I watched a demonstration of this automated essay-improving software on YouTube and desperately want to try it out to see if it works. I thought it interesting that in these days of hypermedia one of the aims of OpenEssayist was to ensure student essays followed the traditional beginning, middle and end, showing how our narrative linear literacies have not been challenged here.
Databite No. 70: Tarleton Gillespie
Tarleton Gillespie (@tarletonG) presents #Trendingistrending: When Algorithms Become Culture:
I liked this on YouTube and have left iftt and YouTube’s default information feed into my lifestream, just adding the bold emphasis to the last sentence.
Algorithms may now be our most important knowledge technologies, “the scientific instruments of a society at large,” and they are increasingly vital to how we organize human social interaction, produce authoritative knowledge, and choreograph our participation in public life. Search engines, recommendation systems, and edge algorithms on social networking sites: these not only help us find information, they provide a means to know what there is to know and to participate in social and political discourse.
If not as pervasive and structurally central as search and recommendation, trending has emerged as an increasingly common feature of such interfaces and seems to be growing in cultural importance. It represents a fundamentally different logic for how to algorithmically navigate social media: besides identifying and highlighting what might be relevant to “you” specifically, trending algorithms identify what is popular with “us” more broadly.
But while the techniques may be new, the instinct is not: what today might be identified as “trending” is the latest instantiation of the instinct to map public attention and interest, be it surveys and polling, audience metrics, market research, forecasting, and trendspotting. Understanding the calculations and motivations behind the production of these “calculated publics,” in this historical context, helps highlight how these algorithms are relevant to our collective efforts to know and be known.
Rather than discuss the effect of trending algorithms, I want to ask what it means that they have become a meaningful element of public culture. Algorithms, particularly those involved in the movement of culture, are both mechanisms of distribution and valuation, part of the process by which knowledge institutions circulate and evaluate information, the process by which new media industries provide and sort culture. This essay examines the way these algorithmic techniques themselves become cultural objects, get taken up in our thinking about culture and the public to which it is addressed, and get contested both for what they do and what they reveal. We should ask not just how algorithms shape culture, but how they become culture.
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This is a quick mind-map made after reading Jeremy Knox’s paper on Active Algorithms, 2015.
The article was a really useful and clear link between the community cultures we have been studying on ECD and algorithmic cultures we are beginning to look at now, demonstrating how the technical (algorithmic), social and material come together to constitute situations in which agency becomes blurred and impossible to locate.
I explored the concept of sociomateriality in my last mscde module, focusing on using it as an approach for IT personnel to examine the ways in which technologies are designed, supported and used. Knox’s paper has added an extra dimension to this study of sociomateriality by thinking of it in spatial terms – the contingent and complex enactment of a learning space as enabled by the social and material.
There is a tendency to think of coding and algorithms as being non-human agentic forces, forgetting the very human intention that has gone into their compilation. Rather, in the non-human camp, and after my experience of ifttt, I would add breakdown and intermittent loss of connectivity and functionality as threads in the entanglement. These happenings are a very real and affective part of our experience of technology and they are often due to emphatically material failure.
I have now just started reading the Gillespie article which makes me want to investigate our creeping acceptance of algorithmic control. We acquiesce in Google’s algorithms because we find it such a useful search engine, we make ourselves marketing targets because online retailers are so convenient. We submit to the narrowing chambers of our social media sites threaded with popular news items, even fake ones, because it is great to keep up with our friends.
It is interesting that the government carefully researches ‘nudging’ us to make ‘better choices for ourselves’ (Behavioural Insights team) whilst watching our global corporations use every trick in the book to relieve us of our cash.