We welcome theoretical or empirical submissions of position papers, case studies, or ongoing research on the following topics in the K12 context. Submissions focusing on the primary school context are particularly welcome. 

• Algorithmic fairness and data biases used in teaching and learning environments

• Accessibility issues when using or teaching AI in schools 

• The interplay between AI decision-making and human decision-making and its impact on fairness

• Equity issues and challenges when teaching AI concepts to students

• Teacher competency frameworks focused on equity in AI integration and usage

• Domain-specific AI-related equity issues (e.g., in subjects like mathematics, writing, etc.)

• Teachers' and students' views on potential equity issues in AI education and its integration into classrooms

• Policymaking for equity in AI use in education: developing frameworks to ensure fair and inclusive AI adoption