How I use generative AI in my work

How I use generative AI in my work

I’ve heard a few people say that generative AI tools are fun for entertainment only, and not really useful for work.

However, I DO find these tools useful. Very useful!

I’m an eLearning developer for the University of Arizona Libraries and I work in the Instructional Design & eLearning unit.

These are the tools I use: ChatGPT Plus, Claude, Bing Chat, and Perplexity AI. For image generation I use Adobe Firefly, AI tools in Canva, and DALL-E 3 in ChatGPT Plus.

Here are some ways I use them.

 

1. Coming up with examples

ChatGPT is very good at coming up with examples. I’ve asked it for:

– Examples of discriminative AI vs generative AI for this tutorial.

– Examples of people mapping old technology concepts to new ones, in a way that causes misconceptions – for a talk I was giving.

– Examples of AI in sci-fi movies, to use for a scene in this tutorial video about ChatGPT.

– Examples of different writing styles – for use in a webinar I offered. (Make my writing more: “formal, persuasive, academic, descriptive, humorous, technical”).

– Examples of how ChatGPT can give you output as emojis, for that same webinar. (I asked it for the plot of Avatar: Way of Water as emojis).

 

2. Understanding new terms and concepts

I used ChatGPT Plus for these, since it’s more capable than the free ChatGPT.

– It helped me understand the process of “reinforcement learning with human feedback,” so I could put it in simple terms in our tutorial.

– It helped me understand more about how generative AI models are trained. See this example: After a model is trained with vast amounts of text, is that data no longer needed?

– It helped me understand embeddings. Here’s what I asked.
In the field of artificial intelligence, what are embeddings? I’d like a very basic definition for beginners.

For all of these, since it might hallucinate, I verified what I learned with other sources. But it really helped to have simple definitions and explanations as a starting point.

 

3. Writing plausible-sounding wrong answers to multiple choice questions

We write multiple choice quiz questions for our tutorials. Sometimes it’s difficult to think of wrong answers that sound plausible to use for the incorrect choices. ChatGPT is great at making things up and sounding plausible!  I used it for a couple of questions in this tutorial about ChatGPT.

 

4. Generating sample prompts

In a talk I gave about ChatGPT, I used it to come up with prompt examples for showing results with and without gender stereotypes.

And I wanted an example of what this more complex prompt might output. This was for a talk I gave to UA writing instructors.

 

5. Help with writing a conference proposal

ChatGPT helped me write a brief description for a session proposal that several colleagues and I were submitting for an upcoming conference. I didn’t use what it wrote verbatim, instead I edited and combined it with my own words. It was a useful starting point.

 

6. Summarizing & asking questions of a very large PDF document

I often want to get information from very long reports or research papers. Claude is very useful for generating summaries of these. Just upload a PDF and say, “please summarize this.” Claude has a much larger context window than ChatGPT, so you can work with very large documents (up to about 75,000 words).

 

7. Creating a bar graph from uploaded data

Using Advanced Data Analysis from ChatGPT Plus, I had it generate a bar graph from data that shows page views of our Libguides from last summer. I just uploaded the .csv file, and asked it to make a bar graph from it. I added the numbers for two of the guides manually (since we were discussing those particular guides). I showed the graph at an all-staff meeting. This was much quicker than using Excel.

Bar graph showing page view of the top 15 libguides from summer 2023.
Click to expand this image.

 

8. Working with data and creating an HTML table

I used Advanced Data Analysis from ChatGPT Plus to generate HTML and CSS for the tables on these pages that show user feedback from our tutorials. I uploaded a .csv file from our anonymous user feedback surveys. I told it to remove the rows that didn’t contain any comments from users, then show only the 200 most recent rows, Then I asked it to make the HTML and CSS for a table with every other row light gray, and with column headings I assigned. It gave me a link to download, I tested it locally in my browser, then pasted the code in my libguide page. I did this for data sets from 8 different tutorials. it was much quicker than using Excel and coding the CSS myself!

 

9. Generating code

I asked Advanced Data Analysis from ChatGPT Plus to write me code for a simple Pong game to run in a browser. I then used the example in one of our tutorial videos. I downloaded the code it made, tested it locally in my browser. Then I made a little video by screen capturing it. After that I converted that video to an animated GIF for this page.

clip of a movie turned into a GIF (Pong code generated by ChatGPT)
Click on this image to see the full animation.

