Event | Playing Domains – Masterclass with Sam Hind (University of Manchester)

Event | Playing Domains – Masterclass with Sam Hind (University of Manchester)
Date: 14 March 2025
Time: 10:00-12:00
Location: room 0.16, Media Studies, BG1 (Turfdraagsterpad 9, Amsterdam)
Contact & Registration: L.Kopitz@uva.nl
Registration Deadline: 9 March 2025
Credits: 1 ECTS

In this masterclass we will examine the growing phenomenon of machine vision ‘challenges’, used in big tech to drive innovations in AI and machine learning (ML). Competitions and prizes have long been used to stimulate scientific and technological discoveries – The British Longitude Prize was launched in 1714 to find an accurate method for determining longitude on the high seas. More recently, the Netflix Prize (2006), DARPA Grand/Urban Challenges (2005-2007), and Manchester Prize (2023) have attempted to drive innovations in algorithmic, autonomous, and AI systems. Across these examples and more, different kinds of collaborative play are seemingly integral to the (competitive) development practices of computer scientists and AI practitioners. The workshop will seek to make sense of this ostensibly ‘technical’ work underpinning machine vision cultures: both the role of online ‘sandboxes’ (such as Google Colab) for such work, and the spectral representation of urban environments (in training datasets) as they become the raw material for machine vision challenges.

Bio

Sam Hind is lecturer in digital media and culture at the University of Manchester, UK. His current research interests include machine vision challenges, autonomous driving, the history of computer simulation, and the platformization of automobility. He recently published Driving Decisions: How Autonomous Vehicles Make Sense of the World (Palgrave).

Reading preparation

• Hind, S., van der Vlist, F. N. and Kanderske, M. (2024). Challenges as catalysts: How Waymo’s Open Dataset Challenges shape AI development. AI & Society 0 (0): 1-17. https://doi.org/10.1007/s00146-024-01927-x
• Orr, W. and Kang, E. B. (2024). AI as a sport: On the competitive epistemologies of benchmarking. FAccT ’24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency 1875-1884. https://doi.org/10.1145/3630106.3659012