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Medical students who skip writing their own reflections are not lazy, they are surviving an irrational system. Kathleen Muldoon, a coach and professor, returns to discuss what student AI use in medical education actually reveals about the curriculum, the hidden incentives behind it, and why she calls students in instead of catching them. This episode is based on her article “Driving medical education reform through intellectual honesty,” published on KevinMD. You will hear why pass-fail courses inside graded curricula push students to put their energy elsewhere, why the hidden curriculum speaks louder than the syllabus, and what students disclosed when she asked them what was going on. You will learn what her workshops are designed to do that AI cannot, why she believes AI cannot teach empathy, and what a more humane medical education would actually require. Press play to find out why she thinks the next generation of clinicians is not the problem, and what the systems training them must change to produce humane physicians.

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Transcript

Kevin Pho: Hi, and welcome to the show. Subscribe at KevinMD.com/podcast. Today we welcome back Kathleen Muldoon, professor and medical educator. Today’s KevinMD article is “Driving medical education reform through intellectual honesty.” Kathleen, welcome back to the show.

Kathleen Muldoon: Thanks for having me.

Kevin Pho: All right. What’s your latest article about?

Kathleen Muldoon: The latest article came about because I have the honor and privilege of working with large groups of medical students, and I do so mainly through workshops that require courageous conversation about difficult topics. And the course that I’m teaching at the moment was Humanity in Medicine, which I have built a series of workshops where we look at and examine topics in medicine like bias and how it can impact care, but also just looking at data on disparities in medicine in various groups and our relationship to it and how we come to understand data.

And I purposely construct these workshops, when people come to them, to be as diverse as I can make them given what I know about the students so that they can learn the clinical skill that we can look at the same facts and derive different meaning from them. So the work is in the discussion.

And the evaluative component of the course is a reflection on that discussion. And I explicitly say, “No AI,” because I want to know what you think. I don’t care if you use bullet points. I don’t care if your grammar’s any good. It’s really just, what are you taking away from this conversation?

But I was seeing so much AI use, and I had this realization that I think is really relevant as I see people of my generation and a little bit older and clinicians talking about the next generation of doctors that we’re training and either calling them lazy or “kids these days” kinds of sentiment, and I don’t think that’s it.

And it’s not even that I’m anti-AI. It is a reflection on what rational decisions are our learners making inside of irrational systems. Right? And so, if students or trainees or anybody who’s in a position where they feel like they don’t have power notice that what is being incentivized is performance over engagement or over reflection, you know, the hidden curriculum is going to speak louder than the syllabus. And I think that’s an opportunity for us to think about what are we incentivizing in our learning environments. And so that’s why this article came together.

Kevin Pho: So in your workshops and when students have to write or reflect on some of these difficult conversations, you mentioned that so much AI is being used. So how are you sure that AI was being used? Because I know a lot of the tools that’s used to detect AI, they’re a little bit, you know, not 100 percent accurate. And how are you suspecting the students are using AI?

Kathleen Muldoon: You’re exactly right. Those detective systems are just not up to par. So I feel like my gut is, which I know sounds very unscientific. But as somebody who does a lot of writing and a lot of reading, I could see the phrases that have become very common with AI usage. The short sentences. There were a few that included emojis, you know. So some tell signs. And even the prompt in some cases.

But I think the real work was, you know, I had available to me the professionalism write-ups and failures and things like that, but I feel like it was more powerful in those moments to call some of those students in and say, you know, “I think this is what you’re doing, and I need to tell you, and I want you to believe me, that you are enough, and that what you think is enough, so tell me what’s going on.”

And I think in doing so, and meeting these students knowing that all of these students are coming to medicine to make it a better place, right? They’re paying their tuition. They’re delaying starting their families, starting their economic life, like, all of the things that these professional learners are doing.

So I know that something else is going on. I believe that in my soul, right? Because I do believe that, you know, medicine is a calling, right? And it is a gift that anybody who wants to come to this profession. And so in creating that space of psychological safety, it’s really important that a student can feel safe engaging with a conversation, and trust, just like we do in our clinical environments, I want to know what’s going on with you.

Can you tell me what’s going on? Because this is what I expect. This is what I hope. This is what my objective is. What is yours? Can I understand what’s going on with you? And so, without exception, I had really great conversations. I was able to model that space and so, you know, I always say you won’t know unless you ask, so I asked.

Kevin Pho: So what was the gestalt of those conversations in terms of, as a whole, what were some of the reasons that the students said they potentially use AI, and perhaps you could even speculate some of their motives behind that?

Kathleen Muldoon: So this class is a pass-fail class that is embedded within a graded system. And I think that automatically shifts students’ perceptions of, I would say value, but I don’t know that that’s what I mean. I think I mean, that our students are smart, and they will respond to the systems that are in front of them. And so, you know, given it is graded on a different level, I don’t think that diminishes its value.