 

10. Getting a transcript of a YouTube video that didn’t have one

ChatGPT Plus has many plugins (some useful, some not). For this, I used the Vox Script plugin to get a transcript of a YouTube video. It only gave me chunks of it at a time, so I had to copy and paste it all together. There are many other third-party AI tools that do this, but I wanted to test this particular plugin.

 

11. Getting ideas for improving an infographic

A while ago I made this infographic about our process for instructional design. I used a template from Canva. With the new vision capabilities in ChatGPT Plus, I was able to upload the image and ask for advice on improving it. It gave excellent advice! I haven’t had time to remake the infographic yet, but when I do, I’ll use the design brief it gave me. (I can’t link to the response here because some parts of ChatGPT Plus don’t have the ability to make a shared link yet).

 

12. Creating an animated GIF from an image

I saw a presentation online where the presenter showed an image to help explain the concept of embeddings in generative AI. I wanted to use a similar image (but as an animated GIF to show in my future training sessions). I used ChatGPT Plus with Vision to describe the 2D image (after I uploaded it). Then I went to Advanced Data Analysis and used that description to have it recreate the image and then turn it into an animated GIF I could download. Here it is.

an image depicting a three-dimensional scatter plot with a dense cluster of red dots spread throughout the space. Among the sea of red dots, there is a single distinct blue dot. The axes of the plot are labeled from 0.0 to 1.0 at regular intervals. Above the scatter plot, the caption reads

Click on this image to see the full animation.

 

13. Creating the images for this blog post

I used the new DALL-E 3 (inside of ChatGPT Plus) to create the images for this post. It’s improved quite a bit since earlier versions! I still think MidJourney is the best, but I don’t want to pay for another tool when I’m already paying $20/month for ChatGPT Plus.

Since the default for DALL-E 3 is to make square images and I forgot to ask it to make landscape-oriented images, I took the two images I liked best and generated wider versions using Clipdrop’s Uncrop tool. That’s a free tool from Stability AI. And that’s why you see all the weird globe shapes in the image at top of this post. They’re a bit weird, but I like them! (I deleted many other versions that were too weird).

I also sometimes also use Adobe Firefly. I like all the options for styles of art, and the inspiration from images made by others.

 

 

14. Creating an AI-generated background for my own profile photo

Canva (which has been around for quite a while) has several generative AI features built in. I used it to upload a photo of myself, remove the background, and generate several other backgrounds to choose from. I ended up liking the forest background. You can see it on my bio page. If you look closely, you can see that the forest is not completely realistic, but I liked the effect. And since I’m so involved in teaching about AI these days, I thought it made sense to use something AI-generated for my profile. 🙂

 

Caveats

I know that many people have qualms about the ethical issues around these tools. Here are a few things that are good to know about.

a. If you’re worried about the ethics of image generation, Adobe Firefly is a good option (free or paid). They’ve trained their tool only on Adobe Stock images, openly licensed content, and public domain content. Learn more in their FAQs.

b. If you want to use DALL-E 3 for images, it’s good to know that it incorporates safety measures that restrict the generation of violent, adult, or hateful content. Also, it has guardrails in place to prevent generating images of public figures by name, which helps safeguard privacy and reduces the risk of misinformation.

See this from OpenAI: “In response, we added a refusal (see 1.1) which triggers when a user attempts to generate an image in the style of a living artist. We will also maintain a blocklist for living artist names which will be updated as required.” – From the DALL-E 3 System Card (PDF)

You can use DALL-E 3 in ChatGPT Plus or for free with Bing Image Creator.

c. Since ChatGPT can get things wrong sometimes (known as “hallucination”), I find it’s best used for tasks where you can easily recognize (or suspect) when something is wrong. Like most of the tasks above. Using it for something you’re not familiar with (like I did for #2), means that you’ll always need to verify what it tells you. But it’s still useful for getting you started with unfamiliar terms and concepts (even with the extra step of verification from other sources).

d. When a language model is connected to the Internet (like Bing Chat or Perplexity AI) it hallucinates less. That’s because it searches the web first, reads several results quickly, and uses the information on those pages as the basis for its summary. And it provides links to those websites, so you can easily check. So for situations where I would have used a Google search, I like to use these tools, because they summarize several sources quickly – which helps me decide which ones are worth looking at.

e. One more thing: Did you know you can easily tell ChatGPT not to use your input for training? It’s an easy toggle switch in the settings. See How do I turn off chat history and model training? I don’t turn it off myself, because I never enter confidential or private data into ChatGPT, and I’m fine with letting them using my inputs to make the model better. But if you feel strongly, you can easily turn it off.

