Latest / Azadeh and Guy on AI / AI Adoption in Higher Ed

Transcript

AI Adoption in Higher Ed · Azadeh and Guy on AI

• 0:00
  SPEAKER_01: Hello everyone and welcome to Azadeh and Guy on AI.
• 0:05
  SPEAKER_00: And I've got some news.
• 0:08
  SPEAKER_01: Okay, yeah.
• 0:09
  SPEAKER_00: We're almost at the end of Season 3.
• 0:12
  SPEAKER_01: Oh my gosh, yes.
• 0:13
  SPEAKER_01: Yes, I know.
• 0:15
  SPEAKER_00: But we promised that we will be back.
• 0:17
  SPEAKER_00: So we have this week and we will finish this season.
• 0:22
  SPEAKER_00: And then we will start around mid-September with Season 3.
• 0:27
  SPEAKER_01: On AI.
• 0:30
  SPEAKER_00: What will we do when Azadeh leaves?
• 0:32
  SPEAKER_00: She will have to still come back electronically because this is forever.
• 0:37
  SPEAKER_00: Anyway, I don't know if it's good news or bad news, but we all need a break.
• 0:42
  SPEAKER_00: We're going to take a few weeks break, plan the next season.
• 0:45
  SPEAKER_00: We've got some exciting things that we're thinking about, but today we're doing something else.
• 0:51
  SPEAKER_01: Yeah, yeah.
• 0:52
  SPEAKER_01: And I think today you have some news about one of the conferences or huge meetings
• 0:58
  SPEAKER_01: that you attended.
• 0:59
  SPEAKER_00: Well, it was not huge.
• 1:01
  SPEAKER_00: It was moderately sized.
• 1:02
  SPEAKER_00: No.
• 1:03
  SPEAKER_00: I went to the Google Education series for higher education,
• 1:09
  SPEAKER_00: so they decided to hold sessions for higher education.
• 1:13
  SPEAKER_00: There were a number of them in California, in New York.
• 1:16
  SPEAKER_00: I went to the one in Chicago because it's close by.
• 1:18
  SPEAKER_00: And it was also the right date for me.
• 1:21
  SPEAKER_00: And so I spent a couple of days in Chicago talking to other educators from higher education.
• 1:28
  SPEAKER_00: I expected to have more people from teacher education,
• 1:32
  SPEAKER_00: but actually people were from all over, which is fantastic.
• 1:35
  SPEAKER_01: You mean from different disciplines?
• 1:37
  SPEAKER_00: Yes, completely.
• 1:38
  SPEAKER_00: So we had computer science,
• 1:40
  SPEAKER_00: we had quite a few people from law schools, instructional designers, CTOs.
• 1:50
  SPEAKER_00: So people from all kinds of walks,
• 1:52
  SPEAKER_00: people in administration, faculty members, instructors, instructors.
• 1:58
  SPEAKER_00: So a lot of people which made for very rich conversations
• 2:04
  SPEAKER_00: and really recognizing some of the cross-cutting
• 2:11
  SPEAKER_00: elements that AI is presenting all
• 2:14
  SPEAKER_00: of us and sharing solutions and where we're at and all of that.
• 2:17
  SPEAKER_00: So that was fantastic.
• 2:19
  SPEAKER_00: And the special thing about this series is this is a series that was started by Google and
• 2:27
  SPEAKER_00: With collaboration with ISTE,
• 2:29
  SPEAKER_00: which is the International Society for Transformative Education,
• 2:34
  SPEAKER_00: used to be Technology in Education,
• 2:36
  SPEAKER_00: now it's transformative,
• 2:37
  SPEAKER_00: they changed their name,
• 2:39
  SPEAKER_00: they incorporated another organization, what used to be ASCD.
• 2:45
  SPEAKER_00: And so they've been very, very thoughtful.
• 2:48
  SPEAKER_00: And it's probably the best professional learning about AI that I've been to.
• 2:54
  SPEAKER_00: And I try to go to a lot of webinars, a lot of opportunities.
• 2:58
  SPEAKER_00: This is the one where I feel like I got the most.
• 3:02
  SPEAKER_00: And I'm speaking for my position where I live in this weird position where in
• 3:08
  SPEAKER_00: the institution I'm doing a lot of work on AI.
