Tag: machine learning

This monologue by Mrs Wilson at the end of Gosford Park immediately made me consider how digital assistants, driven by datasets such as Amazon’s buying and viewing history for a long term users, might one day come to constitute an ideal of service as thick as the one we see represented in films like this: What […]

On pg 258-259 of her Don’t Be Evil, Rana Foroohar poses a question which will become more urgent with each passing year, binding political economy and digital governance together in a way which will define the fabric of social life: Is digital innovation best suited to an environment of decentralization, in which many firms in […]

From Automating Inequality by Virginia Eubanks pg 167: Parents in Allegheny County helped me articulate an inchoate idea that had been echoing in my head since I started my research. In Indiana, Los Angeles, and Allegheny County, technologists and administrators explained to me that new high-tech tools in public services increase transparency and decrease discrimination. […]

I thought this was extremely powerful by Virgina Eubanks in Automating Inequality. She explains on pg 121-122 how machinic learning systems can operate as a form of triage, sorting people in order to distribute scarce resources in a seemingly more rational fashion: COunter INTELligence PROgram of the FBI), for example, focused on civil rights activists […]

The promise of introducing machine learning into public administration is that it can counteract human bias. The latent promise of bureaucracy can be realised by systems that won’t be up-ended by the messy imperfections of their human operators. However Virginia Eubanks makes clear in Automating Inequality that the reality is something much more worrying, as […]

My notes on Rahwan, I. et al. (2019) Machine Behaviour. Nature, 568, 477–486 The proliferation of intelligent machines, ranging from machine learning systems through to their embodiment in robotics, raises the question of how their behaviour should be studied and understood. In this agenda setting paper, the team of authors suggest this now requires the deliberate formation of a […]

My notes on Andrejevic, M., Hearn, A., & Kennedy, H. (2015). Cultural studies of data mining: Introduction, European Journal of Cultural Studies 18(4-5), 379-394 In this introduction to an important special issue, Mark Andrejevic, Alison Hearn and Helen Kennedy that the ubiquity of data infrastructure in everyday life means that “we cannot afford to limit our thinking about data […]

Tuesday December 4th 12pm Faculty of Education, University of Cambridge Everyone welcome! It’s a short journey from Cambridge train station We hear a lot about the coming ‘automation revolution’, but what might developments in machine learning and AI mean for researchers in the social sciences and humanities? In our next masterclass, Associate Professor Inger Mewburn […]

The robots are coming! The robots are coming! After watching More Human Than Human, I’ve woken up preoccupied by the rise of the robots narrative and how inadequate it is for making sense of the cultural politics and political economy of automation. The film is an engaging exploration of artificial intelligence and its social significance. While its […]

How good does this look? So much of this chimes with the paper I’m currently struggling to finish The Cultural Life of Machine Learning: An Incursion into Critical AI Studies Preconference Workshop, #AoIR2018 Montréal, Canada Urbanisation Culture Société Research Centre, INRS (Institut national de la recherche scientifique) Wednesday October 10th 2018 Machine learning (ML), deep […]