The glowing blue brain – the visual myth of AI cognition 

Four overlapping, staggered rectangles in different shades of blue are overlayed by a glowing circle. beneath, the title reads 'The glowing blue brain – the visual myth of AI cognition'

There is a blue hue in the darkness. Upon closer examination, it is a glowing blue brain, threaded with circuits and inscribed with binary code. This is not an unfamiliar sight; instead, for many of us, it is a common visual of the expansive and unstable notion of ‘artificial intelligence’ (‘AI’). Such visual representations of AI systems have become commonplace.

In this blog post, Raghu Krishnan unpacks the prominence of the glowing blue brain imagery as a visual signifier of AI and considers its implications for public understanding. The post focuses on three primary visual tropes: the use of luminosity or glow, the brain form and personhood, and lastly the colour blue itself, which combine to create an elaborate visual myth of AI cognition.

“The blue, the glow and the brain form combine to create a culturally situated myth of machine cognition.” 

Blue, Glow, Brain

Images associated with the blue brain metaphor for AI often include a luminous brain form surrounded by circuits and binary code, placed near a dark, futuristic background. Instead of showing AI as infrastructure, code, machinery, data or labour, it is depicted as a glowing centre of thought. In this vein, meaning comes from a combination of different components, from the brain to the use of the colour blue, and even the use of luminosity itself, that combine to provide us with a trope which presents the alignment of computation and cognition.

A screenshot of Google imagery shows a series of futuristic images of glowing blue brains, white robots, and holograms.
Figure 1. A quick Google search for ‘visualising AI confirmed the prominence of blue brain imagery. Screenshot by author on 14 July 2026.

Here, semiotic work by Sorensen and Thellefsen (2024) is useful; they claim that the blue brain metaphor in all its forms has become a foundational part of the contemporary imagery around AI. In their view, the “blue brain metaphor” for AI is clearly related to the primarily verbal metaphor “the computer is a brain”, while also moving beyond this and attaching itself to a diversity of other meanings related to potential cognition. In terms of signs and symbols, they view the metaphor as part of Umberto Eco’s notion of a socio-cultural encyclopaedia, where Eco proposed that a larger shared cultural knowledge is utilised to interpret such signs. So, for instance, the blue brain can be assigned ideas of trust due to an existing shared cultural understanding of the brain; this ‘encyclopaedia’, in his view, is open-ended, where people attach endless contextual meanings to signs embedded in a shared societal network. Simply put, these visual signs are connected to expanding and interconnected cultural knowledge, which impacts interpretation. It is this contextual nature of interpretation of images and signs that is underscored throughout the article. 

Make me Glow

Glow or illumination may seem almost natural in imagery surrounding future technology, as well as in attempts to showcase the inner workings of the mind. More recently, there have been attempts to construct an ‘anthropology of luminosity’ showing how the use and experience of light are culturally embedded. Bille and Sørensen (2007), in their work, An Anthropology of Luminosity, argue that philosophical treatises and critiques have often neglected the social role of light, the role of illuminating people, places, experiences, biases, and myth. While light is a concrete physical phenomenon, it also has its ‘lux’, or the sensual qualities formed through sight and vision. The Western primacy of vision perpetuates the importance of light and vision in experiencing the world and, often, in forming concepts (Levin, 1993). It is this emphasis on light which finds itself represented in the ‘glow’ of the blue brains used to represent AI. 

Here, this importance is sketched onto social settings, as ‘lightscapes’ operating through the interaction of light and its environment. An example of the culturally relative experience of light comes from the work of Japanese author Tanizaki, who argues that the role of shadows, or the appreciation of shadows, was crucial in Japanese material culture and way of life. Japanese aesthetics, in this view, placed a cultural emphasis on indirect light, in which material culture was meant to interact with shadows, from lacquer and ceramics to paper. Appreciation for such items, in Tanizaki’s account, relied heavily upon their emergence from the darkness, an appreciation that eventually gave way to ‘intense illumination from the west’. Therefore, the glowing brains borrow the social role of light, which is situated in the West, neglecting other cultural notions of light, as seen in Tanizakis account. 

