  We discuss the implications of generative AI on education across four
critical sections: the historical development of AI in education, its
contemporary applications in learning, societal repercussions, and strategic
recommendations for researchers. We propose ways in which generative AI can
transform the educational landscape, primarily via its ability to conduct
assessment of complex cognitive performances and create personalized content.
We also address the challenges of effective educational tool deployment, data
bias, design transparency, and accurate output verification. Acknowledging the
societal impact, we emphasize the need for updating curricula, redefining
communicative trust, and adjusting to transformed social norms. We end by
outlining the ways in which educational stakeholders can actively engage with
generative AI, develop fluency with its capacities and limitations, and apply
these insights to steer educational practices in a rapidly advancing digital
landscape.