 

Summary

So, as you can see, I find these tools useful in my day-to-day work. Maybe I use it more often than most because I’m creating webinars and tutorials about generative AI, but I think it could be useful for most jobs that involve working at a computer.

I hope this inspires you to think about ways you could use it in your work.

I didn’t use ChatGPT to help me write this post.😀

 

Generated with DALL-E 3 (ChatGPT Plus). The cat represents my cat, Max.

Evaluating generative AI tools for purchase: a checklist

Evaluating generative AI tools for purchase: a checklist

At academic libraries, we’re starting to get pitches from developers of various apps and software based on generative AI – pitches to purchase this software for our campus.

Because of that, I realized that it can be challenging to evaluate these tools. Especially since it may require having some knowledge of how the underlying technology works.

So I decided to draft a checklist for this purpose. You can download it here:
Evaluating Generative AI Tools: A Checklist. (PDF)

This is version 1.2, updated on Dec. 23, 2023. (first version was created in Oct. 2023)

It’s a starting point for thinking about what you might want to ask developers when considering a purchase. Your comments and feedback are welcome!


To learn more of the basics about generative AI, see our interactive tutorials on ChatGPT and Generative AI, from the University of Arizona Libraries.

And to stay current with the latest news about generative AI, follow me on any of these platforms. I post daily.

What’s next with ChatGPT?

What’s next with ChatGPT?

I recently heard someone ask, “What’s next with ChatGPT?” This was a person who doesn’t have time to follow the news about generative AI on a regular basis.

So for those who haven’t had time to keep up, here are some interesting developments.

I’m not aiming to predict the future (well maybe a little bit), only to summarize some news that might be of interest if you haven’t had time to keep up with this topic.

1. The free version of ChatGPT will connect to the internet, making hallucination a bit less of a problem. Currently a web connection is only available in the Plus version ($20/month)

2. Language models from Open AI, Microsoft, Google, and others will be incorporated in many tools that people already use (Microsoft Copilot for Windows 11, Google docs, etc). See also The AI revolution is about to take over your web browser.

3. Educators will find more ways to use it creatively with students in the classroom. And some are moving beyond worrying about students writing essays with ChatGPT. See AI detectors: Why I won’t use them. See also Why Is My Attitude Towards Generative AI Different From Previous AI in Education? And also 6 Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence.

4. The amount of text you can work with at one time will keep increasing, allowing you to work with the text of an entire book (Anthropic’s Claude already does this). You can summarize, outline, ask questions of the book, and so on.

5. Many more software tools and apps will continue to be created (some useful, some not) that use this technology (large language models). Some useful ones: Duolingo, Be My Eyes, Elicit: The AI Research Assistant, Explainpaper (for reading research papers), for just a few. See this TED Talk from Sal Khan, How AI could save (not destroy) education.

6. Plugins will be incorporated into Bing Chat and Google’s Bard. (The Plus version of ChatGPT already has plugins). However, they don’t always seem to work well yet. Listen to this podcast episode: Are ChatGPT Plugins Overhyped?

7. There will be some progress with making AI less biased and more multicultural. Some of the open source models  will do this (see BLOOM). Another model (not open source) that shows promise is Claude from Anthropic, with their method known as “constitutional AI.

8. Copyright issues will not be solved for a while, as it takes time for the courts to decide how to interpret the law. See this video for a summary: Generative AI Meets Copyright, by Pamela Samuelson, Professor of Law, UC Berkeley. See also this interesting development: Japan Goes All In: Copyright Doesn’t Apply To AI Training. Another article: Creative Commons makes the case that training AI models is fair use, see Fair Use: Training Generative AI.

