My main idea is algorithmic co-teaching by 2035. I believe that there will be a lot of tension between personalization and autonomy.
I could go the direction of algorithmic co-teaching as unevenly distributed futures, and speak to Singh & Maughan’s warning that technological futures emerge unevenly producing “pockets of privilege” and “zones of abandonment,” Macgilcrest et al.’s idea of “datafied schools” where optimization becomes the hidden curriculum, and Selwyn’s argument that AI’s limits are most visible in contexts where human judgment is already stretched thin. I could frame algorithmic co-teaching not as a single future but as multiple futures unfolding simultaneously that are being shaped by geography, funding, and politics.
I could go the direction of algorithmic co-teaching as a site of contestation and resistance, and speak to the emphasis that Roberts placed on relationality, sovereignty, and community-based knowledge, Veletsianos et al.’s argument that hopeful futures requires justice, not just innovation, and Selwyn’s warning that ed-tech must be understood within environmental and political limits. I could frame it as algorithmic co-teaching is not simply adopted, but negotiated, resisted, and reshaped by human values. Right now it leans toward critical pessimism; however, I could add in Veletsianos et al.’s critical hope. This would show that although futures are contested, they are not predetermined.