• 3:11
  SPEAKER_00: But we as an institution...
• 3:14
  SPEAKER_00: Have not moved very much in a cohesive, coherent manner.
• 3:18
  SPEAKER_00: So there's tremendous effort in the College of Engineering,
• 3:21
  SPEAKER_00: in the Prairie AI,
• 3:23
  SPEAKER_00: We're leading some things here in the College of Education and Human Sciences.
• 3:27
  SPEAKER_00: There's sporadic work across campus, but there isn't a campus-wide effort.
• 3:34
  SPEAKER_00: And when I say campus-wide, I'm not talking about AI, because people are talking all the time.
• 3:40
  SPEAKER_00: I've been on panels for years now.
• 3:45
  SPEAKER_00: And so we're talking and people are coming and listening.
• 3:48
  SPEAKER_00: I'm talking about commitment.
• 3:51
  SPEAKER_00: And when a campus commits to something,
• 3:53
  SPEAKER_00: one of the expectations is to actually put resources behind it and not just to talk
• 3:59
  SPEAKER_00: about it.
• 3:59
  SPEAKER_00: Because it's easy to say something like the president of our university said,
• 4:04
  SPEAKER_00: all courses within a year or so will have something about AI in them.
• 4:11
  SPEAKER_00: But if you're not putting resources behind it, Both in money or in people or in time.
• 4:18
  SPEAKER_00: You can do this a few ways.
• 4:20
  SPEAKER_00: But if it's just a declaration, that means, that signals to me as a faculty member...
• 4:26
  SPEAKER_00: That this is not important enough for you to go and seek those extra resources
• 4:32
  SPEAKER_00: that it would take to do it at an institutional or even cross-institutional level.
• 4:39
  SPEAKER_00: So that's how I think about it.
• 4:40
  SPEAKER_00: People can correct me.
• 4:41
  SPEAKER_00: People can say, well, people can do it on their own.
• 4:44
  SPEAKER_00: Yes.
• 4:44
  SPEAKER_00: But also recognizing that both graduate students and faculty members
• 4:48
  SPEAKER_00: and staff members have full-time jobs.
• 4:51
  SPEAKER_01: Yeah.
• 4:52
  SPEAKER_00: And so what we're asking them to do is something that is extra,
• 4:56
  SPEAKER_00: at least in the beginning,
• 4:58
  SPEAKER_00: Because doing something that is unfamiliar requires extra resources.
• 5:02
  SPEAKER_00: Now, some people will go after it because they love, like me.
• 5:05
  SPEAKER_00: I love playing with AI.
• 5:06
  SPEAKER_00: For me, that is a leisure activity almost.
• 5:10
  SPEAKER_00: But I can't expect everybody to think that way.
• 5:12
  SPEAKER_00: I think it's unfair and it's not very professional.
• 5:17
  SPEAKER_00: So it is about resources.
• 5:18
  SPEAKER_00: So we have some islands of excellence and islands of a lot of activity and then
• 5:24
  SPEAKER_00: a lot of people who are not sure what to do about it.
• 5:28
  SPEAKER_00: And again, I can't expect everybody to go and listen to a daily podcast about AI.
• 5:32
  SPEAKER_00: This is not where they are.
• 5:33
  SPEAKER_00: They might not be listening to this podcast, which is their loss.
• 5:38
  SPEAKER_01: I mean, let's be honest.
• 5:41
  SPEAKER_00: But it is,
• 5:43
  SPEAKER_00: you know,
• 5:43
  SPEAKER_00: they have the things they're interested in and the things that get them excited.
• 5:47
  SPEAKER_00: And AI is not one of them, which is perfectly fine.
• 5:50
  SPEAKER_00: It's still a reality that we have to deal with.
• 5:52
  SPEAKER_00: And to deal with it, we need some resources.
• 5:54
  SPEAKER_00: Anyway.
• 5:55
  SPEAKER_01: Yeah.
• 5:55
  SPEAKER_00: I'm off my soapbox at least for a second.
• 5:58
  SPEAKER_00: So you wanted to ask me some questions about this.
• 6:00
  SPEAKER_00: So what were you curious about?
• 6:02
  SPEAKER_01: So thinking about that series, AI Educator series, so what do you think?
• 6:08
  SPEAKER_01: What inspired Google to launch that series at this moment in education?
