI as client" consulting exercise example.
• 23:26 – 25:53: Institutional policies on AI-checkers and handling plagiarism in the AI age.
• 32:04 – 33:24: Course redesigns, group work, peer policing, and new grading mechanisms.
• 37:40 – 41:12: Detecting authentic student voice amid widespread AI use; evolving teaching strategies.
• 43:40 – 50:00: Myths, truths, and practical realities about AI bias, capabilities, and limits.

Engaging and Fluid Episode Takeaways

• AI Is Here to Stay: Professors are rapidly adapting to a new academic normal: AI is everywhere and policing it is less effective than embracing it thoughtfully.
• Critical Thinking is Crucial: The new skillset is not suppression of AI, but learning to critically analyze, supplement, and sometimes refute its outputs.
• Policy and Practice Lag: Universities are still catching up, with inconsistent policies and often unreliable detection methods for AI-generated work.
• Equity and Authenticity: AI is democratizing certain academic supports but raises new questions about equity, authenticity, and the very definition of plagiarism.
• Human Connection Still Matters: Despite AI’s impressive capabilities, real human motivation and relationships—between teachers and students, between peers—are the best catalysts for authentic learning.
• Future-Proofing Students: The most valuable graduates will be those who can use AI as a tool but also provide what AI can’t: independent thought, creativity, judgment, and effective collaboration.
• Rapid Change and Uncertainty: Both educators and students face an uncertain, fast-changing landscape—but open, ongoing dialogue is the best path forward.

Final Thoughts

The episode closes with a sense of cautious optimism. Professors and students alike are in the midst of a transition—navigating anxiety, exploring new practices, and working to define what learning and intellectual integrity mean in the AI era. The panel encourages educators not to stick their heads in the sand, but to actively engage with both the promise and the perils of AI, shaping education for the better wherever possible.

Recommended segment for newcomers:
Listen from [16:25] for a creative example of using AI to simulate real-world communication skills in the classroom.

Most quotable moment:
"At this point, I assume they're all using it for everything." — Dr. Lyra Stein ([00:05] & [40:10])