Cinamon Bailey
Papers
2
Total Citations
33
H-Index
2
About
Cinamon Bailey is a leading voice in the emerging field of critical machine learning education for young learners. Her research sits at the intersection of computer science education, child development, and social justice, exploring how children can understand not only the technical mechanics of ML but also its profound ethical and societal implications. In her landmark 2022 study, "Characterizing children’s conceptual knowledge and computational practices in a critical machine learning educational program," which has garnered 29 citations, Bailey demonstrated that elementary-aged children can grasp complex concepts like biased training datasets and their harmful effects on marginalized populations. This work established a foundational framework for integrating critical perspectives into K-12 computing curricula. Her subsequent 2023 design paper further details the pedagogical architecture of these programs, emphasizing the need to equip children as both discerning consumers and responsible future producers of technology. By centering equity and social impact, Bailey’s contributions are reshaping how we think about AI literacy, ensuring that the next generation has the technical and social expertise to engage with—and challenge—the technologies that increasingly shape their world.
Research Focus
Key Achievements
Top Papers
- 1
- 2The Design of a Critical Machine Learning Program for Young Learners4 citations · 2023