2023 AI Symposium: AI at the Intersection of Teaching, Learning, and the Future
Thank you for attending what we hope will be the first of many Artificial Intelligence (AI) summits at Miami. We would also once again like to thank the many university departments and organizations who pitched in to make this event happen, including IT Services, Associated Student Government, the Office of the President, and University Communications and Marketing.
Keynote Speaker: Greg Simpson
Former Chief Technology Officer, Synchrony and GE
Author of The Quantum Contingent
Greg had an extensive IT career that spanned more than 37 years. Early on in his career, Greg served in several GE business CTO roles, including GE's Healthcare, Aviation, and Lighting businesses. Greg also was the CIO for a major GE Healthcare acquisition and previously served as Commercial Quality leader for GE Lighting, where he led Six Sigma initiatives including the implementation of one of the first web-based order tracking/status systems at GE.
In 2005, Greg became the Chief Technology Officer for all of GE where he created the shared services infrastructure team that supported all GE businesses. In his role as GE’s CTO, Greg advised GE’s CIO and the business CIOs on new technology directions. The “service business” Greg created leveraged GE’s scale to increase controllership and decrease cost as well as facilitated better collaboration across GE through common solutions.
In 2014, Greg went to GE Capital to work on the IPO and full spin-off of the GE Capital Consumer business, ultimately staying on as CTO for the new business, Synchrony.
Greg Simpson retired from Synchrony in March of 2021 where he had been Senior Vice President and Chief Technology Officer. In addition to his CTO role, Greg had been the AI leader for Synchrony since 2017. Greg worked closely with Synchrony’s CIO on developing the company’s technology strategy and was responsible for the Technology Committee of the Board. Greg oversaw a large global team, responsible for things ranging from Technology Engineering and Operations to Data Engineering and AI. He was a thought leader for how technology would change the company going forward and initiated activities to advance their use of AI and other emerging technologies.
Greg has been a frequent presenter and moderator at industry events and has been quoted in the Wall Street Journal, USA Today, and other national media. Most recently, Greg leveraged his technology knowledge and global travels to write a spy novel titled, The Quantum Contingent.
Greg received his BSME from Purdue University and his MSME from Case Western Reserve University. He resides in Loveland, Ohio with his wife and has 2 adult children.
2023 AI Symposium Presenters
Read MoreSymposium Schedule and Presentation Descriptions
9 - 9:50 a.m. Sessions
Implications of AI Tools for Writing and Literacy
Presenter: Mandy Olejnik and Rena Perez
Track: Policy, Law, and Changing Pedagogy
Room: ASC 1086
AI: The Future of Creative Teaching and Learning is Now
Presenter: Ann Mackenzie and Todd Edwards
Track: Academic
Room: ASC 2080
Beyond Traditional Methods: Generative AI's Impact on STEM Pedagogy, Research, and Innovation
Presenters: Josh Ferris, Rayna Xu, Jay Shan, and Fadel Megahed
Track: General AI
Room: ASC 1062
10 - 10:50 a.m. Sessions
Generative AI and IP: Frenemies or BFFs?