• 6:13
  SPEAKER_00: Well, I think that, I mean, you know, I always think that what inspires them is money.
• 6:20
  SPEAKER_00: I mean, at the end of the day.
• 6:22
  SPEAKER_00: But I think that Google has been very active in education in general.
• 6:30
  SPEAKER_00: They entered the education market with Chromebooks and then with Google Classroom
• 6:35
  SPEAKER_00: and with other products.
• 6:37
  SPEAKER_00: And some of them are fantastic products.
• 6:39
  SPEAKER_00: Notebook LM, now it's called Gemini Notebook or something like that.
• 6:43
  SPEAKER_00: They keep changing names of things.
• 6:45
  SPEAKER_00: Also, maybe not the best policy, but whatever.
• 6:50
  SPEAKER_00: They have,
• 6:51
  SPEAKER_00: throughout the last 20 years,
• 6:54
  SPEAKER_00: really have taken a significant look into education and thought,
• 6:59
  SPEAKER_00: this is a space we want to be in.
• 7:00
  SPEAKER_00: And if we want to play in this space,
• 7:04
  SPEAKER_00: we need to do a responsible job and we need to be attentive to the clients,
• 7:08
  SPEAKER_00: namely K-12 schools,
• 7:10
  SPEAKER_00: because that's where most of their, originally, most of their clients were.
• 7:15
  SPEAKER_00: And later also to higher education because higher education is not another business
• 7:22
  SPEAKER_00: that you need to cater to like you do a business.
• 7:25
  SPEAKER_00: But this is a very specific industry with very specific concerns and legal obligations.
• 7:31
  SPEAKER_00: For example,
• 7:32
  SPEAKER_00: FERPA and all of the rules around student privacy,
• 7:36
  SPEAKER_00: student data and all of that requires a different treatment Then companies,
• 7:40
  SPEAKER_00: companies want to protect their data sometimes because of privacy,
• 7:44
  SPEAKER_00: often just because they want to protect their business.
• 7:46
  SPEAKER_00: We have to protect every student's identity
• 7:51
  SPEAKER_00: and we have very high restrictions around breaches that actually puts us
• 7:57
  SPEAKER_00: in violation of the law.
• 7:59
  SPEAKER_00: So if a small company has a website and somebody breached it,
• 8:02
  SPEAKER_00: they have an obligation to report to To their clients.
• 8:08
  SPEAKER_00: But if they haven't done anything, they haven't broken the law.
• 8:11
  SPEAKER_00: But if somebody breaks into university data, then the law has been broken.
• 8:17
  SPEAKER_00: So there are other concerns here that have to be answered.
• 8:21
  SPEAKER_00: And of course,
• 8:25
  SPEAKER_00: intellectual property and all of these things are also a concern for scientists,
• 8:30
  SPEAKER_00: for scientists.
• 8:31
  SPEAKER_00: Anybody that's writing all of these things.
• 8:34
  SPEAKER_00: So these are different concerns and they've realized,
• 8:36
  SPEAKER_00: I think,
• 8:37
  SPEAKER_00: that they didn't have the capacity to deliver the same thing that they deliver
• 8:41
  SPEAKER_00: with businesses to varying degrees.
• 8:43
  SPEAKER_00: I don't know even how successful they are there.
• 8:45
  SPEAKER_00: I'm not in the business community.
• 8:48
  SPEAKER_00: But I think they realized this is different and we need to do this differently
• 8:51
  SPEAKER_00: and we need to do this with educators in the room,
• 8:54
  SPEAKER_00: creating the So for the first time,
• 8:56
  SPEAKER_00: I felt like they were listening and they were crafting things
• 8:59
  SPEAKER_00: that were actually useful for the institutions.
• 9:15
  SPEAKER_01: Another thing that I was thinking about is
• 9:17
  SPEAKER_01: that Google has created Google higher ed faculty groups.
• 9:21
  SPEAKER_00: Yes.
• 9:21
  SPEAKER_01: So what gap do you see in faculty professional learning that these communities aim to fill?
• 9:28
  SPEAKER_00: Well, I'm not speaking for Google.
• 9:31
  SPEAKER_00: This is my perspective, right?
• 9:33
  SPEAKER_00: I don't want to say I speak for Google because I don't.
• 9:35
  SPEAKER_00: If they pay me enough, maybe better.
