Ways of machine seeing

Learning experiments in computer vision and visual literacy

What opportunities and challenges does AI present for the art and design classroom?

The development of this wiki follows workshops with artists and educators that took place at the Institute of Education and The Photographers' Gallery in Autumn 2022, exploring how computer vision impacts upon visual literacy in schools. We take our point of departure in John Berger's ''Ways of Seeing'' (1972), and consider the ways in which humans and machines now learn to see. Our aim is to produce an iterative teaching resource (toolkit), open to further development by all interested in the topic.

If you'd like to contribute, or find out more, please contact us.

Computer Vision Activities

• Seeing at speed, an experiment about human and machine vision
• Algorithmic bias
• Face detection
• Inside the Black Box of text-to-image AI
• Machine Teaching (initial sketch)

Resources

• Artists
• Glossary
• References
• Events
• Reflexive accounts
• Workshop notes
• Suggested areas of discussion
• Website with classroom activities

Credits

Learning Experiments in Computer Vision and Visual Literacy is a public engagement project funded by The Alan Turing Institute, as part of a research collaboration between the Centre for the Study of the Networked Image (CSNI) at London South Bank University, UCL Institute of Education, and The Photographers' Gallery. With contributions from Geoff Cox (CSNI), Annie Davey (UCL IoE), Yasmine Boudiaf (Justice Matrix), Nicolas Malevé (Constant/Aarhus University), Janice McLaren (The Photographers’ Gallery), Yugyoung Choi (UCL IoE), Hsin-Mei Lin (UCL IoE), Siddony Kalair (Roding Valley High School), Makaila McKenzie (Heartlands High School), James Stevenson (Forest School), Nikoletta Papaxenophontos (St. Paul’s Way School), Andrew Dewdney (CSNI), Tim Fransen (CSNI), Dean Kenning ...