Dive into the nuanced realm of educational algorithms, explore the definition and implications of algorithmic bias, scrutinize instances of bias in Large Language Models, and discuss actionable strategies for bias mitigation. Connect these insights to NYS Computer Science and Digital Fluency Standards and the NYS Culturally Responsive Sustaining Education Framework.