But it does shift where you might think that you should put your energy if you don’t trust that you’re more than a number in a system that has a lot of benchmarks and, you know, cutoffs for qualifications that feel like gates to the life that you want to have. So I feel like the gestalt of the conversation was really trying to impress on my students that there is a human side of medicine, there is that soft skill, and that presence is going to matter for yourself to not burn out in these systems, but also for the person in front of you who is also not going to be want to be referred to as a number, who’s going to want to be understood.

And so this is a practice of dealing with your own emotions and your thoughts that come out of these conversations. I drew attention to the fact that a lot of clinicians these days use the narrative medicine skill of keeping a parallel chart where you can keep track of your own emotions, and this is starting to look at it.

So it’s worth the time. And again, just impressing on them, nobody expects a perfect doctor. I certainly don’t expect them to be perfect students when they’re in their training phase. And a present doctor is always more effective in all of the ways that you can measure it. And so why not start practicing that now?

Kevin Pho: Now, just from your conversations and from the student’s perspective, how much of their potential use of AI in your course was just them adapting to the incentives that the system created? You know, not to excuse academic dishonesty at all, but how much is it the system itself that rewards some of these metrics of success over the value of the course itself?

Kathleen Muldoon: I think it’s mostly in that area. I think that this is a systems-level problem, not a student-level problem. Number one, we’re all grappling with how to use AI, and again, I’m not anti-AI, but I am anti outsourcing your critical thinking and your professional identity formation to an algorithm. Because if for no other reason, it makes the students feel like they’re not good enough.

So, I do think it is the system. I think that all of us are grappling with when AI is appropriate and when it isn’t. None of us know how often it makes mistakes, more often than we think. And there may be times where, I mean, there are 100 percent times where it is more efficient, and even in this case, it’s more efficient to put in either the readings and saying something like, “Tell me what I thought about this,” you know, which would be an extreme example, or just putting in a series of thoughts and asking it to organize them, right?

And there is a gray area there, right? Is that cheating? Is it just cleaning it up? I did not grow up with AI. I did not form my own professional identity and my voice around it. And this is something that this generation is going to have to think about. I know a lot of people love AI scribes, you know, inputting notes and having something come back that’s very efficient and cost-effective.

I just really think that we, as educators, as people who construct the system, it is taking away that formative component where not everything has to be evaluative and that how will people learn if they don’t feel it’s safe to be themselves, to be authentic and to be unpolished? Because that’s how we are as human beings.

Kevin Pho: Now, as you reflect on that situation and as you continue to teach this course going forward, any changes that you would make with a new cohort of students?

Kathleen Muldoon: I’m thinking about it, right? How am I going to incorporate? I do think that writing is part of processing, so how do I create a. I see that burden being on me. Right? Like how do I create a psychologically safe system to know that they’re enough without, I think, resorting to, like it was at least in my day with the blue books and, you know, writing things out while you’re in class time. I think that the work of this workshop-based class, this discussion-based class, just like it is in clinics, is in the conversation.

So, I’m going to have to think about how that processing piece is incorporated. And it’s not that I’m trying to catch people. I think the work is how do I really think about just getting that message across that I want you to be real in this moment. So I mean, to my mind, I feel like there’s two extremes, either incorporating the writing piece into the workshop itself, or getting rid of it altogether, or fully embracing and incorporating AI and asking for honesty in the way that it is required for disclosure when it’s used in other intellectual environments.

Hopefully it comes to a point where the students themselves can certainly recognize the threat AI poses to their critical thinking because it is going to affect how, of course, they interact with patients later on, right?

Kevin Pho: So I could understand the predicament that you as a medical educator, and I’m sure medical educators across the country, they’re grappling with this similar problem, right? I do think that when you say the words safe space, I do think that is something that would resonate with students. But tell me what you think when you had these conversations with your students about their potential use of AI, what were some of their responses when confronted with their potential use?

Kathleen Muldoon: I had no pushback, defensiveness. And I think it was they disclosed the feeling of needing to survive a curriculum instead of thrive in it. And to me that means, you know, we as people who engage in clinical learning environments need to really think about what systems are we creating and what are we incentivizing, right?

How do we create. I mean, a student can’t learn unless they feel safe to learn, and they can’t do that if there’s not psychological safety, which includes the safety in being wrong, which includes the safety in saying, I made a mistake. I did something I shouldn’t have done. And in those conversations, I want to be clear, I have said I’m not, it is 100 percent not appropriate for you to be using AI, and I understand why you’re doing it.

Because this is something that in your perception is a thing you got to get through to get to the next thing you have to do on your to-do list, right? And critical thinking is hard, and putting yourself down on a piece of paper in terms of your own thoughts is hard, especially when the rest of your curriculum, the board examinations, they’re all multiple choice tests with one right answer.

