Media, Technology and Culture 09: Algorithmic Technologies

Publicly Sited

There is now widespread awareness of, suspicion about, and even opposition to 'algorithms'. As widespread as the multiplicity of situations and domains in which these mysterious entities seem to be making more and more decisions: around welfare payments; university places; travel routes; and police patrol routes. Algorithms are also pervasive in media and communications. They build you customised magazines with news from several sources, help inform what movies you watch, the posts you see in your social media feeds, the way a matchmaking website pairs you with others, not to mention all that advertising and direct marketing. Media today are personalised, whether we want them to be or not. And we are becoming more than a little worried about these algorithmic agents that seem to make all this personalisation possible. Their computational decision making, their capacities at deep learning: so hidden; so obscure. In this episode, we think about the growing role of algorithms in shaping contemporary media cultures, from the early rise of apps and personalised ‘filter bubbles’ to the rather ordinary recommendation systems we rely on today. We also grapple with growing concerns for how deep structural biases around race, class, gender and sexuality are embedded into and reinforced by the way algorithms – such as those enabling facial recognition technologies – actually work. But we will also ask: what if the politics of algorithms is not just about prying these black boxes open, revealing their internal biases and perhaps correcting them? Instead, might it be that we need to understand the problematic social and cultural conditions from which these algorithms and associated technologies sprout up, get nurtured and grow?

Thinkers Discussed: Eli Pariser (The Filter Bubble: What the Internet is Hiding From You); Blake Hallinan and Ted Striphas (Recommended for You: The Netflix Prize and the Production of Algorithmic Culture); Raymond Williams (Keywords); Daniela Varela Martinez's and Anne Kaun (The Netflix Experience: A User-Focused Approach to the Netflix Recommendation Algorithm); Safiya Umoja Noble (Algorithms of Oppression: How Search Engines Reinforce Racism); Ruha Benjamin (Race After Technology: Abolitionist Tools for the New Jim Code); Axel Bruns (Are Filter Bubbles Real?); Frank Pasquale (The Black Box Society: The Secret Algorithms That Control Money and Information); Taina Bucher (If...Then: Algorithmic Power and Politics); Mike Ananny and Kate Crawford (Seeing Without Knowing: Limitations of the Transparency Ideal and its Application to Algorithmic Accountability).