Okay, oops. Okay.
So, Hello, my name is Terry.
And I work as an inter library services associate I am a DM digital media design liaison, and I teach, um, an class.
And when I was 1st, asked to do the presentation on a, I, my 1st reaction was, I am by no means an expert not at all, but I do Co chair.
Uh, a community of interest that I Co, started with another colleague of mine or UConn library staff to just really talk and communicate about AI and pretty much staying informed. Right? So, I am learning and I'm hoping to share what I have been learning and what I've learned with you to.
You on your journey to learn more quick overview. I'm going to give you.
A brief overview of general AI, the pitfalls and exploring tools.
So instead of me creating a whole.
Description of what generated a I have a 2 minute video, which I'm gonna extend slightly when I play it I'm going to actually slow the speed down so that we can hear what they're saying because it's it's a good video but it's a little fast. So, I'm gonna start it and then I'm gonna pause it. I'm gonna change the speed.
And then what exactly is generative a, I.
When new content is created by artificial intelligence, it's called generative a, I.
This could involve generating texts and images as well as videos, music or voices.
To do this, you describe in a chat dialog box what you want the, a, I, to create.
This description is called a prompt.
The generative a, I tools provide answers to all sorts of questions.
Summarize complex information and generate diverse ideas quickly, depending on how they used, they can create short stories paintings.
Pieces of code, or even musical compositions.
The foundation for this creation lies in large amounts of data that the API system accesses to identify patterns and similarities.
The content produced by the a, I is name it's often impressive.
And challenging to distinguish from things. Humans have made.
Generative a, I can also be misused in so called deep fakes.
Api is utilized to produce images or videos that seem real.
Ai generated text. Oh, so tough to recognize as machine made moreover, the API can provide answers. That sound correct but are actually incorrect. This is called hallucinating. The quality of what's created. It depends on the, the quality.
Of the day she used, and the quality of the prompt given.
Effectively utilized generative a, I.
We need to learn how to guide the tools with meaningful prompts.
So, thoughtfully generative ai holds immense potential and can help us in many ways.
Such as serving as a writing or learning partner.
However, the, a, I should do the hard work and human should be responsible for the facts.
Jerry, we aren't seeing a video you are.
Alright, I should just play the whole thing. Oh.
It's already over. I'm sorry. Oh, goodness.
I wonder why we.
Here you've been watching me the whole thing when we go back to my.
And stop sharing here, we could hear it. You could.
We can clear it, so maybe okay, we can just post a link.
Ok, I will do that. I will do that. Oh, my gosh. I, I sorry.
Um, let's get out of here now, then. Oops. Nope.
All right, so.
That's okay. We're going to summarize this anyway. Um, so, let's summarize what general is and when I was creating the slide show, I thought, okay.
I could summarize it, or I can ask AI to do it for me.
So this happens to be in a I, um, product.
Terry, I'm sorry, you're, you're not sharing your screen right now, so we can't see slides. Okay.
This is not good. Let me escape.
It's really interesting because I see the red dot around the red line around everything. I'm doing. Let me just close. Can you see the screen now?
No, okay. Let me go back and share it differently. Then.
I'm going to share I'll just share the PowerPoint then. How's that?
I hope this is gonna be better. It was a really good PowerPoint to have a good studio. Is that, uh.
Yeah, so you can see that here. Thank you. Okay, so, let me just go to the next slide. Now I will send the link for that.
Okay, um, so again we're going to summarize, but what I'd like to do then is to use a tool.
Which will summarize it for me. So, down below, I have a link.
To supervisor, and if you do not see this web page, please let me know.
It's going to open up and I'm not sure if you're going to be able to see this cause it's not highlighted. Are you seeing the webpage?
No, you'll have to share that. Okay, so I'm gonna.
I'm gonna I'm gonna stop and share my screen differently than.
Do it this way? Okay.
Now, can you see the webpage? Yes.
