AI and Higher Education in Developing Country Contexts: About Envisioning Potentiality!

Indeterminacy and uncertainty have been perennial conditions across the world and more so in developing country contexts characterised by frequent political and social upheaval. What remains constant though, is technological ‘progress’, in all its multiple manifestations. Technology’s disruptive-productive trait requires that the subjects that have to give effect to its application in various spheres of society, have to remain vigilant of the promises and pitfalls that accompany any innovation. In recent years, AI has begun to increasingly impact the work of the education sector, with the higher education sector particularly affected by the discomfit that sophisticated AI technology like ChatGPT (an acronym for Generative Pre-trained Transformer) might have for the knowledge agenda that they engaged with. Both alarmist technophobes and technophilic subjects abound in both higher education governance structures and the general academe. In this paper, we draw on Bernard Stiegler’s notion of the pharmakon as we address the question as to how Artificial Intelligence (AI) might be harnessed for productive use in teaching, learning and assessment in higher education. We attempt to move beyond the narrow binary or dichotomous, technophilic-technophobic approach to understanding the pedagogic encounter, towards a nuanced, spectral analytic—a spectral gaze at the implications of novel Apps (like ChatGPT) for teaching, learning and assessment in higher education. We adopt a deliberative pharmacological analysis to argue that irrespective of the functional potential of innovation, fundamental principles of teaching, learning and assessment remain the same. We contend that given the unevenness of the socio-economic terrain in higher education in developing countries, AI innovation and take-up are likely to present particular challenges. We remain cognisant of Stiegler’s caution of the entropic consequences of techno-euphoria—that technology, instead of creating conditions for subject autonomy, might well render a witting heteronomy, as subjects succumb to technology’s application in the pursuance of narrow, destructive, narcissistic market-driven aspirations (Stiegler, The lost spirit of capitalism: disbelief and discredit, 2014). While technological innovation might be ‘disruptive’ we advance the concept of ‘productive-disruptive’ as dissonant, liminal space—a constantly mutating borderland, ripe with opportunities for critical reflection on current practice, and explosive lines of productive flight (Deleuze and Guattari, A thousand plateaus, 1987) for thinking anew, and growth for both the undergraduate curriculum and postgraduate research.