 Hello, hello. Hi everybody. Yeah, it's wonderful to see everybody. This is a really, really exciting event. I'm sort of, you know, I'm tasked with just saying hello to everybody as they come in. And I'll be talking more later as is my, as is my custom. I'm always happy to talk for as long as people give me. But first I just, before we get into that, like the weeds of everything, I just want to thank Lucas, and just say how much work Lucas and the team have put into this symposium and frankly into everything to do with the generative efforts at CTLT. So a lot of the, a lot of the team are on screen right now. So Rich and Lucas and Judy have been doing so much work to, to get all of the generative AI stuff together. So thanks to all of you for making all of us a reality. It's just been an incredible, incredible push really to, to get all of these things up and running. So, so yay it's thanks to, thanks to everybody that, that we're here, but mainly this one I think, you know, Lucas this was, you sort of came around to this you were like I think we need a symposium I think it needs to look like this and so the reason that we're all here is, you know, thank you, thank you, Lucas. So, nice work. Well done. You did it. Congrats. So yeah so while we're just welcoming everybody I just want to say hello. And the way that the session is going to go it's not a tremendously long session it's just kind of an orientation to the whole to the whole couple day event. Lucas is going to start us off by kind of orienting us in the space. And then I will take a few minutes to wax philosophical. You know, I don't know why I'm allowed to do that but here I am and I'm just going to do that which is going to be exciting for me, and you're all going to be subjected to that which is great also for me. And then, yeah, and then we're just going to take a look at the next couple of days. I think that it's the case that every zoom link is the same for this event. Right, Lucas. Yeah. So if you've registered only for this event but you're like oh I wish I had registered for a couple of other but don't worry you can just click the same link and it's all just one one whole day of you know to hold dates and stuff all on the same link. So, yeah. Okay, well I think our numbers have kind of settled. Super excited to see everybody here and again, you know, thank you so much Lucas for putting this together it's just been this for cullian effort, and so much of your vision has gone into this and so thank you thank you I'm super proud to hand it over to you to to welcome everybody to today. Thanks for the kind words and that hopefully it doesn't all go wrong now. So welcome to the teaching and learning with gen AI symposium and what we're going to do for the next half hour is we wanted to all go through land acknowledgments and intros and then we wanted to kind of give a little bit overview around almost a thought experiment we've doing thinking about some of the challenges that the institution and societies looking at with gen AI and then at the tail end of that, I'm going to kind of go over the events and link them into that little framework we put together. So, just to begin with acknowledging that I'm coming from UBC campus which is on traditional unseated Musqueam territory, and also that I think when we think about generative AI. One of the big ethical issues is the amount of indigenous knowledge that was online, and has been scraped by these tools and has been used without permission, and I think that goes beyond intellectual property, and it starts to get us thinking about colonialism and what the impact of that might be. Let's start with just a again kind of a thought experiment that Alyssa and I were doing thinking about gen AI in teaching and learning and we put together this kind of levels of change. And the idea behind the levels of changes that at the very top there we have our foundations, thinking about our academic integrity or ethics or capacity. Then the pedagogical changes what approaches is it changing in the classroom, what opportunities are there, and then getting into institutional society changes so what new skills are we needing to learn. What's changing in our professions and disciplines, and then kind of getting to the very top. So what we need to do. How is teaching changing really in a large way. And so what I'm going to do now is walk through one and two, and then Alyssa is going to talk to us more about three and four. So, just from a foundational level. And as I'm saying this I'm like why did I put foundations at the top their odd foundations. However, I think there's kind of some key questions that a lot of us have been asking in the university community and wrestling with and by foundation level I mean kind of what we need to do today around gen AI. And one of the questions right away is what are the capabilities of these tools, and when gen AI started getting quite popular in January of this year. You probably saw there's lots of news articles there's lots of posts there's lots of articles saying this isn't that powerful I put in a question, I didn't get a great answer. And what a lot of us have seen is that this has changed really quickly and we're seeing a lot of incredible capabilities with these tools, acknowledging that they're still not experts. But we have seen a big increase in capabilities and just a couple of examples of that. We know that GPT for was able to get 90 in the 90th percentile in the standard bar exam. The study by Lee at all showed that gen AI when writing critical reflections in the context of pharmaceutical education was able to score better than the average student, and in addition was indistinguishable from evaluators couldn't distinguish the two outputs. In computer science, we've seen studies that show that GPT can score above average in first and second year computer science problems and verata who's going to be presenting later today is going to talk a little bit about some of the stuff she's seen in her own context. So we're also seeing capabilities change in terms of what these tools can do. Computer vision now is significant in chat GPT. If you use GPT voice, you can have some pretty good conversations recently I had a socratic dialogue about the state of nature with my phone, which was a slightly outputting experience. We've also seen Internet access growing and you know one of the things we said initially was that these tools couldn't access the net. And now we're seeing with being AI, the ability to crawl the net and the ability to find more recent references. So that brings up the question is how do we develop capacity as faculty members as staff with this changing. And we're hoping that through this symposium it's one way to start that capacity conversation with the capabilities I think has come some of these huge ethical challenges around this tool and it's a difficult thing to square personally is how do we deal with these ethical challenges we know that a lot of our private data and research and the world's private data has been researched and scraped and sold back to us in some ways. We know that the privacy is quite challenging these tools haven't passed the PIA. I just saw this morning the chat GPT data analysis tool. People were able to access files through it by running queries so we know these tools have leaks in them we know there's privacy problems. There's environmental questions with these tools. There's equity questions. And then finally kind of putting these together how do we think about academic integrity in these space, considering these capabilities of these tools and considering all the work we did that