Presenter: Carla Myers
Track: Policy, Law, and Changing Pedagogy
Room: ASC 1086
AI in Academia: Speeding Up Curriculum Development and Filling Learning Gaps
Presenters: Cara Spray and Addrienne VanOver
Track: Academic
Room: ASC 2080
Writing with Generative AI and Human-Machine Teaming: Insights and Recommendations from Faculty and Students
Presenter: Heidi A. McKee, Andelyn Bedington, Emma Halcomb, and Thomas Sargent
Track: General AI
Room: ASC 1062
11 a.m. Keynote Address
The Art of Generative AI, Unleashing Creativity and Innovation
Greg Simpson
Harry T. Wilks Theatre
12 p.m. Lunch and Conversations
Pavilion
1 - 1:50 p.m. Sessions
Academic Integrity Considerations with Artificial Intelligence Use
Presenter: Brenda Quaye
Track: Policy, Law, and Changing Pedagogy
Room: ASC 1086
With ChatGPT Do We Have to Rewrite our Learning Objectives? Case Study in Cybersecurity
Presenters: Dhananjai Rao, Suman Bhunia, Peter Jamieson
Track: Academic
Room: ASC 2080
ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience
Presenter: Rayna Xu
Track: General AI
Room: ASC 1062
2 - 2:50 p.m. Sessions
Those AI Chatbots are so Dumb: Conflating Text, Conversation, and the Speech Act
Presenters: Bruce Murray and Garrison LeMasters
Track: Policy, Law, and Changing Pedagogy
Room: ASC 1086
Generative AI as a Faculty Friend? Using AI for Course Development and Outcomes
Presenter: Bonnie Erwin, Jenny Culbertson, and Mike Stram
Track: Academic
Room: ASC 2080
Security Risks of AI Models: Diving into Adversarial Attacks and Prompt Injection
Presenters: James Walden and Samer Khamaisah
Track: General AI
Room: ASC 1062
3 - 3:50 p.m. Sessions
A ChatGPT Powered Smart Chatbot for Library Online Services
Presenters: Meng Qu, Aayog Koirala, and Nhut (Steven) Do
Track: Policy, Law, and Changing Pedagogy
Room: ASC 1086
What I Learned from Assigning Generative AI and How You Can Do It Too
Presenter: Dennis Cheatham
Track: Academic
Room: ASC 2080
Critical Media Ecological Perspective on AI
Presenter: Bernadette Bowen
Track: General AI
Room: ASC 1062
Policy, Law, and Changing Pedagogy
Implications of AI Tools for Writing and Literacy (9 a.m.)
Generative AI and IP: Frenemies or BFFs? (10 a.m.)
Academic Integrity Considerations with Artificial Intelligence Use (1 p.m.)
Those AI Chatbots are so Dumb: Conflating Text, Conversation, and the Speech Act (2 p.m.)
A ChatGPT Powered Smart Chatbot for Library Online Services (3 p.m.)
Academic
AI: The Future of Creative Teaching and Learning is Now (9 a.m.)
AI in Academia: Speeding Up Curriculum Development and Filling Learning Gaps (10 a.m.)
With ChatGPT Do We Have to Rewrite our Learning Objectives? Case Study in Cybersecurity (1 p.m.)
Generative AI as a Faculty Friend? Using AI for Course Development and Outcomes (2 p.m.)
What I Learned from Assigning Generative AI and How You Can Do It Too (3 p.m.)
General AI
Beyond Traditional Methods: Generative AI's Impact on STEM Pedagogy, Research, and Innovation (9 a.m.)
Writing with Generative AI and Human-Machine Teaming: Insights and Recommendations from Faculty and Students (10 a.m.)
ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience (1 p.m.)
Security Risks of AI Models: Diving into Adversarial Attacks
and Prompt Injection (2 p.m.)
Critical Media Ecological Perspective on AI (3 p.m.)
Keynote: The Art of Generative AI, Unleashing Creativity and Innovation
Greg Simpson
Academic Integrity Considerations with Artificial Intelligence Use
Brenda Quaye
In this session, I will discuss how AI usage is considered under the academic integrity policy and what both students and instructors need to know about AI with regard to academic integrity (how to talk about it, why it may or may not be allowed). I also will discuss the issues that I have seen in academic integrity cases involving artificial intelligence including the reliability of the AI detectors, why students are using AI in an inappropriate or unauthorized manner, the confusion that exists about the technology, and how writing assistive AI may be problematic. Finally, I will discuss potential appropriate ways to use AI and how this can be communicated within courses. The target audience is both instructors and students, and staff who support students.
