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Season Two Starts Now! · Azadeh and Guy on AI

• 0:01
  SPEAKER_00: Hi, and welcome to season two of Azadeh and Guy on AI.
• 0:07
  SPEAKER_00: And we are really excited because it is January.
• 0:11
  SPEAKER_00: It is a new semester for us.
• 0:13
  SPEAKER_00: And we are excited to do new things with AI.
• 0:17
  SPEAKER_00: And we hope you'll hang with us at least a little bit.
• 0:20
  SPEAKER_01: Yeah.
• 0:20
  SPEAKER_01: So happy.
• 0:23
  SPEAKER_00: Happy New Year and Azadeh is trying to keep me on time.
• 0:28
  So the episodes are short enough for you to consume quickly and
• 0:32
  you don't have to
• 0:33
  SPEAKER_00: listen to my voice that much.
• 0:35
  SPEAKER_01: So before we start our usual thing, let's introduce ourselves.
• 0:40
  SPEAKER_00: All right.
• 0:41
  SPEAKER_01: I'm Azadeh.
• 0:42
  SPEAKER_01: I'm a third year PhD student here at UNL.
• 0:46
  SPEAKER_00: I'm Guy Treinen.
• 0:47
  SPEAKER_00: I'm a professor at UNL in the Innovative Learning Technologies program.
• 0:53
  SPEAKER_00: And I do a few things here and there.
• 0:58
  So we finished the first episode of Azadeh and Guy on AI a
• 1:02
  couple of weeks ago.
• 1:04
  SPEAKER_01: During that season, we talked about multiple things.
• 1:09
  SPEAKER_01: Do you want to have a brief summary of that?
• 1:13
  SPEAKER_00: Well, we've talked about AI in education in a few ways.
• 1:18
  SPEAKER_00: We started talking a lot about AI in research.
• 1:23
  SPEAKER_00: This is one of the things we're both interested in.
• 1:25
  And this is one of the things where we're seeing a lot of AI
• 1:30
  entering the research world.
• 1:32
  SPEAKER_00: Some of it appropriately, some of it not appropriately.
• 1:35
  SPEAKER_00: And then we shifted to AI in learning,
• 1:38
  SPEAKER_00: especially we did quite a bit of work in language learning.
• 1:42
  SPEAKER_01: Yeah, very true.
• 1:43
  SPEAKER_01: AI and also achievement emotions.
• 1:46
  SPEAKER_01: These are among our last topics that we talked about.
• 1:51
  SPEAKER_01: But we also introduced a lot of AI-enabled applications,
• 1:57
  SPEAKER_01: especially those that,
• 1:58
  SPEAKER_01: as you said,
• 1:58
  SPEAKER_01: are useful for doing research.
• 2:01
  SPEAKER_00: And so this season we'll continue with some of these,
• 2:04
  SPEAKER_00: but we promise to have new and exciting things.
• 2:07
  SPEAKER_00: What are some of the things we're planning?
• 2:11
  SPEAKER_01: That's a good question, Gari.
• 2:13
  SPEAKER_01: AI is changing every day.
• 2:15
  SPEAKER_01: So I think I'm talking about myself.
• 2:18
  SPEAKER_01: Plans are also kind of changing every day.
• 2:23
  SPEAKER_01: So thinking about three things that I want to do with AI this semester,
• 2:29
  SPEAKER_01: I'm co-teaching a course with you.
• 2:31
  SPEAKER_01: So I am thinking about how I can use AI or how I can co-teach with AI
• 2:39
  and how I can find new ways to introduce AI in a responsible
• 2:44
  and also ethical way to students.
• 2:46
  SPEAKER_01: That's one of my goals.
• 2:48
  SPEAKER_00: Yeah, I'm working on understanding how AI can help in research.
• 2:54
  That's a strand that I will keep on hitting because I think
• 2:57
  there are more and more
• 2:58
  SPEAKER_00: opportunities that present themselves out there,
• 3:00
  SPEAKER_00: but also more and more pitfalls.
• 3:02
  SPEAKER_00: So I'm seeing,
• 3:03
  SPEAKER_00: for example,
• 3:04
  SPEAKER_00: graduate students putting things into AI without thinking about,
• 3:09
  SPEAKER_00: am I allowed to use this data in AI?
