This article essentially discusses the move towards Zoom in HEIs, including previous investment in asynchronous learning and its future now that we are ‘going back to normal’. The primary focus here is on raising critical issues around privacy and user safety, emphasising that these issues continue to persist and so should be discussed.
Zoom is taken as the example technology here as it existed before the pandemic but benefited from the interconnection of crisis, capitalism, and platformisation that came along with the pandemic. Zoom was basically able to capitalise upon the crisis in education delivery at the beginning of the pandemic as an apparently free and reliable platform. Crisis is presented as central for contemporary capitalism, stemming from the ever increasing privatisation of public sectors after the 2008 financial crisis. Platforms are treated as forms of infrastructure here (or as becoming more infrastructural with time) as they now manage everyday data flows, making them vital to regular life. This dependence upon platforms allows for greater data extraction and so more profit-making from platform users. It is almost natural that this kind of platformisation of everyday life would target schooling, as classrooms have long been a site of power and control. A push towards big data incentivises a shift to increased quantification of education (and students) under the guise of efficiency and objectivity. It is worth noting that these technologies in and of themselves are neither good nor bad, rather it is the Skinnerian, behaviourist approach with which they are applied which creates issues. It is this techno-determinist viewpoint which is challenged here, rather than technology altogether.
Zoom’s approach to data is then challenged in the article. Zoom is presented as a fairly standard tech company in this sense, selling/sharing user data with other large companies, supposedly legitimised through their incredibly long and vague EULAs. Security and privacy should be particularly of concern for HEIs, as students do not really have the realistic option of opting out of data sharing when they essentially must use the platform. Additionally, Zoom has a track record of suspending accounts/calls taking place at HEIs if they are deemed to be politically sensitive, which raises questions about Zoom’s ability to control the content on its platform and the influence from outside (governance) bodies. This is not to say that no moderation should exist but that everyday and essential infrastructures being subject to the political interests of governments (and determining what is ‘legitimate’ speech) is worth resisting. There are also issues of access and resource inequity tied up with platforms. Both the ability to access technology and the mode of access are unevenly distributed, amplified by platforms like Zoom which do not work as well on smartphones, compared with a computer.
HEIs have been struggling financially, which has only been intensified by COVID. In the face of this, technological rationality pushed by big tech companies can seem appealing but the platformisation of university life must be conducted with due caution. This is not to say platforms such as Zoom are all bad, of course, but that we should consciously avoid any deterministic arguments about the outcomes of using such platforms, which may be accelerated by the logic and persistence of a crisis. Ensuring that these conversations continue to happen is still important; we are still in a moment of flux, both in terms of platform choice and of regulation. Questions of security, surveillance, censorship, and equity must be considered by HEIs in the face of this, acknowledging that technology is not a simple cure-all for post-pandemic education.
This chapter also deals with technology implementation in schools. It notes that there is nothing new about student surveillance generally, rather it is the extent to which students are being surveilled which has changed (as well as how this extension of surveillance is treated as a rational move forward, rather than a privacy threat). The result today is the subjectification and subjectivation of students (external and internal governance of the self) through the logic of numbers. Again, this was exacerbated by the pandemic, which was sold as a solution to the woes of education systems, while acting as a means to continue the platformisation of schooling.
The datafication of schools is a continuation of the neoliberal logic of individualisation within education; this employs the idea that, given enough data, we can understand and solve complex structural issues. This effectively ignores the nuances of these issues and the lived experience of students. Again, neither EdTech nor the commercialisation of schooling are new but the pandemic allowed for the popularisation of the Netflix-like commercial model through the logic of numbers The example of the UK’s automated A-level grading in summer 2019 is given here; not as one of commercialisation but as a clear failing of the big data’s supposed objectivity. Essentially, exams couldn’t physically take place and teacher-predicted grades were dismissed as being too lenient. Instead, an algorithm was designed to distribute grades, under the veil of objectivity. This basically ranked students at an institution and assigned them grades based on cohorts from the previous three years, while giving higher grades to students from smaller classes. This effectively mirrored class divides, undermining any perceived notion of a meritocracy. Examples such as this highlight why teachers often feel powerless in the face of platformisation, as well as issues around data privacy and security. The pandemic extended this experience, forcing both teachers and students to take up platforms despite any apparent issues the software may have.
The chapter then returns to the idea of an invisible/entrenched biopower in schooling. Neoliberal education systems have a fondness for Taylorist ideas of efficiency, often aligning themselves with fields like ‘business intelligence’. This has moved on from CCTV to things such as COVID-symptom checkers or facial recognition software. This creates the normative student ideal, through which students are judged and taught to see themselves. With students being measured against this idea, they can become trapped in record prisons. Examples are then given of how these technologies have come to act preemptively, assigning students personal risk scores in order to intervene before problems even arise. In HEIs, this tends to target scholarship holders and other students schools see as an investment/as an important retention figure.
These kinds of surveillance technologies have also been employed for at-home exam taking for HEI students, generally conducted through third-party companies who benefit from the extracted student data. In the everyday classroom, we are also beginning to see facial analysis for micro-expressions. This aims to quantify engagement at a level beyond immediate human comprehension/visibility, while giving students no option to choose which data they share or emit. This is sold as an individualised, tailored educational pathway, acting as a means for students to transform their own subjectivities, while turning students into consumerist analytic devices and unpaid labourers producing value through their data. This begins to change what it means to learn or be educated: the only learning considered real or valid is that which can be quantified and measured within the confines of the platform. Similarly, the work of teachers becomes one of data management and platform authoritarianism under a data gaze.
Platform Pedagogies 