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Close-up of a digital supermodel wearing a thick gold necklace, bright red lipstick and gold hoop earrings, looking straight at the camera, her hands are on her head.

Design; Disruption; Divergence

Curated by Jennifer Anyan, Edward Ward and Jordan Cutler
Words by Suzanna Hall

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  • TheGallery
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  • AUB Campus

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Dates: 14 February – 24 April 2025

Location: TheGallery, AUB Campus; and in a virtual exhibition space

TheGallery, The Library, and the Innovation Studio working in partnership with the Schools of Arts, Media, and Creative Industries Management, Arts and Communications, and Design and Architecture, Graduate School, and AUB Outreach and Alumni Office, present Design; Disruption; Divergence – an exhibition that looks at how Generative AI is impacting on artists’ practice.

This exhibition and the associated events explore identity politics in digital representation and creative AI, contributing to important and current conversations around, authenticity, diversity, and ownership in digital spaces.

Exhibition overview

Design; Disruption; Divergence opens the door to the evolving relationship between imagination and innovation. This exhibition doesn’t just showcase what AI can make – it interrogates what AI means for the act of making itself. In a time when algorithms are part of our everyday world, this is all about how AI collaborates with human imagination. From hyperreal avatars to surreal designs that dissolve the line between the real and the virtual, you’ll discover the many ways AI can be utilised in creative practice. AI emerges here as more than just an assistant; it’s a mirror reflecting our hopes and anxieties about the future of creativity in the digital age. These works illustrate AUB’s proactive engagement with AI and its impact on creative industries, underscoring the need for human guidance and design thinking in shaping its role in artistic practice.

Artists across the UK are finding new uses for AI, inspiring works ranging from uncanny AI kittens at Somerset House to deepfake drag cabarets at the V&A. This exhibition builds on these advancements, showcasing how AI-assisted art is reshaping cultural discussions and redefining what's conceivable in artistic practice. However, alongside this are deeper questions about the ethical, environmental, and social perils of these tools. We must foster a realistic understanding of the limitations and risks of AI. So, while looking at these works, we also invite the question: What does this technology cost us?

So, wander through the fragmented realities, let yourself be drawn into alternate histories, and confront impossible futures. But most importantly, ask questions. This exhibition is as much about discovery as it is about dialogue – between humans, machines, and the possibilities yet to come.

This exhibition can also be viewed from the comfort of your own home, school, or college via a VR headset. Find out more and book your space.

Exhibition development team

This exhibition was developed and made possible by Lisa Mann, Jennifer Anyan, Violet M. McClean, Tim Metcalf, Christian McLening, Suzanna Hall, Penelope Norman, Edward Ward, Jordan Cutler, Beverley Bothwell, Cameron-James Wilson, Andrew England, Millie Lake, Fiona Bavinton, James Garside and William Hernandez Abreu.

Meet the curators and artists

Curator of the exhibition at TheGallery, AUB

J Anyan headshot

Jennifer Anyan

Jennifer is the Director of AUB’s School of Arts, Media, and Creative Industries Management, and is well positioned...

Curators of the virtual exhibition space

Headshot for E Ward

Edward Ward

Edward Ward is a multimedia artist, academic, spatial designer, maker, and creative technologist. He's drawn to the process of...

Headshot for J Cutler

Jordan Cutler

Jordan Cutler is a Lecturer on BA (Hons) Games Art and Design and a Technician Demonstrator for AUB’s Lab for Creative Technology.

Headshot for R Amey.

Rob Amey

Rob Amey is a photographer and filmmaker whose work explores the multifaceted relationship between spirituality, technology...

Headshot of B Aslan

Burcu Aslan

Burcu Aslan is a multidisciplinary designer and researcher specialising in AI-driven workflows for fashion, interiors, and digital...

Black and white photo of a person making a large bubble in a back garden.

Libby Billings

Libby Billings is a photographer and moving image artist. Before joining Arts University Bournemouth as a Technician Demonstrator...

Headshot for C Cahill

Clare Cahill

Clare Cahill is a creative producer and educator, a Senior Lecturer on the BA (Hons) Film Production course at AUB...

Headshot for F Bavinton

Fiona Bavinton

Fiona Bavinton is a creative technologist and storyteller with 20 years’ experience as a software engineer and technical lead...

Jessica Lowther

Jessica Lowther is a third-year BA (Hons) Photography student at AUB. Her work examines memory, authenticity, and AI by...

L Moro standing in front of a colourful, futuristic 3D artwork.

Lisa Moro

Lisa Moro’s practice navigates the thresholds between the absurd and the profound, the factual and the fantastical...

