The Thames Path 2040
By Lex Fefegha
Image credit: Lex Fefegha
In South London's Peckham neighborhood, artist Lex Fefegha confronts an unsettling reality: over a million Londoners live in flood plains, with 17% of the city at medium to high flood risk. Through ‘Thames Path 2040' he uses AI to transform familiar streets into evocative visions of possible futures, exploring how rising waters might reshape London's communities.
Concept and vision
Fefegha's work responds to a growing crisis; according to the UK government’s analysis, around 5.2 million properties in England face flood risk, with that number expected to double over the next 50 years. Rather than presenting these statistics in isolation, he sought to create images that would stir emotional connections to this possible future. The project focuses on his home neighborhood, Peckham, using AI to blend present-day streets with scenes from flood-affected areas elsewhere.
Technical journey
Using The New Real Observatory platform, Fefegha developed a novel artistic approach to exploring these futures. He uploaded two distinct image sets: photographs of flood-devastated areas from around the world, and images of his local South London neighborhood near the river Thames. The platform allowed him to create a spectrum between these two realities, informed by climate model projections.
Image credit: Lex Fefegha
Working with the platform's climate data for 2040, Fefegha used projected precipitation increases to guide his artistic process. Rather than trying to create precise predictions, he used these numbers to inform how far along the spectrum between present-day and flood-affected imagery to generate his transformations – creating an artistic interpretation of possible futures.
The work
The resulting images offer provocative glimpses of how London's landscapes might transform. By connecting artistic exploration to climate projections, Fefegha creates visualisations that are both speculative and grounded in environmental data. The familiar streets of Peckham take on an uncanny quality, making abstract possibilities feel immediate.
Significance
'Thames Path 2040' suggests new possibilities for artistic engagement with climate futures. By using AI as a tool for environmental speculation, Fefegha shows how artistic practice can help us imagine and emotionally connect with possible futures, while making climate projections feel more tangible and personally relevant.
The work demonstrates how The New Real Observatory platform can help artists create compelling environmental narratives. It suggests new ways of using machine learning to explore possible futures, while reinforcing the urgency of addressing challenges to come.
Footnotes
The New Real Observatory is part of The New Real, a partnership between University of Edinburgh, Edinburgh’s Festivals and The Alan Turing Institute. Featured artists Adam Harvey, Inés Cámara Leret, Keziah MacNeill, Lex Fefegha.
Supported by UK Research and Innovation (EPSRC, AHRC), Towards Turing 2.0, Creative Scotland, Scottish AI Alliance, and the Data-Driven Innovation Programme.
‘The Thames Path 2040’ was commissioned as a project of The New Real Observatory, developed between December 2021– August 2022, and first exhibited at ARS Electronica 2022, Linz, Austria.
Links
Artist bio
Lex Fefegha spends most of his time leading a small team of designers and coders at COMUZI, a London-based design studio creating future-positive products, services and experiences for governments, organisations and charities.
In his spare time, he has been exploring AI & creativity projects, working with Google AI & Google & Arts Culture Lab to create The Hip Hop Poetry Bot, an AI research project, exploring speech generation trained on rap and hip hop lyrics by black artists. Lex was an associate
lecturer at the University of the Arts London's creative computing institute teaching a module on computational futures and AI.
Cite as: Lex Fefegha (2025). ‘The Thames Path 2040.’ The New Real Magazine, Edition Two. pp 20-22. www.newreal.cc/magazine-edition-two/the-thames-path-2040