• 9:38
  SPEAKER_00: I'm not speaking for Google,
• 9:40
  SPEAKER_00: but from my perspective,
• 9:41
  SPEAKER_00: what they're trying to do is encourage conversations across institutions so
• 9:46
  SPEAKER_00: that people,
• 9:47
  SPEAKER_00: especially singletons,
• 9:50
  SPEAKER_00: and we know that from K-12 education, especially in Absolutely, yeah.
• 10:15
  SPEAKER_00: And so it can serve in two ways.
• 10:18
  SPEAKER_00: It can serve when you have a few innovators in many institutions,
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  SPEAKER_00: and the United States has literally thousands of higher ed institutions,
• 10:28
  SPEAKER_00: but there might be only two or three people
• 10:30
  SPEAKER_00: that are really championing AI there,
• 10:32
  SPEAKER_00: they need somebody to talk to who's also championing AI
• 10:35
  SPEAKER_00: and also getting this response from colleagues that says,
• 10:41
  SPEAKER_00: not for me, or you are evil if you're doing this.
• 10:45
  SPEAKER_00: These are all of the responses that people have.
• 10:48
  SPEAKER_00: And so this is a place to have community and to really share best practices.
• 10:52
  SPEAKER_00: The second thing is that, again,
• 10:54
  SPEAKER_00: if you're in the smaller institutions and there's only one of you,
• 10:58
  SPEAKER_00: this is again a way to get something that is more discipline specific
• 11:03
  SPEAKER_00: because we've just been writing about AI in the word language space.
• 11:07
  SPEAKER_00: That's why I mentioned word language teachers, right?
• 11:12
  SPEAKER_00: That pedagogy has specific opportunities with AI, but also specific challenges, right?
• 11:19
  SPEAKER_00: Anybody can go home and do their whole homework with AI.
• 11:24
  SPEAKER_00: It's not productive,
• 11:26
  SPEAKER_00: but it's not beyond the realm of possibility to think that students,
• 11:29
  SPEAKER_00: undergraduates or in high school would do that easily, right?
• 11:33
  SPEAKER_00: So you have to think about, okay, what do I do with that?
• 11:35
  SPEAKER_00: On the other hand,
• 11:36
  SPEAKER_00: Character AI and all of these other things develop chatbots
• 11:40
  SPEAKER_00: where people can practice speaking a different language.
• 11:43
  SPEAKER_00: That's highly effective.
• 11:44
  SPEAKER_00: Again, this is specific to the discipline.
• 11:47
  SPEAKER_00: So there's just all of these things entering and you want to have these conversations.
• 11:53
  SPEAKER_00: And for me, that's where the contribution is to these groups.
• 11:58
  SPEAKER_00: Now, the problem is we are all busy people.
• 12:02
  SPEAKER_00: I keep going back to it.
• 12:03
  SPEAKER_00: So the question for me is how active these groups actually are
• 12:09
  SPEAKER_00: the day-to-day craziness of teaching and budget pressures and committee meetings
• 12:16
  SPEAKER_00: and students and office hours and everything else.
• 12:20
  SPEAKER_00: So that remains to see it as to how effective they are.
• 12:24
  SPEAKER_01: Yeah, yeah.
• 12:25
  SPEAKER_01: The other thing is that when they are talking about their initiative
• 12:29
  SPEAKER_01: on their website, there's a phrase that is AI-enabled curriculum design.
• 12:35
  SPEAKER_01: So how should faculty rethink course design or syllabus or curriculum design in
• 12:41
  SPEAKER_01: an era when students have AI chatbots or AI as 24-7 assistants by their side?
• 12:53
  SPEAKER_00: I want to take a step back and say they really thought about starting with
• 13:00
  SPEAKER_00: where are you in the process and how much campus-wide work there is.
• 13:07
  SPEAKER_01: Do you mean AI policies?
• 13:11
  SPEAKER_00: Not just policies, but actual action.
• 13:13
  SPEAKER_00: Not just policies.
• 13:14
  SPEAKER_00: AI policies, everybody's got an AI policy.
• 13:17
  SPEAKER_00: Our policy is that you should have an AI policy.
• 13:21
  SPEAKER_01: And we're not
• 13:21
  SPEAKER_00: the only one.
