Theoretical Frameworks

In the evolving landscape of artificial intelligence (AI), it is increasingly evident that youth and families need opportunities to consider the profound impact of AI on their daily lives. Moreover, they need to understand how to leverage AI for problem-solving and decision-making in many realms while being acutely aware of its potential to perpetuate biases and inequities within society and their own communities. Unfortunately, AI systems often remain obscure to the public, hindering the realization that AI is a product of human intervention, with the power for collective agency over its capabilities (de Saint Laurent, 2018; Emmert-Streib, Yli-Harja, & Dehmer, 2020; Leufer, 2020).

This gathering was strategically designed to shed light on the pivotal role of informal learning in operationalizing AI literacy and fostering people's agency, particularly among youth and communities historically excluded in AI development.  To guide our endeavors, we embraced human-computer interaction traditions and humanistic AI design principles (Schneiderman, 2022; Fei Fei Lee, 2023; others), framing AI as a tool to amplify human abilities, emphasizing the importance of centering diversity, equity, and inclusion to create fair and just systems that work for all. With the collaborative efforts of our planning committee, we crafted an initial AI literacy framework pinpointing key concepts and mindsets crucial for using, interrogating, and designing with AI (see framework below).

To build on the momentum, the NYSCI team facilitated voluntary online debrief sessions post-conference, uncovering promising strategies and identifying key priorities for the next stages of this imperative work. The human-centered approach championed throughout ensures that AI literacy becomes a vehicle for empowerment, inclusivity, and equitable progress for all.

To refine and envision future roles for informal learning in cultivating critical skills, the conference was organized as a participatory design experience to operationalize these ideas and concepts. By deliberately assembling a diverse, interdisciplinary group—composed of AI designers, learning scientists, informal and formal educators, and industry professionals—we aimed to identify core opportunities for promoting agency and advancing human-centered AI literacy skills in informal settings, especially for diverse youth and families.

The conference delved into three core issues: 1) fostering engagement and conceptual learning about AI, including foundational skills for critical use; 2) understanding evolving attitudes toward AI and their implications for learning; and 3) nurturing children's agency to interrogate, intervene, and shape AI, empowering them to become AI-enabled workers and community members. Participants, working in teams and as a collective, explored and critiqued existing AI tools and learning frameworks, sharing insights from successful programs and envisioning future directions.

Culturally responsive pedagogy acknowledges that we bring our full selves into learning. It recognizes that the diversity of people’s prior experiences, cultural norms, values, and identities are assets that shape the way one approaches learning and the possibilities they see for its relevance to their lives. In relation to the future development and application of AI,  this diversity of perspectives and experiences is critical for creating robust and equitable systems. Culturally responsive teaching and learning approaches include incorporating materials, examples, and perspectives from various cultures to not only make the content about AI more relevant and engaging, but to ensure that everyone has agency in using AI in ways that are empowering for them and their communities, and to envision future directions for AI  to tackle problems worth solving to them. 

Diversity, equity, accessibility, and inclusion (DEAI) issues are central to this initiative and influenced who was part of this effort. The recent acknowledgment of bias in datasets and algorithms underscores the critical importance of DEAI in designing, deploying, and assessing AI's impact. Trustworthy and responsible AI practitioners recognize that prioritizing DEAI in design and implementation is crucial for developing robust systems that avoid harm and contribute positively to augmenting human capabilities. This involves not only expanding the participation of individuals from diverse backgrounds but also considering the diversity of data used to train systems, ensuring equitable access to technologies, and carefully crafting algorithms that play a pivotal role in decision-making affecting our quality of life.