‘If politics is about struggles for power, then part of the struggle is to name digital technologies as a power relation and create alternative technology and practices to create new spaces for citizens to encounter each other to struggle for equality and justice.’ (Emejulu and McGregor 2016: 13)
Much of this block on algorithmic cultures has involved us examining the algorithmic systems and cultures at play in our lives, ‘unpack[ing] the full socio-technical assemblage’ (Kitchin 2017: 25) and uncovering ideologies, commercial and political agendas (Willamson 2017: 3).
As I explore power and (the notion of) the algorithm (Beer 2017), and the complexities of agency with regards to these entangled human-machinic relations (Knox 2015; Amoore 2019; Hayles 1999), and its implications for my lifestream here and education in general, I increasingly wonder what form resistance to this might take.
With this mind, I have gathered some rough notes and links below into the form of a reading list of sorts; this is something I hope to explore in the future.
Collating a reading list…
Protest and resistance
A Guide for Resisting Edtech: the Case against Turnitin (Morris and Stommel 2017)
Brooklyn students hold walkout in protest of Facebook-designed online program (New York Post 2018)
Hope (2005) outlines several case studies in which school students have resisted surveillance.
Tanczer et al. (2016) outline various ways in which researchers might resist surveillance, such as using “The Onion Router” or tor (although the tor project website may be blocked for some).
Noiszy offers a browser extension which aims to mislead algorithmic systems by filling sites of your choosing them with “noise”, or “meaningless data”.
#RIPTwitter hashtag, often used to resist changes to Twitter’s algorithmic systems. Noticed earlier in the course, when considering changes to algorithms that may have an effect on my social media timelines. See DeVito et al. (2017).
‘Integrated & Alone: The Use of Hashtags in Twitter Social Activism’ (Simpson 2018). Examines viral hashtags associated with social movements: #metoo, #takeaknee, #blacklivesmatter.
Alternative models (such as platform cooperativism, participatory democracy/design and inclusive codesign)
‘There are people behind big data – not just data scientists, but software developers and algorithm designers, as well as the political, scientific and economic actors who seek to develop and utilise big data systems for their diverse purposes. And big data is also about the people who constitute it, whose lives are recorded both individually and at massive population scale. Big data, in other words, is simultaneously technical and social.’ (Williamson 2017: x-xi)
What/who might we resist? Surveillance, ‘datafication’ and data-intensive practices that discriminate against the marginalised (Noble 2018; Knox et al. 2020)? ‘Learnification’, neoliberal ideologies and the marketisation of education (Biesta 2005)? “Technological solutionism” (Morozov 2011; 2013)?
Looking a little deeper into the models and processes those following the “Silicon Valley” model often evangelise about, reveals the Agile Manifesto (Beck et al. 2001), written by what appears to be an group (calling themselves ‘The Agile Alliance’ and described as ‘organizational anarchists’) of people meeting at a Utah-based ski resort in 2001.
David Beer (2017: 4) argues that ‘a
‘Cooperative creativity and participatory democracy should be extended from the virtual world into all areas of life. This time, the new stage of growth must be a new civilisation.’ Imaginary Futures book (Barbrook 2007)
Alternative business models rooted in democracy, such as platform cooperativism (see Scholz and Schneider 2016).
Alternative design processes, rooted in participation and inclusivity, such as participatory design (see Beck 2002) and inclusive codesign:
‘The importance of inclusive codesign has been one of the central insights for us. Codesign is the opposite of masculine Silicon Valley “waterfall model of software design,” which means that you build a platform and then reach out to potential users. We follow a more feminine approach to building platforms where the people who are meant to populate the platform are part of building it from the very first day. We also design for outliers: disabled people and other people on the margins who don’t fit into the cookie-cutter notions of software design of Silicon Valley.’ (P2P Foundation 2017)
What might this look like in the context of education?
Can Code Schools Go Cooperative? (Gregory 2016)
Looking into critical pedagogy (see Freire 2014 [1970]; Freire 2016 [2004]; Stommel 2014), and If bell hooks Made an LMS: Grades, Radical Openness, and Domain of One’s Own (Stommel 2017).
As we see signs that “EdTech” companies stand to potentially gain from or exploit the current coronavirus crisis…
Never let a crisis go to waste.
"While we are uncomfortable citing ‘winners’ in the coronavirus situation, some companies may be positioned better than others. Specifically, those that specialize in online education could see increased interest should the situation worsen.” https://t.co/nddMgtXcRN
— Ben Williamson (@BenPatrickWill) March 7, 2020
Calls to exploit the #pandemic in order to data-mine #education can be seen as part of a broader 'mission creep' for the normalisation of #surveillance https://t.co/V4x9BiCbni
— Jeremy Knox (@j_k_knox) March 18, 2020
…it is ever more urgent to consider the potential significant effects that these “EdTech solutions” may have on educational policy and pedagogies (Williamson 2017: 6). As Williamson (2020) writes:
‘Emergency edtech eventually won’t be needed to help educators and students through the pandemic. But for the edtech industry, education has always been fabricated as a site of crisis and emergency anyway. An ‘education is broken, tech can fix it’ narrative can be traced back decades. The current pandemic is being used as an experimental opportunity for edtech to demonstrate its benefits not just in an emergency, but as a normal mode of education into the future.’ (Williamson 2020)