New digital tools, such as Generative AI, are easily available to young people through everyday media and yet little formal guidance exists for how students can use these technologies safely or responsibly.
The Ways of [Machine] Seeing project, inspired by John Berger's influential work Ways of Seeing, offers a guide to best practice for secondary school teacher training and curriculum development. It has been developed in collaboration with Art & Design teachers to create, test and refine a series of accessible, engaging activities exploring AI.
From questions about authorship to bias and automation, this afternoon session aims to inform and explore the use of AI in the classroom.
If you can no longer attend, please email learning@tpg.org.uk so we can offer your place to someone else.
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Event agenda
14:00 - 14:15 Welcome
14:15 - 14:45 Ways of [Machine] Seeing project intro
14:45 - 15:30 Practical activity: Unmasking Facial Recognition with Shinji Toya
15 min break
15:45 - 16:30 Panel discussion with teachers: Responses to the Learning Resource in action
16:30 - 16:45 Launch of the website and publication (Ways of [Machine] Seeing: An introduction to using GenAI in the art and design classroom) , with Ricebox Studio
16:45 - 17:30 Drinks reception
About the "Ways of [Machine] Seeing' project
Ways of [Machine] Seeing: Towards a new visual literacy in AI (Sept 2024 – July 2025) is developed by CSNI (Centre for the Study of the Networked Image) at London South Bank University (Geoff Cox, Tanya Boyarkina, Tim Fransen), UCL Institute of Education (Annie Davey), Justice Matrix (Yasmine Boudiaf) and The Photographers’ Gallery. The project team builds upon previous research carried out through a public engagement grant from The Alan Turing Institute entitled “Learning Experiments in Computer Vision and Visual Literacy” (2022-23).
This project is supported by the Engineering and Physical Sciences Research Council [grant number EP/Y009800/1], through funding from the Responsible AI (RAi UK) Skills Programme [RAI-SK-BID-00071]. Further support is provided by the Digital x Data Research Centre at London South Bank University.