AI and Education Policy Expertise Exchange

The AI and Education Policy Exchange was the first of CIRCLS’ AI Expertise Exchanges, running from March-June, 2021. The exchange took place bi-weekly over 7 sessions on Zoom, with a total involvement of 49 total community members. Participants represented multiple stakeholders including faculty members, graduate students, industry experts, K-12 teachers, and district representatives. The goals of the exchange were to: 1) Promote learning through a Speaker Series that brought community members together to share their knowledge and expertise related to AI and Education Policy, 2) Synthesize ideas to develop Community Resources surrounding AI and Education Policy issues, and 3) Effect change by converging on a set of Policy Initiatives to be pursued in smaller groups by Exchange Members.

Community Resources
To date, the exchange has led to two main products:

  1. AI and Education Policy Reading List: The AI and Education Policy Reading List is an annotated compilation of websites, primers, reports, academic articles, and databases that were shared by Exchange members over the course of our sessions. The reading list focuses on the intersections of policy, AI, and education in global & national settings, and provides additional starting points for learning about AI privacy and AI resources for educators.
  2. Identification of Priority Areas in AI and Ed Policy: As a result of the discussions surrounding the Speaker Sessions, members identified four high priority concerns in AI and Education Policy: transparency and disclosure, communication and user agency, AI literacy, and ethics and equity. Members created a taxonomy of potential actions to take surrounding those concerns.

All videos of exchange meetings, slide decks, and activities are available to Exchange Members. If you are interested in being added to this folder, please contact us.

Policy Initiatives
In the final sessions and leading up to the September 2021 CIRCLS convening, we are working in three small groups to create the following policy briefs or comparable deliverables:

  1. Outcome: Developing an AI in EdTech Transparency, Equity, and Agency Pledge
  2. Outcome: Policy brief on federal guidelines for AI in EdTech
  3. Outcome: Document for educators and district leaders to increase literacy and confidence with AI EdTech, plugging into other AI Literacy initiatives to disseminate information (e.g. ISTE & AI4K12).

If you’re interested in plugging into any of these initiatives or learning more, please reach out to us! We welcome any feedback and input that our community has to offer.

Speaker Series
The AI & Ed Policy Expertise Exchange hosted four speakers sessions on global, national, state-level policy initiatives, as well as an educator panel and workshop on a forthcoming product certification.

Speakers Session 1: Global and National AI & Ed Policy Initiatives

  • Kasey Van Ostrand is the Project Director for policy partnerships at Digital Promise, and spoke on her current work with the U.S. Office of Educational Technology on the 2021 National Education Technology Plan (NETP). The NETP sets a vision and plan for learning enabled by technology, and hopes to include a plan for AI in Education in the 2021 iteration. Aside from this plan, Kasey explained the U.S. Dept. of Education has the power to coordinate stakeholders, provide national recommendations, and offer federal grants and incentives to people continuing this work.
  • Joseph Fatheree is a doctoral student and long-time K-12 educator who spoke on his work as part of the advisory committee working on an International Ethical Framework for AI in Education with The Institute for Ethical AI in Education in the UK. The framework, released in March 2021, sets 8 key objectives for ethical AI development and was developed through a series of discussions with experts and round tables dedicated to the participation of young people.

Speakers Session 2: State Curriculum Initiatives

  • Dr. Amy Eguchi is an Assistant Teaching Professor in the Department of Education Studies at University of Florida. Amy takes part in the AI for K-12 initiative, jointly sponsored by AAAI and CSTA, as an advisory group member, and spoke on the AI4K12’s big ideas and AI curriculum initiatives. AI4K12 aims to develop national guidelines for teaching AI, develop curated AI resources for K-12 teachers, and foster a community of stakeholders, specifically developing capacity for curriculum planning on a state level.
  • Dr. Marlo Barnett is the Vice President for Computer Science for Illinois #CS4IL, and Vice President for Computer Science Teachers Association, CSTA-Chicago, and AI4K12 member. She spoke on her experience introducing legislation in the state of Illinois and writing the nationwide framework for Artificial Intelligence K-12. The Illinois CS legislation, passed in March of 2021, set standards for CS curriculums and literacy to be adopted in all Illinois schools between 2021-2024.

Speakers Session 3: Panel of Educators

  • Nancye Black, Cameron Fadjo, Kip Glazer, and David Lockett spoke on their experiences as educators and in advocating for responsible AI and EdTech implementation in various K-12 settings, sharing concerns and hopes for future AI regulation. Some major takeaways from this panel included the necessity of funding professional development for teachers to build opportunities for AI literacy, the need to alleviate teacher workload to be able to build time for technology standards, and the ability for all stakeholders to advocate for themselves to introduce major legislation with the support of organizations like the International Society for Technology Education.

Speakers Session 4: EdTech Equity Product Certification

  • Trisha Callella is the current Product Partnerships Director at Digital Promise and led a workshop on the work-in-progress EdTech Equity product certification that she has been developing alongside Madison Jacobs and Nidhi Hebbar at the EdTech Equity Project. The product certification requires companies to meet and demonstrate specific equity standards in all cycles of AI tool development such as ideation, training/testing, and design/implementation.