In between terms seems like a natural enough time to pause for a bit and refine my research focus for the next few years. I have been writing chapters and papers (hence my lack of writing here) largely around speculative topics and have enjoyed that quite a bit. The topics are seemingly disparate but they are reflecting what I believe what this new focus will be. The abstracts are at the end of the post.
My research (has and) will focus on the critical examination of the mobilities exhibited by groups and sectors in flux and how technology is used to both structure and manage these mobilities. Post-Brexit, with greater concentrations of international students in UK higher education, with a greater visibility of those who are mobile not by choice, with the unbundling of labour and education, with a global edtech regime emerging in deficit contexts largely unmooring local educational expertise and displacing higher education as a vehicle for social mobility, this research focus provides capacity to critically examine these movements a bit more holistically and to begin to address the larger intractable challenges that may stunt educational progress in underserved contexts.
The role digital education might serve in this increasingly unbundled intersectional educational environment is of particular importance: as a personification of mobility itself; as aligning to shifting digital labour, legal, and policy landscapes; as an accelerant to both the unbundling of social institutions (higher education included) and a vehicle for their recomposition (ideally); as a means of co-creating learning systems for those in flux (digital education specifically serving those in states of mobility). Overall, I want to foreground the complicated nature of mobility and to challenge its presentation as an unequivocal good. A bit of a straw man here in that I doubt too many who have experienced it see it as an unequivocal good, but that nuance isn’t always presented accurately in the media or indeed even the research.
I want to take further strides with an employ of the mobilities turn (and its attendant actor network theory underpinnings) to unpick the actors in these larger mobilities systems, or “the distribution of agency between people, places, and material assemblages of connectivity” (Sheller, 2017). A tall order for sure but I grow weary of instrumental mobile learning studies or facile ICT4D research. That isn’t a knock against all research in these areas (and I will elaborate on this in a subsequent post at some point, the research that I find particularly convincing) but much of it is a tough read.
I suspect this position will give me decent latitude to explore some rich interdisciplinary connections, such as:
- Technologies facilitating mobilities and mooring; management of place and technological engagement
- The redrawing of the digital divide as a holistic multi-actor intersectional environment (not inventing this but rather carrying it forward)
- The mobilities and moorings of the disproportionately affected
- Placelessness, statelessness, and xenophobia: a digital post-nationalism
- Labour, digital work, and digital education
- The materialities of mobility in digital education
- International student mobility post-Brexit
- Refugee education and the digital management of passage
- Surveillance and security studies
So a focus on mobilities as opposed to the new spaces being created in these digital environments gives some capacity, I suspect, for understanding how humans move through these systems, as well as for understanding how technologies both structure and move through these systems as well. Moving away from humanistic positions helps here in that I am not forced into some dichotomy between who is serving who: the human or the technology or the social dynamics in which they operate (or the policy framework, or the social norms, or the legal environment, etc.). I have actors and I have mobilities and the old spaces being torn asunder and the new spaces created in their wake.
AI is a good example here (hence one of the papers below). It moves through systems (digital, largely mobile networks), through systems of education and inequitable access, it mitigates some moorings and builds others. It shifts actors (teacher-student-technology) in relational exchanges.
5G networks, AI, and immobility: the “material inequalities in the distribution of communication technologies” (Chouliaraki 2012) is a highly intersectional enterprise with potential immobilities presented at each layer of the intersection, an enterprise that much of the world will interact with or be interacted on by artificial intelligence.
So some speculative book chapters leading to the emergence of this new research agenda hopefully early next year.
Gallagher, M. (2019 forthcoming). Moving beyond microwork: The Role of critical capacity and digital education in the unbundling of labour. In Peters, M. A.; Jandrić, P.; & Means, A. J. (Eds.). Education and Technological Unemployment. London: Springer.
Digital labour is often reduced to microwork, granular tasks disassociated from a larger work project, and the labour market to serve these activities is distributed and largely unorganized as a collective body. Larger platform employers such as Amazon Mechanical Turk and Samasource have mobilised large pools of labour towards microtasks which, often, aggregate into a larger work process made opaque to the labour used to complete them. Some link this micowork to poverty alleviation suggesting the public good that might arise from such a workplace and larger industry reconfiguration. Yet, an important feature of microwork is a general placelessness that subverts labour and the communities from which this labour emerges.