AI: The Future of Creative Teaching and Learning is Now
Ann Mackenzie and Todd Edwards
The session will be comprised of two parts: We'll begin with an exploration of creative projects and assignments that can be done with AI tools. The second part will focus on engaging our colleagues in consideration of things to contemplate in using AI in the post-secondary classroom. Target Audience- all faculty. Overview of content: Suggested creative projects and assignments using AI will be demonstrated and time given for our colleagues to try them using AI tools. The second part will be conversational and will focus on considerations of things to contemplate in using AI, e.g. assessment, ethical considerations, and bias that exists in AI (DEI focus).
AI in Academia: Speeding Up Curriculum Development and Filling Learning Gaps
Cara Spray and Addrienne VanOver
Are you an educator, instructional designer, or administrator curious about the future of teaching? This session is tailored just for you. In this session, we’ll be exploring how AI can take your curriculum planning and gap analysis to the next level. Our goal is to show you how tech-savvy solutions can make your work not just easier, but also more impactful.
We'll delve into the AI tools that are changing the game, simplifying tasks that used to be time-consuming and complex. These tools can help you craft a curriculum that really resonates with students and fills in learning gaps more effectively. You'll walk away with a clear understanding of how technology can be a powerful ally in creating dynamic and meaningful educational experiences.
So, whether you're tech-savvy or a tech-curious educator, join us as we bridge the old with the new and pave the way for a future where technology and teaching go hand in hand.
A ChatGPT Powered Smart Chatbot for Library Online Services
Meng Qu, Aayog Koirala, and Nhut (Steven) Do
As the popularity of ChatGPT surged, academic libraries began exploring manners to integrate ChatGPT into the library's existing Integrated Library System (ILS). This presentation will introduce the ChatGPT-powered Smart Chatbot, a web-based application developed at Miami University Libraries, which functions as an auto-answering chatbot with 24/7 availability. The chatbot employs a frontend user interface to solicit text inputs from users and provides text outputs generated by the underlying bot. Leveraging the ChatGPT API, the system processes user inputs and subsequently delegates tasks to designated virtual agents specialized in distinct service domains. Each virtual agent is tailored to accomplish specific tasks within predefined service categories. The chatbot proficiently addresses queries related to various ILS API-interactable tasks, encompassing searches for online resources, reservations of study rooms, recommendations for subject guides, citation assistance, and more.
The target audience for this proposal includes academic librarians, university administrators, educators, researchers in artificial intelligence, technology developers, information science professionals, and participants interested in the integration of AI into educational and library systems. Other potential readers could be anyone involved in the design and development of educational applications or library systems, AI enthusiasts, and anyone interested in improving user experiences and customer service using AI technology. Also, the proposal would be of interest to students in AI, information technology, library science, and education.
Beyond Traditional Methods: Generative AI's Impact on STEM Pedagogy, Research, and Innovation
Josh Ferris, Rayna Xu, Jay Shan, and Fadel Megahed
In this panel, we aim to delve deep into the transformative potential of generative AI within STEM disciplines. Targeting MU faculty, students, IT staff, and industry professionals, our panelists will introduce the capabilities of generative AI, its real-world classroom applications, and its pivotal role in contemporary research. Beyond each panelist's short introduction/presentation, we anticipate a robust and interactive discussion with our audience, addressing current use cases, and ethical considerations of generative AI in STEM and exploring its future trajectory. Our vision is to provide insights and actively engage attendees in a dialogue about the profound impact and opportunities of generative AI in STEM.
ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience
Rayna Xu
Target audience: Anyone who is interested in the impact of large language models on the search market.
Overview of content: The advent of ChatGPT, a large language model-powered chatbot, has prompted questions about its potential implications for traditional search engines. In this study, we investigate the differences in user behavior when employing search engines and chatbot tools for varied information-seeking tasks and explore the synthetic use of both tools by conducting two online randomized experiments.
