Rapid advances in the field of artificial intelligence (AI) require school and district leaders to understand how emerging technology applications, including those using generative artificial intelligence (Gen AI), fit into schools and districts across the United States. There is a lot of uncertainty about what AI is, how it works, and its impact on students, families, educators, and the broader school community. School and district leaders shared the challenges they face in using AI for teaching and learning. They are also concerned about increased inequities in access to digital technologies and tools, creating further structural barriers for students and communities. In our work with educators, students, and families, we have learned how important it is for educators to understand AI literacy in order to leverage these technologies to support all learners, especially those who are marginalized.
Just as AI has become ubiquitous in our daily lives, it is ubiquitous in schools and across disciplines. Artificial intelligence literacy enables educators to understand how AI works, how to assess it, and how best to adapt it to their subjects and learners. Additionally, demystifying AI can help people use AI technology efficiently and responsibly in society, their personal lives, and their professional careers. At Digital Promise, we strongly believe that AI literacy is the best place to start and goes hand-in-hand with our digital equity work.
What is Artificial Intelligence Literacy?
Artificial Intelligence Literacy applies 21st century skills including communication, collaboration, critical thinking, and creativity. It builds on years of work in digital and media literacy and computational thinking, and includes elements from fields other than computer science, ethics, and science, technology, engineering, and math (STEM).
The skills and practices needed to engage in AI are relevant to all disciplines. What’s more, AI has the ability to extend the way specific disciplines are learned, introducing new teaching strategies and conceptual applications. For example, students could train a machine learning system to recognize patterns in a math class or test a text-to-speech system to see if it can distinguish between homophones in English language arts.
In addition to disciplinary concepts, it is important to address issues such as the appropriate use and timing of AI, the historical context in which AI was developed, addressing bias, protecting the privacy of data shared with AI systems/tools, ensuring fair access to AI tools, and considering the environment and human capacity.
“There seems to be widespread agreement that AI has great potential to disrupt outdated educational narratives. However, it has been emphasized time and time again that teachers need professional learning about AI. We need support from across the education sector to improve educators’ capabilities around AI. –EngageAI Academy Forum participant and educator
Using Digital Equity to Develop AI Literacy
Digital Promise is developing processes, practices, and resources for school districts to support educators in developing AI literacy and utilizing AI for powerful learning in K-12 learning environments. These supports include.
- Learning pathways that explicitly connect classroom learning to cross-cutting programs (e.g., AI). These pathways articulate system-wide K-12 learning opportunities that are consistent across classrooms, cumulative from year to year, and competency-based.
- Professional learning experiences provide contextualized support for educators to learn AI literacy and apply emerging technologies in the classroom. We are working with a number of districts to promote AI literacy based on their ongoing initiatives.
- Resources such as definitional frameworks and contextualized examples are critical to supporting AI literacy. We are developing these resources for education leaders to define and operationalize AI for educators.
Like all educational technologies, AI has the ability to reproduce existing inequities in education. We have a longstanding commitment to equity and are intentional about designing and implementing these educational supports to complement our digital equity initiatives. We address three pillars – availability, affordability, and adoption – in order to provide historically and systematically excluded learners and families with the knowledge and skills they need to support their communities to remain connected, informed, and able to fully participate in society.
We see the rapidly evolving field of AI as an opportunity to design more inclusive learning environments. We have an ongoing partnership between learning scientists, designers, and practitioners to co-design content that is accessible, understandable, and relevant for practitioners in the field of digital equity.