• 3:12
  SPEAKER_00: Should it be AI?
• 3:14
  SPEAKER_00: How do I know it's any good or any of these things?
• 3:19
  So really thinking about the pitfalls,
• 3:21
  the challenges,
• 3:22
  but also the opportunities.
• 3:24
  SPEAKER_00: Obviously, teaching with AI is putting my money where my mouth is.
• 3:30
  SPEAKER_00: kind of thing.
• 3:31
  SPEAKER_00: It's like, can I make this actually work?
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  It's a really interesting question that I'm interested in
• 3:36
  answering this semester.
• 3:38
  SPEAKER_00: And of course,
• 3:39
  we will have actually interviews with a variety of educators
• 3:44
  that are using AI in
• 3:46
  their teaching practice or researchers who are using AI in
• 3:50
  their research practice.
• 3:51
  SPEAKER_00: So you'll get more than our view on everything.
• 3:54
  SPEAKER_01: Yeah.
• 3:57
  SPEAKER_01: I'm also involved in different kinds of research projects.
• 4:02
  And most of them are about how students or how faculty are
• 4:07
  integrating AI into
• 4:08
  SPEAKER_01: their teaching and learning practices.
• 4:11
  SPEAKER_01: So that's another goal.
• 4:13
  SPEAKER_01: And the other one is more about my personal goals.
• 4:16
  SPEAKER_01: So I'm trying to understand and explore more AI tools.
• 4:20
  and go beyond just prompting and understand how I can combine
• 4:24
  and use different AI
• 4:25
  tools and how I can automate my research or at least part of my
• 4:31
  research using
• 4:32
  SPEAKER_01: different AI tools.
• 4:34
  SPEAKER_00: And we have a specific thing that we're pursuing,
• 4:37
  SPEAKER_00: which I'm pretty sure we will not finish this semester,
• 4:40
  but trying to build an application that uses AI to identify
• 4:45
  research that is using
• 4:47
  SPEAKER_00: AI,
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  report on it and aggregate it in a way that can provide some
• 4:53
  information out to
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  SPEAKER_00: those who are interested in outcomes around AI.
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  SPEAKER_00: And I think that there's a lot of vibes
• 5:03
  SPEAKER_00: adoption of technology.
• 5:05
  SPEAKER_00: It sounds like a good idea.
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  SPEAKER_00: It's coming, which I totally agree with, by the way.
• 5:10
  SPEAKER_00: AI is coming.
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  SPEAKER_00: It's going to be required at most workplaces.
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  SPEAKER_00: It has ethical concerns.
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  SPEAKER_00: It has job concerns.
• 5:20
  SPEAKER_00: But kids need to know about this.
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  SPEAKER_00: They need to start incorporating it professionally.
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  SPEAKER_00: So teaching about it and teaching with it is going to be here.
• 5:30
  SPEAKER_00: But we need to be very careful about it.
• 5:32
  SPEAKER_00: That's the thing we go back to again and again and again.
• 5:35
  SPEAKER_00: And that's kind of driving my interest in talking to other people,
• 5:39
  SPEAKER_00: but also in looking at the research.
• 5:42
  SPEAKER_01: So the other thing that is happening is that with AI,
• 5:47
  SPEAKER_01: we are always expecting major developments.
• 5:50
  So I'm curious,
• 5:51
  what are some major developments that you are expecting,
• 5:54
  guys?
• 5:55
  SPEAKER_00: So there are a few things I'm watching.
• 5:58
  SPEAKER_00: So there are two developments that I'm watching very carefully.
• 6:04
  SPEAKER_00: One of them is one that we've actually talked about before,
• 6:07
  SPEAKER_00: especially when we talked about Google,
• 6:09
  SPEAKER_00: and that is the struggle between...
• 6:14
  how does the conflict between the big AI companies and the
• 6:20
  wrapper companies,
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  SPEAKER_00: so we've got people who produce models,
• 6:23
  SPEAKER_00: and then we've got people who produce more school-friendly applications,
• 6:30
  SPEAKER_00: or in the case of SciSpace and Asta and all of these,
• 6:37
  research tools that will help you do a literature search and
• 6:41
  all of these.
