Making AI Accessible with Learning Circles

Artificial Intelligence (AI) can be tricky to explain. The topic is complex, both in theory and in practice, and definitions vary wildly. Informational resources often require readers to have a basic understanding of computer science, resulting in barriers around who has a say in the systems that affect them.

As this technology evolves, so does its invisible influence on everyday life. If you regularly use the internet, AI has likely affected the things you read, buy, and watch. Increasingly, it is being used to help people make decisions in serious areas of life like hiring, education, and law enforcement, impacting many who aren’t aware of its involvement at all.

Professor Julia Stoyanovich, an Associate Professor at NYU’s Tandon School of Engineering and the co-founder and director of Center for Responsible AI (R/AI), recognized a growing need for accessible AI public education. Nearby at Queens Public Library, library staff noticed their patrons asking challenging questions about AI. Motivated to create a non-technical pathway into AI literacy, NYU and QPL reached out to the P2PU team to answer the following question: can peer-driven learning circles and open-access courseware bring AI literacy to new audiences? 

The resulting course—We Are AI—aims to introduce the basics of AI, explore some of the social and ethical dimensions of the use of AI in modern life, and empower individuals to engage with how AI is used and governed. In order to support widespread use, the 5-module course is designed to be run without an expert in the room, and it contains tips and suggested agendas for facilitating specific material with minimal preparation. The materials include a mix of materials to support varied learning styles and digital literacy: informational videos with accompanying comic books, exploratory activities, and discussion prompts. 

The content of the course was designed over the course of 3 months. Staff from each of the 3 organizations brought unique skill sets to the conversations: NYU’s content expertise, QPL’s knowledge of their community’s needs, and P2PU’s expertise developing resources for learning circles. 

Starting in a Google Doc, we collectively outlined the objectives and negotiated learning goals that seemed both substantial and achievable for a five-week course, based on a set of competencies that enables individuals to critically evaluate AI technologies. We agreed on a simple (but not simplistic) glossary of terms that we would use throughout the course, and we developed group activities that showcased both NYU research and peer learning principles. After finalizing the copy for the course, we moved everything into Course-in-a-Box, P2PU’s open source course builder, and worked with Falaah Arif Khan, who designed banner images and a supplemental series of comic books for each module of the course.

The extent of this process became the backbone of a new canonical resource, the Create a Course section of P2PU’s Knowledge Base. We encourage content experts around the world to adapt their expertise to the learning circle model! (Want some help? We’d love to work with you!)

Once the materials were completed, a group of 20 staff members from QPL were the first group to explore the new course. They met for 5 sessions to work through the materials as written and to give feedback about the content. Participants responded positively and enjoyed the opportunity to discuss current news with their colleagues and to understand some of the applications and ethics of AI:

  • “I often get questions [from patrons] about how and why advertisements on personal emails show up. Now I can give a better answer.”
  • “I learned that many of my co-workers have some of the same concerns as I do. I think [the course] reached its goal as an introduction to some of the issues with AI [and] it was a good format for individuals to listen and share insights.”
  • “The content is appropriate. Though not my expertise, I feel comfortable with the material.”

Queens Public Library ran a well-received pilot of the course for the public in June 2021 and will be running additional iterations of the course in the near future online and (hopefully) in-person. We Are AI is also uploaded on the P2PU learning resources page, so anyone can start a learning circle using the course today. If you’d like to try the course, or want help adapting your own expertise into a learning circle course, please reach out to

We Are AI is a dynamic collaboration between the Center for Responsible AI (R/AI) at New York University’s Tandon School of Engineering, Peer 2 Peer University (P2PU), and the Queens Public Library (QPL).

Course materials were developed under the leadership of Dr. Eric Corbett and Dr. Julia Stoyanovich, with input and participation of Dr. Mona Sloane, Falaah Arif Khan, Meghan McDermott from R/AI, Becky Margraf and Grif Peterson from P2PU, and Jeffrey Lambert, Sadie Coughlin-Prego, Kaven Vohra from QPL.

Course development was supported in part by NSF Awards No. 1934464 and 1916505.

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