While light is physical and sensory, it may also extend to the sacred. Morphy (1989), Gage (1995) and Pinney (2001) all argue that colour and light create luminosity, which may have sacred and spiritual dimensions, and that brilliant objects are conceived as the material manifestation of light. Here, brilliant glowing orbs, lamps, and, in our case, blue brains become objects emitting light. In these contexts, light is often imagined as a signifier of ancestral power or, in our case, future power, where the glowing blue brains signal technological potency and imagined authority in the future. Luminosity gives the AI an aura, where computation may appear as sacred.

Apart from affective qualities, the presence or absence of light has also functioned as an important metaphor in Western philosophy. From the classical age, light has often been interpreted as an important metaphor through which people experience the world; for instance, in Plato’s allegory of the Cave, prisoners mistake shadows for reality, while the movement towards light represents a transition from illusion to knowledge (Plato, 2007). 

Similarly, from the Enlightenment, light was seen as a medium through which knowledge was revealed; light hence finds itself deeply entwined with the notion of life and existence, the dead, or the soulless find themselves depicted as dark or lacking illumination. A more recent example is the use of the ‘lightbulb moment’ in comicbooks, where a lightbulb over a character’s head would signal a sudden moment of inspiration. Therefore the glowing brains borrow this  association of light with knowledge and inspiration  situated in the west, to construct an elaborate myth of cognition.

In essence, we have three different notions of light: the material lux, or glow, the social agency of light, and lastly the metaphorical light; importantly, all of these are culturally embedded. In the context of our image, materially the brain glows, socially it signals future authority, and metaphorically it points to ideas of consciousness and life. The glow of the brain  condenses these notions into a single image. The anthropology of light, in a way, provides a framework to interpret the powerful visual of the glowing blue brain, where material, social and psychological notions of light are projected onto the (blue) brain form.

This image is a collage with a colourful Japanese vintage landscape showing a mountain, hills, flowers and other plants and a small stream. There are 3 large black data servers placed in the bottom half of the image, with a cloud of black smoke emitting from them, partly obscuring the scenery.
Deborah Lupton / Better Images of AI / CC BY 4.0

Deborah Lupton’s image, ‘Servers in a Landscape ’, directly challenges the ‘glowing’ visuals of AI by representing AI as a dark cloud of smoke. The image demonstrates the impacts of data centres on the natural world through pollution emitted from the operation of the centres.

Brain dead and Brain alive.

The brain form itself has traditionally had a persuasive influence on public perception. Experimental work by McCabe and Castel (2008) argued that brain images played a role in public acceptance of neuroscience research. They argued that such images or scans of the brain provide a physical basis for abstract cognitive processes, appealing to people’s affinity for reductionist explanations of cognitive phenomena. Later work has complicated the strength of the “seductive brain image” effect (Michael et al,2013); the claim is not that brain images automatically convince people, but that they belong to a wider visual culture in which cognition seems more credible when it is made visible in the brain. Essentially, they aid communication by making the internal cognitive process seem visible and scientific. 

Dumit, in his account of brain scans and personhood, presents this notion in pop culture, showing that the AI brain is a borrowed form of scientific visual authority, where the brain, in a variety of pop culture , and has become synonymous with a modern Euromerican notion of personhood. He gives the example of brain scans being framed with simple labels like “normal,” “depressed,” or “healthy,” reducing visible types of people into individual brains. Moreover, he shows us how this imagery travels extensively from medical literature to pop culture, forming an important mediascape shaping narratives. Dumit’s (2004) ethnographic account reveals that brain scans and imagery do not travel across mediascapes alone; they carry with them culturally situated ideas of personhood. As they move through realms of journalism, medicine, film, and courts, they are important cultural lenses through which people interpret illness and identity. Therefore, the glowing blue brains take on elements of personhood and identity based on how brain images have been viewed across western mediascapes. 