• 6:42
  So when you think about these,
• 6:44
  is there going to be a space or are the big companies going
• 6:48
  to...
• 6:50
  SPEAKER_00: Yes.
• 6:51
  SPEAKER_00: And kind of swallow the little ones or just make them useless.
• 6:55
  SPEAKER_00: They can block access to their models.
• 6:58
  SPEAKER_00: That's one option.
• 6:59
  But they can also just produce something better and cheaper
• 7:03
  because they have so
• 7:04
  much cash at hand that they can trump anything that a small
• 7:08
  company can do.
• 7:09
  SPEAKER_00: So that's an interesting thing to watch.
• 7:11
  SPEAKER_00: We had a conversation before we met here about,
• 7:14
  should we teach our pre-service teachers about the smaller
• 7:17
  models and the wrappers
• 7:18
  SPEAKER_00: like Magic School and all of that.
• 7:20
  SPEAKER_00: I'm a little apprehensive before we see how things play out.
• 7:24
  SPEAKER_00: So this is one thing that I'm watching for.
• 7:26
  SPEAKER_00: I don't know the answer.
• 7:28
  I don't have a divination stick that helps that,
• 7:31
  but it's interesting to watch.
• 7:33
  SPEAKER_00: The other one that I'm watching very carefully is the reaction,
• 7:36
  the political and cultural reaction to AI because we live
• 7:42
  inside the AI bubble.
• 7:43
  SPEAKER_00: Mm-hmm.
• 7:45
  SPEAKER_00: We are excited about it.
• 7:46
  SPEAKER_00: We are worried about it.
• 7:47
  SPEAKER_00: But we are trying to explore it from the inside.
• 7:50
  SPEAKER_00: I'm seeing,
• 7:52
  SPEAKER_00: to a certain degree,
• 7:53
  SPEAKER_00: a growing level of criticism in the political realm,
• 7:57
  SPEAKER_00: in the cultural realm.
• 7:58
  SPEAKER_00: How are people still there?
• 8:00
  SPEAKER_00: How can we resist AI?
• 8:02
  SPEAKER_00: And so I'm watching this carefully to see how it plays out.
• 8:08
  SPEAKER_00: It's very likely to be very political.
• 8:10
  SPEAKER_00: We're already starting to see those events coming in.
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  And Bernie Sanders talking about AI and how AI might take jobs
• 8:19
  and how we can
• 8:20
  SPEAKER_00: counterbalance with that.
• 8:22
  SPEAKER_00: I think that that's going to be part of the discussion.
• 8:26
  I'm seeing a lot of creatives worrying about AI and saying,
• 8:30
  I vow to not use AI in anything.
• 8:32
  And I'm going to actually say that very clearly and mark
• 8:37
  everything that I do with
• 8:39
  SPEAKER_00: no AI has touched this.
• 8:40
  SPEAKER_00: It's kind of like GMO food or whatever you want.
• 8:44
  SPEAKER_00: And so we're starting to see that.
• 8:47
  SPEAKER_00: And again,
• 8:47
  SPEAKER_00: I'm not sure how it's going to turn out,
• 8:49
  SPEAKER_00: but it's another trend that I'm watching carefully.
• 8:54
  SPEAKER_00: Because, again, from our view from inside the bubble, almost.
• 9:00
  SPEAKER_00: I mean, we're both inside and out.
• 9:02
  SPEAKER_00: But the view from inside the bubble can sometimes be distorted.
• 9:06
  And I have a sense that Eli is with us and is going to be
• 9:10
  prominent,
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  but I'm not sure.
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  SPEAKER_00: So those are the two things I'm watching.
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  And I'm really interested in the rising critiques around
• 9:17
  research and what is now
• 9:19
  SPEAKER_00: starting to be dubbed research.
• 9:22
  SPEAKER_00: a slop or junkification of research.
• 9:27
  SPEAKER_00: There's a paper like that.
• 9:29
  SPEAKER_00: There's a paper.
• 9:29
  SPEAKER_00: We'll talk about this.
