The primary goal of the workshop was not to teach participants how to “master” AI image tools, but rather to help them ask better questions about what they were seeing and creating. The workshop was designed to help participants identify and evaluate visual indicators commonly associated with AI-generated images and videos, apply AI detection tools, explain the basics of AI image generation, and consider the environmental impact of the technologies involved.  Because the library is open to the public, the workshop was intentionally promoted beyond campus audiences. Details were included in the university’s “Passport to Programming” brochure, which is mailed twice a year to both university affiliates and community members, and shared through campus flyers and listservs. This multi-channel approach supported the library’s goal of providing accessible technology education to a broad audience.

The presentation for this workshop was created in Google Slides. In preparation for the workshop, I collected AI-generated images encountered through social media and advertising and incorporated them into the presentation alongside guidance on common indicators of AI-generation. Participants worked through these examples together, identifying anomalies such as distorted hands or limbs, inconsistent lighting or shadows, and unreadable or nonsensical text.  I found various videos on TikTok that asked, “Which one is AI?”, comparing a real video to an AI created video. I was then able to download these into the presentation which provided a fun way to get participant interaction. The final portion of the workshop gave participants a chance to create an AI image using one of several available options including FreeP!c, ChatGPT, and Canva. This activity helped participants understand how prompts shape AI-generated images and encouraged them to think more critically about how images they encounter elsewhere may have been produced.  The presentation ended with a disclaimer about the impacts of data centers on communities and the environment.  

The workshop overall was a success. There was higher attendance than most workshops held that semester. Participation was also strong, with many attendees becoming more animated during the “spot the AI” games.  The interactive nature of the activities appeared to lower intimidation barriers and encouraged participants to engage more openly with an emerging technology they had previously viewed as opaque or inaccessible. Several participants were excited to share their AI creations, which included a student that created concept cover art for the book they are writing and a community member that created an image of their pet as a cartoon.  Due to the popularity of this session, it has been scheduled to repeat during the next semester. 

Although the initial workshop was successful, the rapid pace of change in generative AI necessitates regular updates to both content and examples. Future iterations will include expanded discussion of copyright, artistic labor, and the impact of AI-generated art on creative professions. Developing this workshop proved informative not only for participants, but for me as well, as the research required deepened my own understanding of AI-generated images and videos. One key improvement for future sessions will be sourcing higher-quality comparison videos, as lower-resolution clips made it more difficult to distinguish between real and AI-generated content. Overall, this workshop demonstrates how academic libraries can respond thoughtfully to emerging technologies while centering critical inquiry, ethical awareness, and community engagement.