Podcast Summary

Harvard Data Science Review Podcast
Episode: Learning With AI: What It Means for Students, Teachers, and Parents
Date: October 30, 2025
Host(s): Liberty Capito & Shelley Mae (Harvard Data Science Review)
Guests:

• Chad Dorsey (President & CEO, Concord Consortium)
• Victor Lee (Associate Professor, Graduate School of Education, Stanford University)

Episode Overview

This episode explores the rapidly expanding role of artificial intelligence (AI) in K-12 education. The hosts and expert guests delve into misconceptions about AI, its real impacts on teaching and learning, concerns about equity, and the responsibilities of students, teachers, and parents in this changing landscape. The conversation offers candid insights into both the opportunities and challenges brought by AI, aiming to envision a more equitable, human-centered educational future.

Key Discussion Points & Insights

Biggest Misconceptions About AI in K-12 Education

• Overestimating AI’s Intelligence and Autonomy

  • Victor Lee notes that people often believe "it's much more intelligent and borderline sentient than it actually is." (02:14)
  • The personification of AI leads to unrealistic expectations about its capabilities and risks.

• Cheating Epidemic—Fact or Fiction?

  • There’s widespread anxiety about AI fueling cheating, but the reality is multifaceted.
  • Victor highlights research showing that cheating is not a new phenomenon, and the presence of AI merely makes it more visible, not more prevalent. "Cheating levels are actually been quite high for a long time—60 to 80% of students in any given school... will have engaged in some sort of cheating behavior." (04:36)
  • Notably, teachers are surprisingly heavy users of AI tools, often more so than students.

"Surprise. Teachers are some of the heaviest users of the AI rather than the students."
— Victor Lee (02:37)

• AI as Monolithic
  • Chad Dorsey explains that AI isn't "one thing" but encompasses many layers and types of technology, each with their own possibilities and limitations. (03:03)

How AI is Actually Used in Schools

• Teachers as Innovators

  • Teachers use AI for planning lessons, generating new approaches, and handling administrative burden, freeing up time for more meaningful interactions.

• Students Using AI for Learning

  • AI offers students a tool for exploring ideas, brainstorming, and refining their work rather than just cutting corners.

"A lot of the things that students are doing are also genuine in their desire to try to learn... students are also creative in the ways that they can use things."
— Chad Dorsey (07:27)

• Changing Teacher-Student Interactions
  • AI enables teachers to spend less time correcting grammar and more time discussing ideas and higher-order thinking.

"She’s having more conversations about, like, what kinds of ideas they’re trying to formulate... That was something she was feeling very positive about."
— Victor Lee (09:16)

The Evolving Role of the Teacher

• From Deliverer of Knowledge to Facilitator of Skills

  • The future of teaching lies in guiding students to develop "habits of mind, ways of doing things" and critical practices that AI can’t replicate.
  • AI should be "human-led and directed" and only outsourced where feasible and safe (11:59).

• Trustworthy Information & Data Literacy

  • Teachers play a vital role in helping students evaluate the trustworthiness of information—crucial in the age of AI-fueled misinformation (13:04).

Teaching About AI and Data

• Data Science Literacy

  • There's a push to integrate data science into K–12 since AI is fundamentally fueled by data (15:35).
  • Students’ perceptions of "data" are often limited, so educators emphasize authentic experiences—for example, using Fitbit data to understand concepts like tendency and variation (20:13).

• Understanding Biases in AI

  • Essential for students to recognize that data (and AI built on it) reflects societal choices—and can carry biases (17:56, 24:53).

“LLMs are trained on the data in the world, on the Internet, which is reflective of biases, assumptions, et cetera that we have in there... They don’t separate factual from societal biases.”
— Chad Dorsey (24:53)

Equity and Access

• Gaps in Technology and Opportunity

  • Some schools have robust tech, while others lack basic internet.
  • AI could widen disparities if access remains unequal. For example, rural schools are more likely to have AI bans, which may disadvantage their students further (22:54).

• Potential for Reinforcing Bias

  • AI systems may inadvertently reinforce existing social and ethnic biases based on their training data.

“We want to watch out for automation bias... if you use a traditionally black sounding first name and ask for suggestions regarding behavior, it's very different and oftentimes much more aggressive.”
— Victor Lee (26:34)

Fostering Curiosity and Agency in an AI World

• Concerns About Curiosity and Creativity

  • There’s perennial "moral panic" around new technologies. Chad Dorsey references historical resistance to innovations like book indexes to draw parallels with current AI anxieties (28:53).

