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Algorithmic systems claim education - and (re)production of societies
Access to education has remained the focus in debates surrounding the digital divide and sustainability development goals. However, issues in education have never been merely about connectivity but are in fact the root cause of political forces affecting the distribution of knowledge (in its full truth). Yet, a new force arises to as a dominant contender: one that is likely to surpass and diminish the expertise of policymakers to mere figureheads. As education becomes increasingly dependent on education technologies (edtech) and digital connectivity, the owners of the infrastructures that compound hardware, software, data extractive mechanisms and algorithmic decision-making - what comes packaged as applications (apps) and platforms - have the capacity to claim control over not only the distribution of knowledge but also over societies and individuals with regards to who will get - and be – what (Hillman & Bryant, 2022).
The businesses of edtech promise successful futures including that of their users in the hopes for investment and minimal political barriers to market entry – and schools. These same businesses promise to “personalise” the educational experience through the means of datafication – by converting student activities into granular data for profiling and prediction. However, as these products settle as the dominant mode of access, distribution and legitimisation of knowledge (and education), they begin to claim a legitimate pedagogic power in education (Bourdieu & Passeron, 1977/2000). This pedagogic power is accumulated through pedagogic action and pedagogic work, which are expressed by the ability of edtech to extract student data for algorithmic decision-making. The pedagogic action and pedagogic work legitimize the datafication processes and raise edtech products (and their business owners) as pedagogic authority. As such, edtech businesses can have the capacity to legitimize their own pedagogic dominance and therefore influence the reproduction in education.
Moreover, as a legitimate pedagogic power, edtech businesses have the (rather macabre) opportunity to never admit to their own flaws or when they transgress even if they can realise it. For, they become the agents and the domain experts and so they themselves can steer not only societies and education at large but also the laws that are supposed to govern and control them. In the face of lessair-fair authorities (see the scrapping of the UK GDPR), such scenarios are realistic. We see examples of algorithmic transgression (e.g., algorithms giving unfair A-level results [Coughlan, 2020] and showing biases in hiring workers [Ajunwa, 2020] with little consequences for the owners of the algorithms, or the sector that runs on similar business models.
Education is a necessary pillar for a democratic society. It is considered a human right. Edtech business on the other hand have the privilege to sell products in education. To break away from the possible monopoly of legitimate symbolic violence as edtech products settle in with their enchanted determinism and promises for the future, this presentation addresses the need of meaningful governance and oversight of the sector in order to understand how these products work, who decides what is put into these products, and who or how their mistakes are mitigated. It will bring in empirical evidence from recent research on the lack of governance and benchmarking of edtech as they claim legitimate pedagogic authority in education.
References Ajunwa, I. (2020). The “black box” at work. Big Data & Society. https://doi.org/10.1177/2053951720938093 Bourdieu, P., & Passeron, J. C. (2000). Reproduction in education, society and culture (2nd ed.). London, UK: SAGE Publications. (Original work published 1977) Coughlan, S. (2020). Why did the A-level algorithm say no? BBC News. https://www.bbc.co.uk/news/education-53787203 Hillman, V. (2022) Edtech procurement matters: it needs a coherent solution, clear governance and market standards, Social Policy Working Paper 02-22, London: LSE Department of Social Policy. Hillman, V., & Bryant, J. (2022). Families’ perceptions of corporate influence in career and technical education through data extraction. Learning, Media and Technology. https://doi.org/10.1080/17439884.2022.2059765