Okay, great Thank you. All right. Um, okay, so, you know, we had a short video, which unfortunately was just audio for you.
And what I wanted to do was in, in creating this presentation, was to have it summarize it for me. So, um, let me see if I can.
It's to load, of course, as everyone always says, when you do this, when you're rehearsing, it always comes out better than when you're actually 1st a day. But let's see if this will work.
Nope, this is not the right video. Okay. Um.
Let me go back to the PowerPoint. All right so, basically, what I did.
Is I went into this web page I took the URL of the video that I watched that that I showed you and showing, and I hit generate summary.
So, the thing is, I have screenshots to follow up in case.
The patient work, so on the left side of the screen is what was generated by the YouTube video summarize, or it gave me a page. Um, that gave me a summary.
And the summary is, you can see is right here so it's generated AI is the creation of new content, but artificial intelligence.
Including text images, video, it relies on prompt.
It can be misused and create deep.
And it requires meaningful prompts and human responsibility for the facts.
In the end, what I'll do is I'll try to share just the webpage, so I can actually show you live how it just generated it. You just type it in and then it goes ping ping ping the line start to load and.
And you get your responses, it also, um, provided highlights. So, again, on the left is a screenshot from the web page itself and I just enlarged over here on the right.
Of the highlights of that video, so it gives me the timestamps and it gave me, uh, points. So, at 132 a, I can create various types of content at 2:33:uh.
Text can be difficult to distinguish. So, these again are the highlights from that video and remember this was like a 2 minute video. So I would imagine, um, if you use this with a longer video.
It's probably going to be a little bit less repetitive in the highlights.
And also, it gives me key insights. So I'm going to use these key insights.
To discuss what some of the pitfalls are um.
That of HR in general, but again, key insights.
To this video of what generated a I, is, is that it, um, access to large amounts of data.
And that's how it uses it it that data to identify patterns and similarities to create new content.
It can be misused and again, these are a little bit repetitive from the summary but I think a longer video might have.
Pulled out different, um, key insights and had a little more variety in the points.
But so let's use these key insights then to.
To look at some of the pitfalls. So, 1 of the things that that it points out about genitive AI is that it uses large amounts of data.
And why is that a problem? Well, whenever you're looking at.
Data the source is really important as we all know. Right? So I asked.
Our chat in this case, where does ai get in the data?
So, it's getting its data from public data set sets right? Anything that's out there in the public. In fact, probably some of the primary source.
Web pages that were shared, you know, in the previous presentation.
If they're publicly available, then, then they can be great it can be scraped and that's probably contributing to some of this.
A large data that that's being used to generate responses. It can be taken from private data. Datasets.
Web scraping sensor data, or the Internet of things type data.
And user interactions, so again, when you're talking about this of this as a pitfall, right then we're talking about data that's being collected from all different types of sources and.
Whether these are trusted reliable, valid forces.
Or not would would.
Impact the results of of what is going to be generated by AI.
And when you're thinking about data, always, um.
1 thing that has been kind of like, forward in thinking about what's what the response is you might be getting from a, is the algorithm bias, right?
So, again, I asked, please tell us what algorithm wise is and this is a really good description. Algorithm bias is the systematic and repeatable tendency of algorithms to produce unfair or discriminatory outcomes to factors such as biased training training data. I'll go with MC design or deployment context.
Yeah, the data that is being used by AI, um, has bias in it and it's gonna it's gonna be repeatable. So.
It it could, you know, um, potentially.
You know, even a lot impact, um, the bias, even further and further, like, down the road if it keeps repeating information that is biased then.
And that's a whole nother again, another webinar there are webinars on algorithms.
Um, so that's 1 pitfall. Um, the other football is the misuse of general AI, right? Such as deep face. So.
That might be something you're familiar with, but I have a video that please if it doesn't show, let me know I'm going to. It's a really short video, but it's again, I asked ai what a deep fake is.
And it said, um, it's a manipulated or synthesized media.
That uses advanced machine learning techniques.