Critical Media Ecological Perspective on AI
Bernadette Bowen
In recent years, my research has fallen (joyfully and carefully) into an interdisciplinary field called “media ecology”. For those unfamiliar, the theory and practices of media ecology mean a lot of different things to a lot of different people. But, to make myself more mediatingly clear, traditional media ecologists study the ways in which the introduction of any type of media make differences in our lives, that make other differences, environmentally. In other words, we observe and document what happens when -- any type of -- technology, from the biggest to the seemingly most insignificant, is introduced into our overall interlocking ecologies. Then, we wait to see if we were onto something. Perspectively, what distinguishes media ecologists from other researchers is a view that any one “medium” or “media” is an (and inclines other) environmental process. Thus, when taking advantage of this approach, you can focus on just about anything you want. However, in a more traditional sense, you would do so by questioning, breaking down, and reporting on the ways in which any one mediation of your choice inclines users (physically, structurally, and more...).
Since 2019, some colleagues and I "added a little spice" to this lens, and began what has since been referred to as the wave of “gender and media ecology” (Most recently, I've argued that this term is too limited, and that "critical media ecology" would more appropriate). As such, in efforts to advance the field, we began marrying critical cultural concepts with the more traditional approach. And we continue to do so, balancing out the range of traditional approaches with vastly rich insights of gender (and now bodily-ability, race, biological sex, ethnicity, class, etc.) studies, that had been missing from the field, except for a few inspiring scholar's work, like Dr. Sharma. And, despite our very human inclinations toward a loss of overall technological scope, we are now currently living through a monumental time where this fact is finally being revealed to us, for the first time in human ze-story, her-story, they-story, or even, his-story.
- Brief Background on Who I Am (one of the first critical media ecologists, as well as a content creator who now shares their work to my 30,000+ followers)
- Brief Background of Media Ecology (canon, approach, recent work, and ideas)
- Humanness, Authorship, Authority
- Implications of AI
- What We Can Do About It (citizens, educators, students, etc.)
Generative AI and IP: Frenemies or BFFs?
Carla Myers
Generative AI reuses a variety of works protected by intellectual property (IP) law, including copyright, trademarks, and patents. These legal issues include ownership of the computer code empowering generative AI engines, the protected works being used by the engines in the creation of new works, and IP ownership and liability considerations associated with the use of the final output. In this session, we'll take a look at all of these considerations and discuss the ways users are currently navigating them.
Generative AI as a Faculty Friend? Using AI for Course Development and Outcomes
Bonnie Erwin, Jenny Culbertson, and Mike Stram
In our session, we will teach participants how to use Generative AI when designing a new course from scratch, specifically to create a course outline and Learning Outcomes (sometimes referred to as Learning Objectives). Even though faculty are experts in the subject matter they teach, they often find it tedious and stressful to map out a course and create Learning Outcomes. In fact, Learning Designers at Miami Online often hear from faculty that these are their most hated tasks when approaching a new course, or a course redesign. It can be difficult to key outcomes to the appropriate difficulty level on Bloom’s Taxonomy, and it can be frustrating to align modules and module-level outcomes with course-level outcomes. In this session, participants will learn how to let AI do the “grunt work,” freeing up faculty time and creativity for the more rewarding parts of course planning. Of course, while AI can give ideas to get a course started, we know that the true value-added comes from faculty expertise: we’ll discuss how revising and building on AI-assisted brainstorming can create a course that is both unique and rigorous.
We will give an overview of strategies for using Generative AI in course outline and outcomes design, and then we’ll take a discussion break where participants can share reactions and work together to create best practices for building on AI brainstorming with the human “value add.”
Following the discussion break, we’ll lead participants in active practice. Attendees will have a chance to try out what they learn on a course design of their own and share tips and tricks with one another as they learn.
Implications of AI Tools for Writing and Literacy
Mandy Olejnik and Rena Perez
Drawing on scholarship from the fields of writing studies and education, this session overviews the affordances and constraints of LLMs like ChatGPT and Google Bard in teaching and learning, especially relating to writing. Our target audience for this session is any faculty, staff, and students who may use such AI tools in the classroom (either for themselves as learners or to assist in their teaching). In this session, we will walk through scenarios of how ChatGPT in particular can be used to assist writing (and not outright replace it) as well as open discussion for some of the ethical concerns that remain around the usage and production of these tools. Overall, we argue that AI tools have the capacity to support learning in the classroom and that there are some serious ethical considerations to make around these usages.
