The Tuning Machine

A presentation at the Future of The Humanities series of lightning talks at UQ in April 2019. Katherine N. Hayles observed in How We Became Posthuman that the limiting factor in digital culture is not going to be the data-processing power of computers but rather, but rather ‘the scarce commodity’ like it always has been in media cultures, is ‘human attention’. A crucial form our participation takes in culture today is as coders of databases. We are a crucial part of the tuning machine - the historical process of training platform algorithms to sense, process and optimise our living attention. Of making our humanness, affect and feeling machine readable. Digital platforms’ investment in data-driven classification and simulation is characterised by what Mark Andrejevic calls the tech-ideology of ‘framelessness’: the fantasy that by scooping up data, we can create a ‘mirror-world’, a perfect digital copy of reality. What the humanities knows though is that this project is a flawed one. The human experience of reality is necessarily partial. We humans insist on a world ‘small enough to know’, to narrate, to make meaning from, and to imagine as different from what is now. The humanities can help to contend with the risk that focussing only on the fairness, accountability and transparency of algorithmic systems makes an algorithmic future inevitable, and understandable only as a series of technocratic decisions about how to administer life in network capitalism. The humanities of the future will push us beyond procedural questions, to questions about how media can and cannot operate on human experience and feeling, and what enduring role media will play in the possibility of a shared culture. What the humanities knows is that coding databases and training algorithms, like everything else humans try to do together and to each other, is deeply entangled with culture - with structures of feeling and systems of dominance.

Om Podcasten

Thinking about the entanglements between humans and machines that collect, store and process data.