The integration of Artificial Intelligence (AI) into school psychology is evolving rapidly, presenting both opportunities and challenges. AI has the potential to enhance educational and mental health services by facilitating data-driven decision-making, streamlining administrative tasks, and offering personalized interventions for students. However, biases inherent in AI systems—reflecting the prejudices of developers and historical data—pose significant risks of exacerbating systemic inequalities. This paper examines AI’s historical context, current applications in education, and specific uses within school psychology. It also discusses the socio-political factors contributing to algorithmic biases, data privacy concerns, and language/cultural inequities in AI systems. Recommendations are offered to mitigate AI biases, emphasizing the importance of diverse representation in AI development, comprehensive policy formation, transparency, and community involvement. Addressing these concerns is crucial for ensuring that AI contributes equitably to student success.
Lockwood et al. (Mon,) studied this question.