• 13:23
  SPEAKER_00: And it's something I actually wrote about in the Substack,
• 13:27
  SPEAKER_00: so if you haven't checked that out, about K12, I wrote the same thing.
• 13:31
  SPEAKER_00: What they're doing right now is what K12 are doing,
• 13:35
  SPEAKER_00: and they're saying, well,
• 13:36
  SPEAKER_00: you should not cheat,
• 13:37
  SPEAKER_00: and you should use it carefully,
• 13:40
  SPEAKER_00: and you should protect privacy, and also the teacher will tell you what to do.
• 13:43
  SPEAKER_00: Yeah.
• 13:44
  SPEAKER_00: And so in some ways, it's great because me as a teacher, I want maximum flexibility.
• 13:48
  SPEAKER_00: But on the other hand, that's for me as somebody who thinks about AI every day when I wake up.
• 13:54
  SPEAKER_00: I probably dream about AI, but I don't remember.
• 13:59
  SPEAKER_00: And so I think about this all the time.
• 14:01
  SPEAKER_00: So for me, yeah,
• 14:02
  SPEAKER_00: I have policies on my mind and I put a different policy on every assignment
• 14:07
  SPEAKER_00: because I think that's important.
• 14:08
  SPEAKER_00: And that's actually the recommendation that came from them as well.
• 14:11
  SPEAKER_00: But at the same time, I do recognize that not everybody's like that.
• 14:15
  SPEAKER_00: And they need help because it is so overwhelming.
• 14:19
  SPEAKER_00: So we did some exercises around that.
• 14:21
  SPEAKER_00: And for example, you can...
• 14:25
  SPEAKER_00: And I think about it from technology adoption for the TAM model,
• 14:31
  SPEAKER_00: which we used in a number of our studies and other people have used to look at it.
• 14:35
  SPEAKER_00: And what works repeatedly is the perceived usefulness.
• 14:39
  SPEAKER_00: That is, it's got to do something for you, for you to adopt it.
• 14:45
  SPEAKER_00: One of the things that we're seeing is give people a few things that they think is useful.
• 14:50
  SPEAKER_00: And we got a few really nice examples,
• 14:53
  SPEAKER_00: a few gems and a few just prompts that helped, for example, look at a
• 15:02
  SPEAKER_00: Just choose an assignment and look at it.
• 15:04
  SPEAKER_00: And so I chose an assignment and looked at it and used that gem.
• 15:07
  SPEAKER_00: And it said, here's what your stated goals are.
• 15:11
  SPEAKER_00: And here are the things that you haven't thought about
• 15:13
  SPEAKER_00: that you're making your students do that you may want to rethink because...
• 15:18
  SPEAKER_00: You needed something in between this part of the assignment and that part of the assignment.
• 15:23
  SPEAKER_00: And he did that analysis like that.
• 15:24
  SPEAKER_00: You know how AI works.
• 15:27
  SPEAKER_00: And suddenly I went, huh, you're right.
• 15:30
  SPEAKER_00: This is a problem for me.
• 15:31
  SPEAKER_00: And I haven't fully noticed that.
• 15:33
  SPEAKER_00: Or maybe I kind of noticed that, but kind of didn't do anything about it.
• 15:38
  SPEAKER_00: And it had, and so I continued that conversation, and AI suggested the solution.
• 15:42
  SPEAKER_00: So even before, what do you do with students?
• 15:45
  SPEAKER_00: It was, what do you do with your own work that can improve the things you're doing?
• 15:49
  SPEAKER_00: Especially in looking at the summit and things like that,
• 15:53
  SPEAKER_00: that We get that feedback from students.
• 15:56
  SPEAKER_00: I'm not sure what you mean by and all of that.
• 15:59
  SPEAKER_00: Here's an opportunity for AI to work through it and say,
• 16:02
  SPEAKER_00: here's how you can scaffold some of this in a productive way.
• 16:05
  SPEAKER_00: And sometimes you say, no, I want them to have a hard time because this is the point.
• 16:10
  SPEAKER_00: So that's fine.
• 16:11
  SPEAKER_00: That's a given pool.
• 16:12
  SPEAKER_00: And AI will push back more.
• 16:16
  SPEAKER_00: So that's one.