• Preserving Social and Developmental Aspects

  • Victor Lee warns about the risks of AI becoming a "social substitute," possibly undermining the social processes vital to deep learning. (30:00)

“I would most worry that we lose contact with that social quality of learning, which I think has developmental and relational implications.”
— Victor Lee (31:03)

Measurement and Parent Involvement

• Challenges Measuring Success

  • Existing metrics may fall short in capturing the true impact of AI on learning. “If AI is indeed changing the nature of knowledge work... existing measures we have are not going to be very useful.” (34:54)

• Role of Parents

  • Parents model attitudes and use of AI; children "see what you’re doing with AI yourself and...hear what you’re saying about AI" (37:55).
  • The ultimate educational goal should be preparing young people for happy, fulfilling lives with the capacity to solve problems and ask meaningful questions (39:55).

Final Reflections & Magic Wand Wishes

• Chad Dorsey's Wish

  • AI would “become invisible in the long run in a positive way...to enable us to engage with one another in the ways that we find most useful and interesting and to clear away the things that aren’t important for that” (42:05).

• Victor Lee's Wish

  • AI culture would stop overhyping the technology, reducing false promises and fostering more realistic expectations (43:27).

“I would make AI stop overhyping itself, which, to be fair, the AI itself is not doing. It's the culture around AI.”
— Victor Lee (43:27)

Notable Quotes & Memorable Moments (with Timestamps)

• On Cheating:
  “Cheating levels are actually been quite high for a long time—60 to 80% of students...will have engaged in some sort of cheating behavior.” — Victor Lee (04:36)

• On AI’s Role in Education:
  "Teachers are some of the most creative people on earth, and they know a good thing on their side when they see it." — Chad Dorsey (07:27)

• On Data and AI:
  “Data are the product of humans and human decisions, that they are created by humans for some particular purpose... Data can be applied systematically...” — Chad Dorsey (17:56)

• On Equity and Access:
  "AI could subtly reinforce biases...because it's trained on the data of the world, which reflects our own assumptions and biases." — Chad Dorsey (24:53)

• On Social Learning:
  "I would most worry that we lose contact with that social quality of learning, which I think has developmental and relational implications." — Victor Lee (31:03)

• On Parental Modeling:
  “Your kids see you and they see what you're doing with AI yourself and they hear what you're saying about AI when you talk about it at the dinner table. So if you show how you use AI and you use it with skepticism... I think that's a really huge thing.” — Victor Lee (37:55)

• Magic Wand Wishes:
  “I would hope that AI...becomes invisible in the long run in a positive way, and enables us to engage with one another in the ways that we find most useful and interesting.” — Chad Dorsey (42:05)
  “I would make AI stop overhyping itself...the hype has gotten way out of hand and it’s leading to sort of false promises and a little bit too much deference to technology that isn’t there yet.” — Victor Lee (43:27)

Timestamps for Important Segments

• [02:14] — Biggest misconception about AI in education
• [04:36] — "Cheating epidemic" and data-driven reality check
• [07:27] — How teachers and students actually use AI
• [09:16] — AI shifting classroom interactions
• [11:59] — The future of teaching with AI as a partner
• [15:35] — Teaching about AI and fundamental data literacy
• [20:13] — Integrating authentic data experiences in learning
• [22:54] — Equity, access, and AI
• [24:53] — AI and reinforcing societal biases
• [28:53] — Ensuring curiosity and creativity in an AI-rich world
• [31:03] — Risks of AI as a social substitute in learning
• [34:54] — How do we measure the impact of AI in education?
• [37:55] — The crucial modeling role of parents
• [42:05] — Magic wand: What do you wish AI could do?

Tone, Takeaways & Closing Thoughts

The episode is thoughtful, optimistic, and candid—from debunking simplistic narratives around AI to championing the ingenuity of teachers and advocating for strong parental modeling. Rather than alarmism, the guests emphasize nuanced consideration and human agency as AI becomes increasingly present in schools.

Takeaways:

• AI is neither a solution nor a scourge; its impact is multifaceted and context-dependent.
• Teachers and students use AI in creative, constructive ways—far beyond just cheating.
• Data literacy and understanding AI biases are essential for teachers and students alike.
• Real equity in AI access and application requires vigilance and collective investment.
• Parents play a foundational, often-underestimated role in shaping children’s attitudes toward new technologies.
• The metrics by which we judge educational “success” with AI may need radical revision.

Final Word:
AI in education is best envisioned not as a force that overtakes learning but as a tool “invisible in the long run in a positive way” (42:05) that empowers humans to do what we do best: think, question, create, and connect.