9. Large companies will connect language models to their own knowledgebases (known as grounding), with very little or no hallucination. See Bloomberg Uses Its Vast Data To Create New Finance AI, and Introducing Healthcare-Specific Large Language Models from John Snow Labs, and Ethics of large language models in medicine and medical research.

10. Have you heard about autonomous agents? These are AIs that can work towards a goal that you set, and assign different tasks to other AIs. See Auto-GPT, BabyAGI, and AgentGPT: How to use AI agents and How to Use AgentGPT to Deploy AI Agents From Your Browser, and What is Auto-GPT and why does it matter?

11. And farther out in the future, there will be multi-sensory AI that can use multiple senses. See ImageBind from Meta. This open source model combines text, audio, visual, movement, thermal, and depth data. It’s only a research project for now, but you can imagine how this might work in future models.

12. If you’ve heard all the news of AI experts signing statements about risks of AI causing human extinction, you might wonder… is that another thing we need to worry about in addition to climate change and nuclear war? Here is the best response to that that I’ve read: Let’s talk about extinction by Azeem Ahzar. A good point he makes is that “just because people are experts in the core research of neural networks does not make them great forecasters, especially when it comes to societal questions or questions of the economy, or questions of geopolitics.”

13. And finally, people will continue to make serious mistakes in their use of ChatGPT, (until more people develop some degree of AI literacy). See Lawyer cites fake cases invented by ChatGPT, judge is not amused, and Professor Flunks All His Students After ChatGPT Falsely Claims It Wrote Their Papers.

This is why we all need AI Literacy. If you want to develop your own AI literacy (and teach others to do the same), take a look at my May 18 webinar recording, AI Literacy: Using ChatGPT and AI Tools in Instruction. See also the handout for many more sources.

I’ll be doing a similar webinar for AMICAL on June 21, and I’m also talking with ALA about a series of webinars for later this year.

Follow me on Twitter or Mastodon for daily links to AI news.

AI Literacy: May 17 webinar

AI Literacy: May 17 webinar

ChatGPT has been making headlines, with both positive and negative stories, including concerns about plagiarism and false information. You may not have had time to keep up with all the news, and you might be wondering how to separate the hype from the reality.

On May 17th I’m offering a webinar to address these topics. No matter where you fall on the spectrum between critic and enthusiast, it’s important for all of us these days to have basic AI literacy.

AI Literacy: Using ChatGPT and Artificial Intelligence Tools in Instruction
May 17 at 1:30 pm CDT via the American Library Association

In this webinar, you’ll learn why understanding AI tools (like ChatGPT & Bing Chat) is an important part of information literacy and something library staff should be learning about now.

After participating in this event, you will:

  • Understand the basics of ChatGPT and how it works
  • Know about the company behind it and the data that went into the product’s training
  • Know several examples of how to use ChatGPT and similar tools effectively
  • Understand some common criticisms of the technology and problems with it in its current form
  • Know some other tools and apps are available that use this technology

You’ll come away with:

  • A basic understanding of this technology (AI tools based on large language models).
  • Knowledge of why AI literacy is an important part of information literacy.
  • Inspiration & tips for offering workshops, guides, or handouts for your users on this topic.
  • A bibliography of best sources for learning more.

Bring your questions and comments! We’ll include time for discussion.

 

ALA Member Price: $71.10
Non Member Price: $79.00
Credit Type: Certificate Available upon Completion
Chat GPT FAQ

Chat GPT FAQ

In January, I put together a document to share with my department at the Univ. of Arizona Libraries (Student Learning and Engagement): Chat GPT FAQ.

It’s a work in progress – and I welcome your comments.

There are so many interesting questions about what these new tools means for education!  So I’m learning everything I can about this topic and planning a webinar for librarians.

Feel free to share the FAQ with others!

Webinar coming soon!

On May 17th I’ll be offering a webinar via the American Library Association: AI Literacy: Using ChatGPT and Artificial Intelligence Tools in Instruction.

It will focus on the importance of AI literacy for librarians – so we can help our users develop that same literacy.

You’ll learn why understanding AI tools (like ChatGPT) is a necessary part of information literacy and something library staff should be learning about now.

I’ll post more about the webinar soon – after ALA has announced it on their website.