Exploring the facts behind the fiction

Presented by the School of Informatics and the Edinburgh Laboratory for Integrated Artificial Intelligence
A future we can imagine is a future we can build
It is a very human habit to imagine the future. When we envision the future through film where AI is concerned, themes of fear and loss of control are central. From indie cinema to Hollywood, what we see on screen shapes our opinions on artificial intelligence and what its growing prevalence means for humanity.
The most common depiction of AI on film can be lumped into two categories: The anthropomorphised Other who alienates and destroys, or the anthropomorphised Other who is much like us yet could never be us, who then gets alienated and destroyed. In film, there is little room for visions of AI which ease rather than aid human folly. That’s where Imagining Futures: AI on Film comes in.
From 1927 silent masterpiece Metropolis to 2022 Sundance London’s Audience Favourite Brian and Charles, the programme spans decades and genres: it includes sixteen screenings of sci-fi and anime cult classics, comedies, thrillers and documentaries, accompanied by talks and panels.
Edinburgh University academics and invited guests will introduce the films and guide the audience to challenge their own views on AI whether drawn from cinema or elsewhere.
The 5-day film festival continues the 60 Years of Computer Science and AI anniversary celebrations at the University of Edinburgh.
In 1963 the University established its first research hubs in these disciplines. A year-long programme of events marks achievements over the past six decades and looks to the future of computer science and AI at Edinburgh.
Alan Turing imagined a child computer that, like Pinocchio, would dissemble so well that we’d believe it to be human. Was Turing’s child a cautionary tale rather than instructions for what should come? Imagining Futures: AI on Film will bring you one step closer to deciding for yourself.
- AlphaGo
- MindGames: Games and AI (panel)
- WarGames
- Metropolis
- Archive
- WALL·E
- Moon
- 2001: A Space Odyssey
- Ron's Gone Wrong
- Pinocchio
- Only Connect: Storytelling and AI (panel)
- A.I. Artificial Intelligence
- Brian and Charles
- Her
- iHUMAN
- Moral Coding: Ethics and AI (panel)
- The Internet's Own Boy: The Story of Aaron Swartz
- Ghost in the Shell (1995)
- Little Joe

Tickets to each film are sold individually for £8.
Early Bird Festival passes are £76 and are on sale until the end of 13 August. This price is 50% off the total value of all festival events.
Regular festival passes, on sale after 13 August, are £106. This price is 30% off the total value of all festival events.
Tickets to panels are complemented by the films preceding and following the panels, and as such panel tickets are sold in combination with either film.
*Concession prices are available on all tickets for students, under 18s, over 65s, those who are disabled, on pension credit, universal credit, employment and support allowance or jobseeker's allowance. To purchase a concession ticket, please use the promo code CONCESSION for 25% off.*
Sponsors
The festival gratefully acknowledges the support of the School of Informatics at the University of Edinburgh and ELIAI, The Edinburgh Laboratory for Integrated Artificial Intelligence.
The School of Informatics at the University of Edinburgh is the largest in the UK and one of the largest in Europe. It is recognised internationally for excellence of its research outputs, education and knowledge exchange. The central focus of research and teaching in the School of Informatics is the transformation of information - whether by computation or communication, whether by organisms or artefacts. Understanding informational phenomena - such as computation, cognition, and communication - enables technological advances.
Link to the School of Informatics website
ELIAI, funded by UKRI and industrial partners, is seeking to enhance neural network models with reasoning capabilities, a skill required to enhance many AI applications. ELIAI is developing a theoretical framework which characterises what it means for neural network models to reason, designing various reasoning modules, and showcasing their practical importance in applications.