• 16:18
  SPEAKER_00: Their biggest recommendation that came out,
• 16:20
  SPEAKER_00: which is the recommendation we often make coming out also of the paper you wrote
• 16:24
  SPEAKER_00: with Dr.
• 16:26
  SPEAKER_00: Olmanson and all of these things, and that is it's really assignment-specific.
• 16:31
  SPEAKER_00: That is,
• 16:31
  SPEAKER_00: what is the goal of the assignment and how can AI take offload some of
• 16:36
  SPEAKER_00: the extraneous cognitive load but leave the main thing?
• 16:41
  SPEAKER_01: And we saw the same thing,
• 16:43
  SPEAKER_01: the same pattern with the research that we are doing in the College of Engineering,
• 16:47
  SPEAKER_01: React eProject.
• 16:48
  SPEAKER_01: It really depends on the assignment and how low stakes or high stakes they are.
• 16:54
  SPEAKER_00: How low stakes and high stakes.
• 16:55
  SPEAKER_00: And also, what is the point of the assignment?
• 16:57
  SPEAKER_00: If the point of the assignment is to see if you can write on your own
• 17:01
  SPEAKER_00: a basic program in Python to prove basic proficiency, then the answer is no AI.
• 17:08
  SPEAKER_00: But if the question is,
• 17:09
  SPEAKER_00: how can you do architecture of large projects,
• 17:13
  SPEAKER_00: then the specific coding of a specific subroutine is not that important.
• 17:18
  SPEAKER_00: And so you're saying, that can be AI, but the architecture has to be you.
• 17:24
  SPEAKER_00: We have to think about what it is.
• 17:27
  SPEAKER_00: So that came out of that.
• 17:30
  SPEAKER_00: It's always useful to see there was one test case out of one university
• 17:35
  SPEAKER_00: that was highlighted,
• 17:36
  SPEAKER_00: that talked about their process,
• 17:38
  SPEAKER_00: their attention,
• 17:39
  SPEAKER_00: the wrong turns they made and where they're at, which was extremely useful.
• 17:43
  SPEAKER_00: There were a lot of representatives from that institution, so that was useful.
• 17:48
  SPEAKER_00: And lots of different prompts,
• 17:51
  SPEAKER_00: group work and individual work that helped develop and see benefit.
• 17:55
  SPEAKER_00: And I use AI every day and I learned a few new things and got a few new prompts
• 18:00
  SPEAKER_00: and I'm like, that is a good one.
• 18:03
  SPEAKER_00: And so I've had a few conversations and I've had training with Gemini before
• 18:06
  SPEAKER_00: that I hated and I thought was useless.
• 18:10
  SPEAKER_00: And now after having this,
• 18:12
  SPEAKER_00: I'm reconsidering Gemini as a good partner in teaching and in learning.
• 18:18
  SPEAKER_00: Not necessarily my best choice for a frontline model
• 18:24
  SPEAKER_00: that solves my more complex problems in research,
• 18:27
  SPEAKER_00: but it does do fantastic things in my day-to-day teaching and learning.
• 18:32
  SPEAKER_01: Perfect.
• 18:33
  SPEAKER_01: Can I ask one more question?
• 18:35
  SPEAKER_00: Yeah, one more question because we're running out of time.
• 18:38
  SPEAKER_01: So I imagine that you had a lot of conversation with different faculty members.
• 18:42
  SPEAKER_01: Yes.
• 18:43
  SPEAKER_01: So many faculty members right now, they are curious but hesitant about AI.
• 18:48
  SPEAKER_01: What concerns did you hear most often?
• 18:51
  SPEAKER_00: I mean, people are concerned about learning and offloading learning.
• 18:54
  SPEAKER_00: That's the number one concern that most instructors have.
• 18:57
  SPEAKER_01: Have you noticed any change in the patterns of concerns compared to when AI emerged
• 19:03
  SPEAKER_01: or earlier stages of AI adoption?
• 19:05
  SPEAKER_00: So, I need to be careful.
• 19:07
  SPEAKER_01: Yeah.
• 19:08
  SPEAKER_00: Because this was a self-selected group.
• 19:11
  SPEAKER_00: These are the people who chose to take two days out of the vacation and go to Chicago.
• 19:19
  SPEAKER_01: That's a good question.
• 19:20
  SPEAKER_00: And be fed really, really well by Google.
• 19:22
  SPEAKER_00: They emphasize the food, so I got to give them props on that.
