Autonomy and the Machine
It is well-established that the purpose of a liberal education is to enable individuals to see themselves as free, self-determining and responsible for their actions. Meanwhile, discourses of digital technology emphasise empowerment, particularly in terms of personalisation and choice. Technology would therefore seem like a good fit for autonomy.
But, for all that technology offers, it can impose practices, values and routines that may be incongruous or inconsistent with an individuals preferences or desires. For example, if a learner use a platform that collects data, then that data can subsequently be used to guide learning. While this is typically framed in terms of assistance, the power of technology now goes well beyond assistance and it could be said that technology itself has agency.
This means that using technology or participating in online environments or other platforms (such as a game), human agency needs to be subordinated or traded off in some way.
The increasing power of technology troubles our understanding of autonomy. Understanding and being able to locate autonomy is fundamental in highly technicalised learning environments and any inquiry into learning technology must consider how it affects the capacities of learners. We might emphasise the empowerment of the humans, or the capacities of the machine, but there is a danger that a focus on one elides an understanding of the other. Autonomy is relative, indeterminate and, in any scenario, others (including technology) may have the upper hand.
Consider the example of nudge economics, a technique used in behavioural economics that manipulates people by narrowing choices or prompts towards a particular behaviour. The use of nudges to influence learning denies autonomy to learners, though it may result in favourable outcomes. For many learners, these nudge structures may be welcome and useful, and its certainly a seductive idea, but it raises questions about who is really in control of learning. For the most part, however, learner autonomy is poorly understood and may fall back on essentialist or deterministic accounts of learning that do not account for the indeterminacy of autonomy.