R Paul sitting in a gallery space with canvases behind him in the background.

Richard Paul

Richard Paul is an artist based in Southeast London. His work is concerned with material transformation and subjective perception...

Headshot of A. Pearson.

Anya Pearson

As a fashion design and manufacturing specialist, statue builder, published academic, and feminist campaigner, Anya's work challenges...

I. Sousa standing next to a monitor at TheGallery, AUB. The monitor screen shows a young person sitting cross-legged with a glowing red sphere in his lap.

Ione Pinto De Matos De Sousa

Ione Pinto De Matos De Sousa is a multidisciplinary artist with a background in 3D, animation, filmmaking and game development...

Headshot of Professor S N Sobers

Shawn Hailemariam Sobers

Dr Shawn Sobers is Professor of Cultural Interdisciplinary Practice at the University of the West of England...

Headshot of C-J Wilson

Cameron-James Wilson

Cameron Wilson is a British visual artist and founder of The Diigitals, the world’s first all-digital modelling agency. Known for...

Artificial Intelligence: in detail

1950: Alan Turing introduces the concept of "machine intelligence" and the Turing Test to evaluate if a machine can mimic human intelligence.

1956: John McCarthy coins the term "Artificial Intelligence".

1964: Joseph Weizenbaum develops ELIZA, the first chatbot, which simulates human conversation using a simple text-response algorithm.

1974: James Lighthill's critical report on AI's overhyped promises triggers the first "AI winter," slashing funding and interest.

1980: AI research rebounds as IBM pioneers machine learning models for probability-based decisions.

1982: John Hopfield develops the Hopfield Network that can learn and remember patterns, revolutionising our understanding of memory.

1987: AI faces another setback with the second "AI winter" caused by failures and budget cuts.

1997: IBM's Deep Blue defeats world chess champion Garry Kasparov, marking a milestone in AI ability.

2011: Apple launches Siri, bringing AI-driven voice assistants to mainstream smartphones.

2014: Ian Goodfellow introduces GANs (Generative Adversarial Networks), which can generate realistic synthetic images and videos, enabling the creation of "deepfakes."

2014: Google releases DeepDream, an algorithm that produces surreal, dream-like images using neural networks.

2016: Microsoft’s chatbot Tay, designed to learn from Twitter users, gets corrupted by inappropriate interactions, showcasing the risks of AI in uncontrolled environments.

2016: Sophia the robot, the world’s first non-human to be recognised with legal personhood, is activated, combining robotics and AI.

2017: Researchers at Google launch the first Transformer, capable of reading all words in a sequence simultaneously. First applied to Google Translate, it laid the groundwork for generative text models.

2018: OpenAI unveils GPT (Generative Pre-trained Transformer), capable of performing a wide range of language tasks.

2020: GPT-3, OpenAI’s groundbreaking language model, debuts, demonstrating exceptional versatility in text generation.

2021: OpenAI launches DALL·E, an AI model that creates images from textual descriptions.

2022: Stability AI introduces Stable Diffusion, revolutionising text-to-image generation and inspiring tools like Midjourney.

2022: AI goes mainstream. ChatGPT, launched by OpenAI, reaches a staggering one million users in five days.

2023: The Generative AI race heats up: Microsoft integrates ChatGPT into Bing. Google counters with Bard (later renamed Gemini), its generative AI chatbot.

2023: The release of ChatGPT-4 offers some key advancements, such as the abilities to use videos and images as input prompts, as well as to access the internet in real time.

2024: Meta introduces AI-generated accounts on Facebook and Instagram, but later deletes them after facing backlash.

“Any sufficiently advanced technology is indistinguishable from magic.” – Arthur C. Clarke

AI might feel like a recent breakthrough, but the journey to replicate human intelligence with machines has been unfolding for over 75 years. What once lived purely in the realm of science fiction—machines that can generate text, code, images, video, and sound in seconds—is now a reality. It feels like magic, doesn’t it? But look behind the curtain, and you’ll see it’s anything but.

Reaching this point has taken decades of research, colossal amounts of training data, and endless experimentation. And even now, AI doesn’t work alone. Human creativity and judgement are woven into every step – writing the prompts, curating the training datasets, and critically assessing outputs. The fingerprints of human intervention are everywhere, reminding us that AI isn’t a replacement for human effort but an extension of it.

So, while AI might look like magic, it’s really a collaboration – a fascinating blend of technology and human ingenuity working together to reshape what’s possible.

