Centering Personal Identity in Embodied AI Literacy Activities

• In Event: Integrating AI Education in K–12 Humanities Curricula: Opportunities, Challenges, Design Considerations, and Promising Solutions

Abstract

Objectives or purposes: AI is increasingly affecting young people’s lives, with far-reaching consequences. AI algorithms are affecting young learners’ social relationships and the way they perceive their own self-worth and place in society, while companies are powering AI with data collected from young people. It is therefore critically important that young learners have opportunities to reflect upon their personal relationship to AI. In providing such opportunities, STEM researchers can leverage the expertise of humanities educators in engaging students in challenging discussions about their personal identities and relationship to society. We aim to develop a set of low-tech activities that teachers across humanities disciplines can incorporate as standalone lessons to engage middle-school age learners in reflecting on their personal relationship to AI.

Theoretical Framework: We are focused on designing embodied activities that allow learners to make sense of AI using their own body and on centering learners’ identities as they consider how AI utilizes their data—approaches that have been effectively leveraged in prior work to teach about analogous subjects such as computer programming and mathematics (Abrahamson & Bakker, 2016; Eglash et al., 2006).

Methods and Data Sources: We have preliminarily tested several activities in a co-design study conducted with 5 family groups (20 participants) with children of varying ages (over 6). We recorded audio of family group interactions and analyzed the audio for evidence of learning talk (Long et al., 2021). We plan to conduct additional studies this year, including having middle-school age learners complete a pre- and post-test surrounding interaction with the activities and interviewing teachers to understand how they perceive and use these activities in practice.

Results: We are iteratively developing activities that center learners’ personal identities in relation to AI. We elaborate on a few examples here. In a paper-based activity called “Magic Mirror,” learners are prompted to create a cyborg using human body parts, computer sensors, and actuators. Learners are encouraged to consider how the sensors relate to their own body and think about the unique affordances offered by both the human body and AI devices. In another activity, “Online Footprint,” learners use a map and game-like tokens to reflect on which aspects of their personal data are collected or tracked by different AI algorithms online. Finally, in “Are you smarter than an AI?,” learners engage in a card-based trivia game that prompts them to reflect on their own knowledge and strengths in relation to AI. Early results from the co-design study we conducted with a subset of the activities indicated that they supported family group learning talk (Long et al., 2021).

Significance: We are developing low-tech activities that can be easily led by teachers with little prior knowledge of AI, leveraging instead humanities teachers’ abilities to foster student discussion and reflection on their personal identities. This has the potential to broaden access to opportunities for students to learn about AI and how it relates to their lives.

Authors

• Duri Long, Northwestern University

• Lauren Bichelmeir, Northwestern University