Security Risks of AI Models: Diving into Adversarial Attacks and Prompt Injection
James Walden and Samer Khamaisah
In the rapidly evolving landscape of artificial intelligence, understanding cybersecurity implications is essential before deploying a model to the public. This talk aims to demystify the security challenges associated with AI models, with an in-depth focus on adversarial attacks and prompt injection. We will explore how AI models, especially LLMs, are susceptible to attacks that can lead the models to reveal confidential information or perform malicious actions. We will look at examples of attacks in both language and image models.
Those AI Chatbots are so Dumb: Conflating Text, Conversation, and the Speech Act
Bruce Murray and Garrison LeMasters
For philosopher John Searle and others, the "declarative" Speech Act -- a kind of "illocutionary act" whereby "you make something the case by representing it as being the case" -- is unique to homo sapiens. Even better, these declarations are the foundation of "human institutional civilization." Odd as it may seem, then, even curses like "[may the devil] $%&# you" -- illocutionary declarations -- help give our species its staying power. But ChatGPT is literally incapable of cursing us, not because of its programming, but because it lacks intention.
What I Learned from Assigning Generative AI and How You Can Do It Too
Dennis Cheatham
I assigned design students to use ChatGPT and DALL·E 2 in a 200-level Interaction Design course in Spring 2023. Students wrote prompts to create images and text for an open-ended digital storytelling website project and learned these Generative AI tools through use. I will share details about my experience in this session, including assignment parameters, the in-class process, work outcomes, and what I am learning about implementing Generative AI into my teaching. Participants in this session will gain insights into how they can integrate Generative AI use into their assignments through an interactive discussion. We will map Generative AI tool strengths to various course activities that participants share—producing a resource to assist in developing coursework that activates Generative AI skill building and responsible use.
Some content in this session inspired the development of CCA 190, “Creating With Artificial Intelligence: Shaping the Future,” which I will teach in Spring 2024.
With ChatGPT Do We Have to Rewrite our Learning Objectives? Case Study in Cybersecurity
Dhananjai Rao, Suman Bhunia, Peter Jamieson
With the emergence of Artificial Intelligent chatbot tools such as ChatGPT and code writing AI tools such as GitHub Copilot, educators need to question what and how we should teach our courses and curricula in the future. In reality, automated tools may result in certain academic fields being deeply reduced in the number of employable people. In this work, we make a case study of cybersecurity undergrad education by using the lens of “Understanding by Design” (UbD). First, we provide a broad understanding of learning objectives (LOs) in cybersecurity from a computer science perspective. Next, we dig a little deeper into a curriculum with an undergraduate emphasis on cybersecurity and examine the major courses and their LOs for our cybersecurity program at Miami University. With these details, we perform a thought experiment on how attainable the LOs are with the above-described tools, asking the key question “What needs to be enduring concepts?” learned in this process. If an LO becomes something that the existence of automation tools might be able to do, we then ask “What level is attainable for the LO that is not a simple query to the tools?”. With this exercise, we hope to establish an example of how to prompt ChatGPT to accelerate students in their achievements of LOs given the existence of these new AI tools, and our goal is to push all of us to leverage and teach these tools as powerful allies in our quest to improve human existence and knowledge.
Writing with Generative AI and Human-Machine Teaming: Insights and Recommendations from Faculty and Students
Heidi A. McKee, Andelyn Bedington, Emma Halcomb, and Thomas Sargent
Presentation followed by extended discussion with attendees on processes for writing and teaming with generative AI for writing; three undergraduate students and one faculty member will share and discuss their experiences, drawing from semester-long usage of ChatGPT in a Professional Writing for Healthcare course and also discussing uses in other classes and contexts.
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