faculty did during the pandemic to make our institution more flexible more accessible for students with things like online exams, online approaches, how do we wrestle with this now how do we think of academic integrity, when we also know that AI detectors have been problematic, and they get a lot of positives a lot of the false negatives and human capability to detect AI in recent studies, linguists were only able to identify 38% of output generated by chat GPT. So I think this is a big challenge at the foundational level. And that brings us a little bit to the opportunity there. You know what are new ways of thinking about learning what are new ways about thinking of teaching in these environments. We have new opportunities for personalization that I don't know if we've seen before. When you think of things like I know Simon's in the room we talked about the bloom Sigma two problem, how we know the tutoring is tends to be at least according to that study, a more powerful way of or more effective way of teaching. But what does it mean now that we can have tutoring that may be scalable. How did these models augment our roles as faculty. And what are some new and emerging approaches to teaching and learning a list over to you. You think after years of this zooming that I would know where my mute button is but you know, takes me 17 seconds to find it every time thanks. Thanks, Lucas. Thanks for, for bringing us to this space and also thank you for your land acknowledgement. I think it is. I'm also joining from traditional Muslim territory in my office at CTLT. And when Lucas and I were planning this session. We had that picture from slide, you know this the other slide where is it the this one on the on my whiteboard. And Lucas said okay well I think I can speak about the foundational the pedagogical the institutional, but what do you mean when you say the singularity. What are you, what are you talking about. I can just speak about that one. So that this is falling to me. And the reason that I think it's important for us to talk about it is because once we have examined, I mean, so the questions that have been raised are like, you know, we initially met this with sort of saying okay we can do this. How do we get everybody access how do we, how do we make sure that students aren't cheating. How good is this thing really there was a lot of concern. And then we sort of moved through these layers of abstraction like now we're sort of thinking okay well how can we actually leverage this what is the role of this in our education. We're very much thinking within our shapes that we've already made our abstractions of our education and our, our system. That that we have already worked within how do we bring this tool into our into our system, so that it can help us so that it's a facilitator of our existence. And realizing maybe, or maybe kind of corner of our I realizing but without maybe grappling with the fact that this isn't just a tool that's going to help us. This is a tool that is going to take over, and that is going to, in some ways replace us, and that we will begin to rely on the same way and I think Simon you and I were talking about this it's almost like the way that we rely on electricity. It goes out what do we do we start to, everything starts to kind of collapse. How much are we going to start to rely on these tools and what is it that they can really do. You know it's really funny listening to, to how these tools can, you know beat the bar exam or beat, you know, beat various assessments of course, of course they can they're cheating these tools cheap, right they are have the ultimate open book exams and they are memorize the entire book and so of course they can beat these things it would be shameful if all the LSAT textbooks in the world didn't then produce, you know, a tool that could easily query itself and see what the answer should be to all those questions. But now that we have something that can do these things that can guess better than us and that can that can code faster than us with with better correctness. What is our role. So I think the next question that we need to ask is what is actually the human component in this. I think market forces will keep looking for cheaper options to everything that we do, whether philosophically, we want education to dramatically change maybe we have a very sort of nostalgic notion of what education should be maybe we feel like we should be in a monastery thinking philosophically about things, but the truth is the market drives what we do. And if something is cheaper, it'll probably be a success. And so what is it about, I mean we know that this is going to be cheaper for so many things. So I think that Rich and and I have been exploring how to take one of my courses and completely robotify it so that you know just basically pushing it pushing this to its limits so that we can replace me as an educator just to see how much how much I can be replaced. And I bet it's pretty, I bet it's pretty far I think you know I think it's going to do a pretty good job I'm excited to see how it goes. It's not that I'm trying to bring on my own. My own obsolescence but I think it's a good idea for us to think through how much, how much can we really be replaced and then what is our final role in this space, so that we can work on that. As educators, you know our business is education we do need to know where we fit as educators what the special sauce is that we bring. My thinking is that we, you know that human touch human human emotion human motivation pragmatics all of these things are genuinely important in education. But it remains to be seen. And I think until we've tried it until we've gotten ahead of it and tried it I really don't think we'll know. And I feel like for our university for our institution it's our job to get ahead of I guess I should have gone on one slide. What comes next. It's our, it's our job as educators to try and figure out what education will look like in 15 years, you know not I mean even in two years that's going on with dramatically changed all of those things that we've said, TAs will be, you know augmented and instructors will be augmented in 15 years what will it actually look like how many of us will there be and what will classes be like, and will there be classes and will it just be students talk to robots and then come to an office hour. I'd love to hear everybody's perspectives Celeste I see you've joined just be delighted to hear your perspective on this. I think you know that's one of the reasons that we sort of set this, you know, Lucas is going to go over the shape of the shape of the plan, but this is one of the reasons that we wanted to explore the depths of this because it is truly our mandate here at this enormous university in the class of university in Western Canada, we should really be leading the way in seeing what is coming in the next decade, so that we can, to some extent influence the space, I don't think we want to be the ones on the back foot, I think we want to be, to some extent the leaders and the, and the way pavers for the way that education is going to take shape. Luckily, we're, we are behind in some things, as everyone always is in this global world everyone's always behind in something, but we're ahead and in some other things and I think right now, we can get ahead and thinking about how our massive role is in totally revolutionizing education to really bring this on so that we can be an ally with the new approach as opposed to being just a rider of the tidal wave. So that is my, that's my, my thinking and yeah, I'm excited to explore this with everybody here.