On the Limits of Artificial Intelligence (AI) in Education
There is a call for slowing down and recalibrating current discussions around AI and education – paying more attention to issues of power, resistance and the possibility of re-imagining education AI along more equitable and educationally beneficial lines.
Abstract
The recent hyperbole around artificial intelligence (AI) has impacted on our ability to properly consider the lasting educational implications of this technology. This paper outlines a number critical issues and concerns that need to feature more prominently in future educational discussions around AI. These include: (i) the limited ways in which educational processes and practices can be statistically modelled and calculated; (ii) the ways in which AI technologies risk perpetuating social harms for minoritized students; (iii) the losses incurred through reorganising education to be more ‘machine readable’; and (iv) the ecological and environmental costs of data-intensive and device-intensive forms of AI. The paper concludes with a call for slowing down and recalibrating current discussions around AI and education – paying more attention to issues of power, resistance and the possibility of re-imagining education AI along more equitable and educationally beneficial lines.