• 19:25
  SPEAKER_00: Too much food.
• 19:28
  SPEAKER_00: So these are obviously people who are more interested than the average.
• 19:31
  SPEAKER_00: So I don't think I can talk about this in a longitudinal way.
• 19:35
  SPEAKER_00: Inside our department, in the conversation I've had over the summer, I did see a change.
• 19:40
  SPEAKER_00: So if you think about this as a three-group problem, right?
• 19:44
  SPEAKER_00: We have the...
• 19:47
  SPEAKER_00: The omnivores or carnivores,
• 19:49
  SPEAKER_00: however you want to call them,
• 19:50
  SPEAKER_00: that are going after it,
• 19:52
  SPEAKER_00: that are interested,
• 19:55
  SPEAKER_00: are exploring, are listening to our podcast, are doing everything that they can.
• 20:00
  SPEAKER_00: Good for them.
• 20:00
  SPEAKER_00: They're going to be ahead of everybody.
• 20:02
  SPEAKER_00: Then you've got the group of people who are actively resisting, and that's a group that's
• 20:11
  SPEAKER_00: That's hard to deal with and we're not ready for them yet.
• 20:13
  SPEAKER_00: And that's perfectly fine.
• 20:15
  SPEAKER_00: And then there's a group that's on the fence.
• 20:17
  SPEAKER_00: And they need to see that it's actually changing something in their everyday life
• 20:21
  SPEAKER_00: before they commit to it.
• 20:22
  SPEAKER_00: They know it's serious.
• 20:23
  SPEAKER_00: They know they need to do something.
• 20:25
  SPEAKER_00: But they're either overwhelmed by just the enormity of the task
• 20:29
  SPEAKER_00: or they just don't know where to start.
• 20:32
  SPEAKER_00: And so that is the group that I start seeing coming to the table and saying,
• 20:37
  SPEAKER_00: hey, teach me something.
• 20:38
  SPEAKER_00: Show me how to do something.
• 20:40
  SPEAKER_00: Show me how it can help.
• 20:41
  SPEAKER_00: I can see that it's really working for you.
• 20:43
  SPEAKER_00: I want to learn a little bit.
• 20:45
  SPEAKER_00: So that's the shift I'm saying in that middle group.
• 20:47
  SPEAKER_00: The people who resist, and I appreciate all the reasons they resist.
• 20:50
  SPEAKER_00: Some of them are very valid and some of them less so.
• 20:55
  SPEAKER_00: But All of these questions are very, very serious.
• 20:59
  SPEAKER_00: And so I think that the task in the next coming year is really to move the people
• 21:04
  SPEAKER_00: who are in that group,
• 21:05
  SPEAKER_00: who are hesitant and don't know where to start,
• 21:07
  SPEAKER_00: to show them a few things that can be super helpful.
• 21:10
  SPEAKER_00: And then once they see its usefulness, we will probably be able to move forward on that.
• 21:17
  SPEAKER_00: And with other people,
• 21:19
  SPEAKER_00: you know,
• 21:19
  SPEAKER_00: it'll take the time that it takes unless the institution,
• 21:22
  SPEAKER_00: again, I'm doing it as a faculty member.
• 21:24
  SPEAKER_00: So...
• 21:26
  SPEAKER_00: I have very limited capacity.
• 21:28
  SPEAKER_00: Not just capacity,
• 21:29
  SPEAKER_00: but also without backing, people can choose to participate or not participate.
• 21:34
  SPEAKER_00: And if they're actively resisting,
• 21:36
  SPEAKER_00: they're choosing not to participate, which again, is their right.
• 21:39
  SPEAKER_00: They have a full-time job.
• 21:40
  SPEAKER_00: I completely understand.
• 21:42
  SPEAKER_00: But if you're talking about where is the shift,
• 21:44
  SPEAKER_00: the shift is in that middle group that is probably the largest group that's saying,
• 21:48
  SPEAKER_00: great.
• 21:49
  SPEAKER_00: What do I do?
• 21:50
  SPEAKER_00: Where do I start?
• 21:51
  SPEAKER_00: What is a way that I can use this or think about this in
• 21:54
  SPEAKER_00: a way that's not overwhelming or does not require me to rewrite my whole class?
