This chapter looks at the use of artificial intelligence (AI) in education, which immediately conjures the fantasy of robot teachers, as well as fears that robot teachers will replace their human counterparts. However, AI tools impact much more than instructional choices. Personalized learning systems take on a whole host of other educational roles as well, fundamentally reconfiguring education in the process. They not only perform the functions of robot teachers but also make pedagogical and policy decisions typically left to teachers and policymakers. Their design, affordances, analytical methods, and visualization dashboards construct a technological, computational, and statistical infrastructure that literally codifies what students learn, how they are assessed, and what standards they must meet. However, school procurement and implementation of these systems are rarely part of public discussion. If they are to remain relevant to the educational process itself, as opposed to just its packaging and context, schools and their stakeholders must be more proactive in demanding information from technology providers and setting internal protocols to ensure effective and consistent implementation. Those who choose to outsource instructional functions should do so with sufficient transparency mechanisms in place to ensure professional oversight guided by well-informed debate.
A Crowdsourcing Approach to Collecting Tutorial Videos -- Toward Personalized Learning-at-Scale