And I’m asking them to engage in something that has not one right answer, which is actually real clinical medicine and real interactions with human beings. So, I do think that, you know, modeling repair and humility is really powerful. I hope that I did that in that moment. And what I’m asking for all of us to do in medicine is to think about how we can do that ourselves in creating a more humane system, because I think we do need to grapple with, as AI is pushing itself more and more into our practices and our learning environments and we want to, or we say we want to encourage critical thinking.

Well, how are we incentivizing that to be appropriate? How are we incentivizing it, you know, on grand rounds when we’re allowing students to ask us questions that might feel hard that we also need to be curious about, how do we teach humanity without reducing it to a competency checklist.

Kevin Pho: Now, you mentioned that conversations among medical educators need to happen in terms of making the system more humane. So not just in your institution specifically, but in general, are those hard conversations really happening currently?

Kathleen Muldoon: I think that people are interested in it. I’m not sure that people understand how to do it. I have had the opportunity to engage in conversations with different residency programs, with some medical schools that are just beginning and starting to construct their curriculum. And I think there’s an opportunity there to build something that probably might be easier than retrofitting these kinds of conversations into an already established curriculum.

But it’s not impossible, and I’m seeing it happen. I’m seeing, I just had a wonderful conversation at a new institution that’s opening up where part of the early curriculum is allowing students to formally think about their professional identity, to formally think about how am I incorporating rest and exercise and nutrition at the outset of learning the basic sciences, and how amazing is that? That these students are really going to think about “Look, I am a human in this system too, treating other humans,” and it’s sort of a palliative care model approaching to our learning environments, and I just think it’s really, really powerful.

And, you know, medicine has gone through, medical education has gone through periods of significant, like, reform. Starting with, you know, like the Flexner Report, but even, like within the last, like 100 years, like as we move from a lot of didactic teaching to flipped classrooms, to active learning, to allowing students to set their own learning objectives. There are some medical schools that have capstone projects and theses. There are a lot of ways to do it.

I think what we need to start and incorporate is what the students want and what they need, and how we see them on the other side, because this is a new generation grappling with a massive amount of knowledge that many of us didn’t have to learn when we went through our training. And so I think, you know, centering these conversations is really important to building something that is going to last us.

Kevin Pho: Now, as a medical educator and specific to your course, eventually these AI tools are going to get so sophisticated where you’re not going to be able to tell what’s AI-generated or not. So is there a role for AI specific to what you’re teaching? And if so, and how would you speculate that role to be if in fact there is a role for AI?

Kathleen Muldoon: I mean, there’s going to have to be, right? So you’re asking me a tough question, right in this moment. Like, you know, at this moment in time, I do not believe that artificial intelligence can teach empathy. And I think that only comes from understanding each other, right? From allowing someone to show up rough and raw and emotionally volatile, and being able to see underneath that to what is the core value here, right? Because that’s how our peers show up for each other on a rough day.

That’s how our patients show up to us on their worst days. And AI is not the tool to teach us how to deal with that. So, you know, just on the spot thinking about it, like maybe there is something where there’s an AI response, and then there’s a human response. And, you know, I’m very adamant that peers and medical trainees show up best when they’re showing up for each other and supporting each other.

And I have so much hope in the way that I see that peers both evaluate each other and, like, lift each other up and call each other in when they need to be. But also show up for each other and practice that gentle challenge, that moral courage that we’ve talked about before, pausing a conversation, asking a question. And AI can’t do that at this moment. So just off the top of my head, maybe there is some exercise to be developed in the context of a workshop where it’s like, you know, this is how I’m reacting. This is how a robot’s reacting or an algorithm, and what’s the difference here? But I don’t think that AI can replace that human connection at this moment in time.

Kevin Pho: We’re talking to Kathleen Muldoon, professor and medical educator. Today’s KevinMD article is “Driving medical education reform through intellectual honesty.” Kathleen, as always, let’s end with some take-home messages that you want to leave with the KevinMD audience.

Kathleen Muldoon: Well, this message is, I have two. One is for your student learners who are in this, who engage with your materials, like, keep doing it. Keep engaging with the KevinMD space. There’s so much here for you to learn. And as you’re learning it, just know that you are enough, and how you are showing up is enough and is what medicine needs. That’s what you’re learning to do.

And for people who are creating the learning environments, people like me, people like you, like clinicians, I think we really need to think about if we want courageous clinicians that are going to carry us through the next generation, take care of us, then we must create environments where humanity and honesty is survivable. I think we really need to think hard about that, how we’re doing it. And I think we need to consider whether. Well, I just encourage everyone to understand that we cannot build humane physicians in dehumanizing systems. So let’s step up to the challenge and consider what we’re doing in these environments.

Kevin Pho: Kathleen, as always, thank you so much for sharing your perspective and insight. Thanks again for coming back on the show.

Kathleen Muldoon: I appreciate you, Kevin.