To create convincingly realistic, but false content. So here was a really short little video of.
Please tell me if it doesn't work. Okay. You've got me thinking about my fulltime reports. Yeah, I'm gonna just pause for a 2nd. Can you see the video.
Yes, thank you. Okay. Yes. Perfect. Okay.
And their ability to survive on 8 dollars an hour, in New York City, foremost, in all of our minds, it's been the loss. The grief held by the people who are Orlando.
Most of us don't get our health care through marketplace.
To our job, Medicare, Medicare.
What you should know is that thanks to the affordable care act your coverage is better today than it was before women could get free chickens.
And get charged for just for being a woman.
If his employees younger to pass a Congress, a builder with boost America's very, very hard times some progress, at least within the small complex, legal community. I think it's real important a year ago.
Robin, and when you giving us the.
Make sure you. Okay so that was just an example, um, which.
Again, you know, with elections, coming up, you know, any type of worldwide events defects is certainly a pitfall of the right because it has, it has.
Demands potential to do harm get to the next slide. He got me thinking about not what I want to do.
Okay, and then it also talked about in the video, the quality of the prompt right? If if any of you recall, I know, I recall this when I was younger, I had to teach you that said, okay, we're going to write out instructions for how to make a peanut butter and jelly sandwich and, you know, you raise your hand. Okay, you put the peanut butter on the bread.
Okay, here's the Peter benefits on the brand. Right? So a good gen, generative ai prompt is clear specific.
Provides enough context or direction to guide the response effectively while allowing for creative interpretation and flexibility. So again, the prompt is is important about prompts going to.
Probably not give you the results that you want and another pitfall, which, to me is probably 1 of the most frightening is that whatever you enter or upload into generated ai tools.
Becomes a part of it's corpus, right? So, and I've been looking at all of the tools that are out there for privacy security statements and.
It's really difficult. I would imagine I don't have any paid versions, but even if you do pay for it.
I think that your, um, your information, the information that's being put in there.
Put into to get responses your prompts or whatever, or your, if you're uploading documents or videos and saying summarizes, um.
That they're going to it's it's again becoming part of it's Corpus so, um.
Be mindful of that right? Um, I, I hear people say no yeah, I had, uh, write me my resume. I uploaded all my information. Well, guess what now that's that's out there that's in there, right? Um.
There probably are some I've seen, like, I think Amazon, the, their web solutions.
Has tools that you can bring into your institution, your Corporation, whatever it is, and upload your data and then they.
Explicitly say that there's some type of.
Privacy with that information that that it's digesting ingesting right?
But unless you see it explicitly presume that it's going to be that you're just helping to feed the monster.
And as it also mentioned in the video, there are hallucinations. So ask AI, what's the hallucination? It refers to the generation of seemingly coherent, but nonsensical or surreal outputs by ai models.
Often, resulting from the model extrapolating beyond its training data.
Or accounting, ambiguous or incomplete input. So, again, that trading data, that is.
You know, the worldwide web, everything that it's scraping all, you know, this large amounts of data. Um, it's just extrapolating it incorrectly. And Here's 1 example that I found that was very specific to libraries. Um, this was a Tweet.
That somebody else had shared at some point, and it says, uh.
That there's apparently this economic paper that is the most cited paper of all times, a theory of economic history and it's.
And in until library services, occasionally we've been seeing this, we'll have somebody request something and we dig, dig, dig, dig in. It turns out that it was probably also fake. So, um, to the best of our.
Research abilities. Okay.
So, then the next step is, you know, exploring some of these tools. And again, here, I'm going to try to go to the web page, but if not, I have screen shots.
1 thing that is good to start in your learning, is that chat is just 1.
Cool right. A lot of people say, you know, refer to chat if it's the whole, it's, it's really generative AI.
That is the, the bigger, um, Box right? And is just 1 of those.
Programs that is a general.
Application right so, and not that you need to know what genative pretrained Transformer is, but that's what stands for.
