Planning at the edge of tomorrow : a structurational interpretation of Maltese AI-related policies and the necessity for a disruption in education

Abstract

Technology provisions what we as humans are physiologically missing. Technology has facilitated the process that empowered us from once merely competing with other species to essentially becoming the gatekeepers of the planet’s resources for all. Technology has progressed in tandem with civilization effectively blending in within our mundane activities. In several instances it has also become the obvious if not consequential vehicle through which our lives are organized and ensue. Such technological determinism is also strongly disputed by discourse drawn from recursive dialogues taking place between users whose needs have direct influence on the design of the technology, and, the inherent structural qualities of technology that in several instances dictate the need for new requirements and skills (Mackenzie & Wajcman, 2005). It may also cause one to wonder if, as digital technology, and now, Artificial Intelligence (AI), are becoming more re ned we are facing thinking machines that can seamlessly merge in, complement, mimic and unless properly catered for, determine what we can do. Findings compiled by Benedikt and Osborne (2013) at Oxford University, Arntz et al. (OECD, 2016), and the McKinsey report on Automation and Employment (2017) all resonated the threat of automation on structured and manual jobs in general. Ironically the reports also came with a short-lived silver lining. In the same instances of predicting the vulnerable as the most vulnerable (Muro et al., 2019), the effect of automation on better educated workers was taken to be much less. However ongoing advancements and eventful technological disruptions brought about by AI and machines that can learn, reason and act for themselves (Muro et al., 2019) instilled concern for the permanence of seemingly unchallenged white-collar professions. Saying it differently, as technology such as AI progressively untethers itself further from human supervision, the issue is not anymore solely biased towards automation but more so towards autonomy (Gatt, 2021; Singh, 2020). Just, like in the case of the Japanese venture capital firm ‘Deep Knowledge’ that became the first company to name an artificial intelligence to its board of directors, AI is also provoking the reconsideration of what are exclusively human skills. Nonetheless, the issue here is not to shun away, because in context of technological progress we cannot. Rather, as the boundary on what pertains to human nature and what can be performed by the machine becomes more blurred, one wonders if ultimately humanity is after all really drifting towards a technologically deterministic future. Then again, the tendency to educate people according to what is deemed to be valuable at any particular time is a proof that historically, education has always risen to serve socioeconomic needs (Aoun, 2017).