“AI is whatever hasn't been done yet.” – Larry Tesler

In 2025 and beyond, artificial intelligence remains a driving force in cultural, technological, and economic transformations. Once an invisible enabler of innovation, AI now dominates the global conversation, reshaping industries and redefining possibilities. Groundbreaking applications are emerging daily, from revolutionising personalised medicine to advancing creative fields, empowering both experts and everyday users to tackle problems that once seemed insurmountable.

But with great power comes even greater responsibility. Questions about privacy, data ownership, and copyright have taken centre stage as industries and governments race to shape the future of AI development. While the potential benefits are boundless, the need for responsible innovation has never been clearer.

From chatbots to personalised recommendations, AI tools have long quietly transformed how we work and live, often without being recognised as “intelligent.” As AI continues to push boundaries, the challenge isn’t just about advancing technology – it’s about ensuring that progress is guided by accountability and ethics. By balancing innovation with responsibility, we can shape AI to amplify human potential and serve as a force for collective good.

Looking backwards into the future: the history of AI

  • Boden, M.A. (2018). Artificial intelligence: a very short introduction. Oxford: Oxford University Press.
  • Burgess, M. (2021). Artificial intelligence: how machine learning will shape the next decade. London: Random House Business.
  • Cave, S., Dihal, K. and Dillon, S. (2020). AI Narratives: A History of Imaginative Thinking about Intelligent Machines. Oxford: Oxford University Press.
  • Mitchell, M. (2020). Artificial intelligence: a guide for thinking humans. London: Pelican.
  • Wooldridge, M.J. (2021). The road to conscious machines: the story of AI. London: Pelican.

The artist in the machine: AI-assisted creativity

  • Armstrong, H. and Dixon, K.D. (2021). Big data, big design: why designers should care about artificial intelligence. New York: Princeton Architectural Press.
  • Bernstein, P. (2022). Machine learning: architecture in the age of artificial intelligence. London: RIBA.
  • Del Campo, M. and Leach, N. (2022). Machine hallucinations: architecture and artificial intelligence. Oxford: Wiley & Sons.
  • Du Sautoy, M. (2019). The Creativity Code: how AI is learning to write, paint and think. London: 4th Estate.
  • Grba, D. (2022). Deep Else: A Critical Framework for AI Art. Digital. Vol. 2 No. 1. pp. 1–32. https://doi.org/10.3390/digita....
  • Hageback, N. and Hedblom, D. (2022). AI for arts. Boca Raton: CRC Press.
  • Luce, L. (2019). Artificial intelligence for fashion: how AI is revolutionizing the fashion industry. Berkeley: Apress.
  • Magrini, B. (2017). Confronting the Machine: An Enquiry into the Subversive Drives of Computer-Generated Art. Berlin: Walter de Gruyter.
  • Miller, A.I. (2019). The Artist in the Machine: The World of AI-Powered Creativity. Cambridge: MIT Press.
  • Navas, E. (2023). The Rise of Metacreativity: AI Aesthetics After Remix. New York: Routledge.
  • Pasquero, C. and Poletto, M. (2022). Biodesign in the age of artificial intelligence: deep green. New York: Routledge.
  • Ploin, A., Eynon, R., Hjorth I. & Osborne, M.A. (2022). AI and the Arts: How Machine Learning is Changing Artistic Work. Report from the Creative Algorithmic Intelligence Research Project. Oxford Internet Institute: University of Oxford.
  • Thiel, S. and Bernhardt, J.C. (2024). AI in Museums: Reflections, Perspectives and Applications. Bielefeld: Verlag.
  • Voigts, E., Auer, R.M., Elflein, D., Kunas, S., Röhnert, J. and Seelinger, C. (2024). Artificial Intelligence - Intelligent Art?: Human-Machine Interaction and Creative Practice. Bielefeld: Verlag.

Reasons for robophobia: Confronting the big issues with AI

  • Benjamin, R. (2019). Race after Technology: Abolitionist Tools for the New Jim Code. Newark: Polity Press.
  • Borg, J.S., Sinnott-Armstrong, W. and Conitzer, V. (2024). Moral AI: and how we get there. London: Pelican.
  • Bridle, J. (2018). New dark age: technology, knowledge and the end of the future. London: Verso.
  • Broussard, M. (2023). More than a glitch: confronting race, gender, and ability bias in tech. Cambridge: The MIT Press.
  • Crawford, K. (2021). Atlas of Ai: power, politics, and the planetary costs of artificial intelligence. New Haven: Yale University Press.
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Design; Disruption; Divergence – Formal opening and private view

Join us for the formal opening of Design; Disruption; Divergence.

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