Education has largely aligned itself with this efficiency and microwork maxims in moves towards granular capacities that are both restrictive and empowering. In these contexts education is reduced to serving the granularization in work that automation and microwork has accelerated. Yet, there is a role for an education that embraces the ‘messy’ configurations of digital labour, one that provides a futures dimension and a critical capacity for redefining the futures of work. This chapter explores this microwork contexts and suggests several educational reconfigurations that might serve this critical capacity.
Gallagher, M. (2019 forthcoming). Artificial intelligence and the mobilities of inclusion: the accumulated advantages of 5G networks, machine learning, and surfacing outliers. In (J. Knox ed.) Inclusive Education, ICT, and Artificial Intelligence. London: Springer.
The burgeoning use of artificial intelligence in a learning increasingly mediated through mobile technology makes inclusion problematic. This is largely due to the sheer ubiquity of mobile technology globally, the complexity of the machine learning regimens needed to function within increasingly sophisticated 5G cellular networks, and the legions of professionals needed to initiate and maintain these AI and mobile ecosystems. The promise of artificial intelligence in inclusion is curtailed precisely due to the accumulated advantage (the Matthew effect) presented in such a technological sophistication: only those with the most sophisticated and agile of educational systems will stand to benefit, a scenario that poses significant impact on inclusion strategies increasingly mediated through ICT.
Further, the accumulated advantage is not only a dichotomy between those with access to these sophisticated technologies and those that do not enjoy that same privilege. A further parallel is between the “curriculum” of machine learning of artificial intelligence in 5G networks as outlined in Li et al (2017) and traditional and human-centred educational curricula that is being increasingly redrawn as a reductionist enterprise aligned with national and international quantitative metrics. While AI has evolved to include multidisciplinary techniques such as machine learning, optimization theory, game theory, control theory, and meta-heuristics in both supervised and unsupervised formats, traditional educational curricula is increasingly influenced by third party commercial enterprises and reductionist moves towards computational thinking.
This poses significant disadvantage to educational inclusion beyond technological advantage, the sophistication of machine learning curricula, or the general paucity of human curricula increasingly modeled on computational thinking; the biases at work in larger society are encoded into the datasets that machine learning operates. Inclusion operates, statistically, as an outlier in these data-driven environments; as an equitable model in education, largely designed to counter prevailing societal biases, rather than conform to them. The equity that this inclusion seeks to provide is not inherently a naturally-occuring entity and will not render naturally in the data that AI is learning from. As more and more education is engaged through mobile technology and more and more of that mobile learning is driven by an artificial intelligence emerging from curricula of greater and greater sophistication, a situation emerges that poses great challenges for any sort of meaningful inclusion, particularly in the potential acceleration of entrenched advantage.
Gallagher, M. (2019). Disposition, abstraction, and distilling a complex cosmopolitanism in mobile spaces. In M. de Laat, N. Bonderup Dohn, P. Jandric, T. Ryberg, (eds.). Politics, agency and data in Networked Learning. London: Springer.
The capacity of individuals or systems to generate or learn how to generate a metastability, a state of navigating the largely unmanageable aspects of complexity, “cannot be reduced either to the actions of individual actors or to persisting social structures” (Urry, 2016: 59). It is a complexity resists proportionality or linearity; small changes can generate large structural consequences, and individuals will, intellectually or dispositionally, exert considerable resources towards navigating this metastability, exhibiting, on occasion, cosmopolitan identities in the process.
This paper explores this complexity through Amira, a Nepalese woman studying in a postgraduate programme in Europe. Drawing on mobilities theory, chaosmosis, and cosmopolitanism, the habitus of Bourdieu is repurposed as disposition; a tendency of an individual to act, react, or think in a particular way based on the social systems through which they move. Disposition is advanced in as a necessary addition to the theorizing of mobilities and mobile learning respectively, one that countenances Amira’s navigational practices and learning. It provides a foundation from which to observe engagement and interaction across mobile spaces and subsequently observe how that mobile activity is then siphoned back into other learning spaces. It is a fluid process of engagement across multiple contexts, some being materially, cognitively, and dispositionally mobile. Ultimately, it is one that Amira must negotiate to maintain the mobility on which she depends. Mobile learning, if it to be of use to Amira, needs to account for the wider range of this activity: across multiple interactional contexts, amongst people and interactive technologies, encapsulating public and private processes; activity that moves between micro (Amira’s) and macro (those “immanent to the material conditions of global interdependence”) systems. Amira needs capacity to artfully manage her movement through these systems of complexity, and through the ‘diaspora’ of her mobility. Disposition is advanced in this paper as a means of expanding her capacity to navigate the complexity of her own mobility.