• 22:00
  SPEAKER_00: Because we're two weeks before the semester starts,
• 22:03
  SPEAKER_00: give or take, and nobody wants to rewrite the syllabus for nothing.
• 22:08
  SPEAKER_01: That's true.
• 22:09
  SPEAKER_00: All right.
• 22:09
  SPEAKER_01: Thank you so much, Guy.
• 22:10
  SPEAKER_01: Wait.
• 22:11
  SPEAKER_00: So now I have a question for you.
• 22:12
  SPEAKER_01: Sure.
• 22:14
  SPEAKER_00: This last week, how have you been using AI that's been very productive?
• 22:20
  SPEAKER_01: That's a very good question.
• 22:22
  SPEAKER_01: So I think about two days ago, I'm working on a manuscript.
• 22:28
  SPEAKER_00: Surprisingly.
• 22:31
  SPEAKER_01: Yeah.
• 22:31
  SPEAKER_01: And we had already thought about the structure of the Let's Review section.
• 22:37
  SPEAKER_01: We had different parts, but we were not sure about, and how can I say this?
• 22:43
  SPEAKER_01: We were kind of frustrated because we didn't know how much overlap exists
• 22:49
  SPEAKER_01: Between different sections of the list review.
• 22:52
  SPEAKER_01: So what we did is that,
• 22:54
  SPEAKER_01: and I'm using the ChatGPT education version,
• 22:57
  SPEAKER_01: so I'm not very concerned about the privacy of the data.
• 23:01
  SPEAKER_00: Yeah, it's institutional ChatGPT, which we're happy to have.
• 23:05
  SPEAKER_01: Yes, yes, absolutely.
• 23:07
  SPEAKER_01: So we put the lead review into ChatGPT and we explained about our project.
• 23:13
  SPEAKER_01: We gave it enough contextual data and we talked about the organization of what made sense to us.
• 23:21
  SPEAKER_01: And then we asked ChatGPT to suggest an organization for our lead review.
• 23:27
  SPEAKER_01: And it did a super good job in terms of moving some of the parts,
• 23:33
  SPEAKER_01: suggesting us to move some parts of the subsection to another subsection,
• 23:38
  SPEAKER_01: merging headings together.
• 23:40
  SPEAKER_01: Most of the things that it said made sense.
• 23:43
  SPEAKER_01: And what we did was that we did not just copy what AI produced.
• 23:48
  SPEAKER_01: We started comparing what AI suggested versus what we created originally.
• 23:54
  SPEAKER_01: And then we started editing with more confidence,
• 23:57
  SPEAKER_01: going back to AI,
• 23:58
  SPEAKER_01: checking,
• 23:59
  SPEAKER_01: and many of the things that AI created for some of the sections were redundant.
• 24:05
  SPEAKER_01: So we did not change that part in our writing,
• 24:10
  SPEAKER_01: but it helps us a lot to think through what was happening in the let review section.
• 24:15
  SPEAKER_01: Yeah.
• 24:16
  SPEAKER_00: And organizationally, it can suggest things.
• 24:20
  SPEAKER_00: And one of the things that I've started doing more recently is also asking it
• 24:25
  SPEAKER_00: to critique its own work.
• 24:26
  SPEAKER_00: So now that you've suggested this,
• 24:28
  SPEAKER_00: point out to where the suggestion is weak and where it could be either improved
• 24:34
  SPEAKER_00: or just to have to admit that there's just,
• 24:37
  SPEAKER_00: you know, in a lit review, you often have to admit there's limited space.
• 24:40
  SPEAKER_00: You don't want the lit review to take over everything.
• 24:43
  SPEAKER_00: Because you can easily create very long narratives about the literature itself.
• 24:49
  SPEAKER_00: And it's like too much.
• 24:50
  SPEAKER_01: Yeah.
• 24:51
  SPEAKER_00: So what do you do?
• 24:52
  SPEAKER_00: All right.
• 24:53
  SPEAKER_00: So I'm excited that this is the last episode of Season 3.
• 24:59
  SPEAKER_00: But coming up in mid-September, we will have the beginning of Season 4 of Angai.
• 25:06
  SPEAKER_01: On AI.
• 25:07
  SPEAKER_00: All right.
• 25:08
  SPEAKER_00: We'll see you then.
• 25:08
  SPEAKER_01: See you.