• 9:30
  SPEAKER_00: We'll do an episode on it.
• 9:32
  SPEAKER_00: But this is something I've been interested in for a while.
• 9:35
  SPEAKER_00: It actually has very little to do with AI except that AI accelerates.
• 9:40
  SPEAKER_00: Mm-hmm.
• 9:41
  SPEAKER_00: Cheating,
• 9:42
  the ability to write quickly meaningless papers and the rise of
• 9:48
  just multiple
• 9:48
  publications for profit and all of these other things that are
• 9:53
  happening in the
• 9:53
  academic realm where AI just accelerates them and makes it
• 9:58
  almost overwhelming to
• 9:59
  SPEAKER_00: be able to consume all of this research.
• 10:02
  And on the other hand,
• 10:03
  there's the emergence of tools that help you process this
• 10:05
  amount of data.
• 10:06
  SPEAKER_00: So it makes the data and then it solves the problem.
• 10:11
  SPEAKER_00: And that's something that people are concerned with.
• 10:14
  SPEAKER_00: I'll be honest, I'm less concerned with sometimes.
• 10:17
  SPEAKER_00: I'm very concerned with other times.
• 10:19
  SPEAKER_00: It depends on what it is.
• 10:20
  But that's going to be a topic for our show where we can talk
• 10:24
  through the issues
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  SPEAKER_00: and think through it and maybe invite somebody to talk about it.
• 10:31
  SPEAKER_00: All right.
• 10:33
  SPEAKER_01: Let me see.
• 10:34
  SPEAKER_01: Personally, I'm waiting for Google Labs to be improved.
• 10:37
  SPEAKER_00: Yes.
• 10:39
  SPEAKER_00: Google, if you're listening, please, do something.
• 10:45
  SPEAKER_00: Because we are right now disappointed.
• 10:48
  SPEAKER_00: Also,
• 10:48
  it's an opportunity to use the other things we have out there
• 10:54
  that help us do this
• 10:56
  SPEAKER_00: kind of work and uncover.
• 10:58
  SPEAKER_00: And really, this is about uncovering.
• 11:00
  SPEAKER_00: I do want to go back to some of these issues and see how they're using.
• 11:06
  SPEAKER_00: And if we're talking about
• 11:07
  SPEAKER_00: how I want to use.
• 11:09
  One of the things that I want to do with AI this semester is be
• 11:13
  more persistent
• 11:14
  SPEAKER_00: about improving my prompts and getting better.
• 11:17
  SPEAKER_00: I've given up on so many halfway done Gemini images.
• 11:22
  SPEAKER_00: Yeah.
• 11:23
  SPEAKER_00: And I couldn't get them to move.
• 11:25
  SPEAKER_00: And I'm like, what is going on?
• 11:27
  SPEAKER_00: Why can't you make the change I want?
• 11:29
  It's probably a prompting issue because lately I've been a
• 11:32
  little bit better.
• 11:36
  SPEAKER_00: And so it's been delightful.
• 11:37
  And now ChatGPT is coming up with a new image,
• 11:40
  a model,
• 11:41
  or just came out with an image.
• 11:43
  SPEAKER_01: I haven't tried it yet.
• 11:43
  SPEAKER_01: Yeah, but I heard about this yesterday.
• 11:45
  SPEAKER_00: But the advice is always get good at a few of them.
• 11:50
  SPEAKER_00: And if they do what you want, great.
• 11:52
  SPEAKER_00: If they don't, keep on looking.
• 11:54
  SPEAKER_00: There's going to be something better.
• 11:55
  SPEAKER_00: If not this week, next week.
• 11:57
  SPEAKER_00: Because this is how the AI world works.
• 12:01
  SPEAKER_00: All right.
• 12:01
  SPEAKER_00: So welcome to season two.
• 12:04
  SPEAKER_00: It's going to be a fun ride.
• 12:06
  SPEAKER_01: Sure.
• 12:07
  SPEAKER_01: Yeah.
• 12:08
  SPEAKER_01: Can't wait.
• 12:11
  SPEAKER_00: We'll see you next time.
• 12:12
  SPEAKER_01: See you.