And there are a lot of API tools out there. In fact, there's a.
Webpage called there's an API for that.
And you can see that it says right up here at the top there's like, 13000.
Or almost, you know, 16,500 tasks and 5,000 jobs. So.
If you're curious as for any specific type of task that you have in mind, and you can scroll through this. There is an API for that.
Um, and you will find all kinds of things, you know, image ones.
You know, job tools, all kinds of things. Mm. Hmm.
Okay, see.
Okay, um, specifically for the library in the classroom, uh, somebody shared with me this.
A, I tool called research rabbit, which visualizes research? Um, hopefully again, the page is going to load.
And this is this is their video, so they're showing basically.
Um, entering a journal title bibliographic information.
And it'll give you similar articles on that topic. It'll it can expand out on the authors. It can tell you who else is working on it. So.
It is, I think there's a free version, but probably more useful. If you had a paid version.
Right. To to save your data um.
But that 1 looks looked interesting to me again, for the purposes of.
Library specific type work and this was shared with me too. Perplexity. So perplexity is another AI, you know, along the lines of chat.
And what I liked about perplexity is that it actually gives you some citation information. So.
I did a search over here.
I said in 5 short bullets, how can library media specialist learn about ai? And it gave me.
The bullets, but it also gives you sources.
Which is nice and if I ask another question, let me just say.
Should I ask a.
Why is her black city?
A good tool. I don't know. I just.
Pop that up so it's gonna respond sometimes what it does. It'll give you like a an infographic of the responses, which is what I used in the PowerPoint. Um, I don't know.
At what point? So Here's getting started with complexity for educators again. It gives you some sources.
That's kind of a a neat tool, but when I, um.
I don't know what prompt I put in because again I'm still learning. Right? But it gave me this infographic and I thought well, that's kind of neat, right? I put what are they use? Maybe that's what I put in. What are the users of complexity? I and I said research understand topics citations, generate an outline.
And then 1 that you may or may not be familiar with is called down E.
And again, I'm going to open this 1 this 1 again, because it's.
Not a paid account. What I.
You have limited amount of prompts that you can ask. In fact, I saw this the other day that that is actually going to a paid version, but I can do something like, um.
Create an image.
A black dog.
With a red color sitting.
On a.
Blue couch looking.
Out a window generate, let it do its thinking.
While it's thinking, it just gives you some, uh, prompts that other people have put in.
So, like, you can see right there and dropped lounging in a tropical resort in space.
And these are, this is what it gave me with my prompt.
So, pretty good now, I could have been more specific instead of black Labrador. I could have said, a black sheep, and it would have.
It would have generated that probably a little bit. Um.
Post it to what I had in my head, but again, you have to just provide more information.
So, dolly, like I said is is 1 of those that was free, but apparently they're going to a paid version. You get credits I think.
And how do you stay informed? So, I think I mentioned to you that I, that I, uh, CO started a community of interest in the Yukon library. And what we did is, we just set it up that every 2 weeks on a Thursday. Anybody that wants to come and join us can just come and talk about about AI and we practice.
Our discussion by saying, we're not a podcast. We are actually not here to teach you. We will share what we know, but we really want everybody to share what they know they're learning as well. What their tools are using.
And it's been a really great discussion. Sometimes it's 5 people. Sometimes it's 12 that come, it's all online virtual. Um, and and people will just share what they've been using it for. We've had, uh, some of our catalog and librarians talk about how they extracted data from Omaha in an Excel report, and then had, um.
Had it separate some of the values that were were important to her for something some data that she was trying to gather that alma couldn't do.
There have been some really interesting projects that librarians have have done in applying AI.
Um, and that was from the, and again, this was the results that, um.
Complexity gave us of what you can do attend webinars.
Follow experts, you know, learn, learn the language, keep philosophy. Right. Uh, use it for everyday tasks if you can just so that you're saying.
Um, active with the tools and explore.
Deep fakes and images.
