Corbyn! Trump! Brexit! Politics has never been more unpredictable, more alarming or more interesting. TALKING POLITICS is the podcast that will try to make sense of it all.
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Another one of my favourite podcasts, but this time it’s totally relevant to this course. Look at the synopsis for it:
This particular episode looks at the ways in which politics and technology intersect, socio-critical and socio-technical issues around power and surveillance, the dominance of companies, and the impact of the general political outlook of the technologically powerful.
There are two things that I think are really relevant to the themes of the algorithmic cultures block. The first is about data. Data is described as being like ‘the land […], what we live on’, and machine learning is the plough, it’s what digs up the land. What we’ve done, they argue, is to give the land to the people who own the ploughs. This, Runciman, the host, argues, is not capitalism, but feudalism.
I’m paraphrasing the metaphor, so I may have missed a nuance or two. It strikes me as being different from the data-as-oil one, largely because of the perspective taken. It’s not really taken from a corporate perspective, although I think in the data-as-land metaphor there’s an assumption that we once ‘owned’ our data, or that it was ever conceived by us of as our intellectual property. I have the impression that Joni Mitchell might have been right – don’t it always seem to go that you don’t know what you’ve got ’til it’s gone – and that many of us really didn’t think about it much before.
The second point is about algorithms, where the host and one of his guests (whose name I missed, sorry) gently approach a critical posthumanist perspective of technology and algorithms without ever acknowledging it. Machine learning algorithms have agency – polymorphous, mobile, agency – which may be based on simulation but is nonetheless real. The people that currently control these algorithms, it is argued, are losing control, as the networked society allows for them to take on a dynamic of their own. Adopting and paraphrasing the Thomas theorem, it is argued that:
If a machine defines a situation as real, it is real in its consequences.
I say ‘gently approaching’ because I think that while the academics in this podcast are recognising the agency and intentionality of non-human actants – or algorithms – there’s still a sense that they believe there’s a need to wrest back this control from them. There’s still an anthropocentrism in their analysis which aligns more closely with humanism than posthumanism.