And, of course, that eventually follows along with copyright, there's, there's a lot a lot.
Every 1 of these topics, you could just spending, you know, a lot of professional development on but, um, it just, you know, touch it a little bit here at a time. And, and and it will.
Eventually start to you'll start to feel more confident with it.
And this was just a podcast that I happened to come across um, and it was called AI in the school library again, very, a little bit more specific to what you're doing and you might find it. I found it interesting. I thought she had some some good resources there that might even be where I saw perplexity.
And that's it. So, um, again, just trying to give you an overview of what a I, is.
Trying to encourage you and hopefully see that that some of these tools are really fun and easy to use and can be.
Explored so that you feel more confident in using in general.
And to always be aware of the pitfalls, there's, you know, the, where the data's coming from the hallucinations, the bias.
All of that and the privacy that's that's again. Huge.
He was there, but that's that's all I have. Um.
Does anybody have any questions? Okay, well, it looks like Sarah wrote in there that perplexity is is good, because it doesn't call it data. That's good to know.
Are you put your hand hand up? Did you have a question.
Hello.
No, Sarah. Sorry. Good question here.
Up there.
Oh, okay thanks. So so sorry about that we'll get that video up. Um.
And see it, um, oh, definitely. I'll get you the video.
Yeah, sorry about that. It was it was a good video. It's quick. It's just, I mean, the audio, it probably was.
Explain what was going on as well what's the point?
I had a question for that, um, library, media specialist. Um.
How how you're seeing a I being used in the high schools, and if you're, um, encouraging it.
And all in and what what points of it are you encouraging.
Anyone has any insight on that, and I'm really curious about how it's being used at that level.
I know in the, in the that's actually been a topic, you know, how, how.
Is it being used in the classrooms? How professors feel about it? I attended a focus group with the University.
Um, with faculty, and there was some faculty that are.
That are still really hesitant about a I, no, not in my classroom and then there's others that are have embraced it and are incorporating it.
And really seeing a, as a tool, you know, it's not, it's not there to do your work, but it can certainly support it.
But there are ways to use it still.
Um, without providing personal information, by doing these generically, the catch all will be in creating an account that that, in and of itself right. Is providing data.
Um, yeah, I would, I, I would really like to see the university Yukon.
To have some type of paid accounts that we can explore this with so that we don't have to divulge all our price. It should.
Oh, that's cool. Annie. And he says she's used it with video journalism classes to generate scripts.
And on Facebook trailers that's great. Yeah.
Yeah, it's it's I yeah, I I forgot about the, the each 1 that's in the in the data privacy, but, um.
You know, there's good to it too, and we struggle with the same things, you know, at Yukon um, you know, it's good for some things and terrible for others. So, you know, just trying to figure out that balance, you know, students are going to use it.
I could stop them and the, the detectors aren't great. So trying to figure out how to embrace it just like.
We embraced lots of things that were new Wikipedia. You weren't you weren't allowed to cite Wikipedia, you know, so, so trying to figure out ways to kind of embrace the technology and figure out how to use it for.
And I and I do know that, um, in the page chat version.
Um, again, so, privacy issues and other concerns, but it does provide you, you can have, it gives you the sources.
And citations in the same way, that perplexity it.
So, if somebody's used, uh, heather's use illicit and research rabbit with an AP research students in finding academic research studies.
Perplexity also has been used as a place to start with our freshman, doing a research project on climate change.
And there is, you know, a, I is built into so many of the tools that we do have license to. So, even if you.
You know, if your school has license to something like canvas or other products, maybe even dig in and find out what's the AI component of that? And how can you share that with your students?
30, so we're right we're right against time. So there's no other questions for Terry. Terry, thank you so much. This is I learned a lot. This is, this is great. Thank you so much.
Um, we will have again, um, short, short.
And we will see back here at 10040.
Um, with robots who will look at, um, searching, fundamental so, strategic searching right? So we will see you all soon. Thank you. Thanks here.