Racine et al’s 2005  notion of ‘neurorealism’ is also useful here, where brain images can make mental phenomena appear more real by providing them a physical location. These interlinked narratives of personhood and the brain have been crystallised by Vidal and Ortega in their (2017) book ‘The Cerebral Subject’, arguing that increasingly there is a tendency for people to be visualised through their brains. In a sense, our physical health, our mental health, our ability, and even our relations are seen through this image of the brain; in other words, they argue we are increasingly being visualised as our brains, where the brain becomes a symbol of our agency, intelligence, identity and moral responsibility. 

In the context of AI imagery, the glowing blue brain borrows from what we can call ‘neurocultural authority’, appealing to ideas of personhood and intelligence, where the narrative moves beyond computation to potentially misleading tropes of consciousness. The use of the physical brain enables the viewer to visually locate the machine, giving it potential for cognition. While the glow lights the machine up, the brain form provides an important visual architecture for us to visualise this active cerebral process; here the explicit use of the brain form helps transform luminous computation into a potential digital mind. This elaborate multi-modal trope, hence, removes us from the harsh reality of labour and infrastructure, and instead posits an anthropomorphic myth of a computer that is alive.

Illustration of a surreal office scene with neon birds interacting with digital elements around three people near servers and file cabinets; one bird writes on a digital mesh, another carries a paper.
IceMing & Digit / Better Images of AI / CC BY 4.0

Ice Ming’s image challenges the representation of AI as a brain through a different visual metaphor: stochastic parrots. The ‘stochastic parrot’ is a metaphor for large language models (like ChatGPT) that generate text by statistically predicting the next word based on large datasets, rather than by understanding the meaning, truth or context of the user’s prompts – perhaps like a cognitive being. 

Don’t Look so blue.

The use of the colour blue may seem a matter of ‘fitting the aesthetic’, given that such imagery is commonplace in science fiction cinema. However, the colour choice is an atmospheric device to make the visuals appear clean. Blue further helps remove AI from its socio-material context of data centres, energy use, supply chains, and labour. Sørensen and Thellefsen (2024) show that the role of colour in the blue brain metaphor is to ground the visuals in legitimacy. Crucially, this is not to claim that the use of blue, or the effect of blue, is universal, with Jonauskaite et al (2020) demonstrating that colour emotion associations are shaped by language, geography and culture, and this use of blue is perhaps limited to contemporary Euroamerican stock image culture, which has become the face of AI. 

This culturally situated use of the blue glow belongs to a wider regime in which AI imaginaries have been dominated by particular sections of society. This is connected to what Cave and Dihal (2020) have called the ‘whiteness of AI’, where the future seems Western and sanitised. The image further extends the erasure of other cultural and material ways of imagining AI; in a way, other ways to develop and conceive of AI  have been crowded out by such deterministic narratives. One can further draw a parallel to anthropologist Alex Taylor’s (2019) work on the aesthetics of data centres, where imagery used to depict data centres has emphasised them as sterile and technical spaces, devoid of fallible human labour. In both cases, visual narrative conveniently  distracts the viewer from human labour, which is at the core of the supply chain.

Cooling pipes hug data servers, extracting water from a shared reservoir while people collect water from the same source, set against a background of eroded soil textures.
Gloria Mendoza / Better Images of AI / CC BY 4.0

Gloria’s image, while still including elements of blue, is not used to represent AI, but the resources it relies upon – including water, local communities, and servers. It symbolises how data centre operations contribute to erosion, water scarcity, and drought.

Conclusion

The blue, the glow and the brain form combine to create a culturally situated myth of machine cognition. The myth has many layers: where a brain may provide it with physical authority, glow may suggest activation, and blue may signal a sanitised future in the Global North. This, when combined  with circuits placed upon a dark digital background, removes AI from physical infrastructure and human labour to a luminous future. This is symptomatic of visual media describing AI systems, which is disengaged from the social and environmental effects of such systems, while also perpetrating a grossly misleading narrative about the capabilities of current large language models.

About the author

Raghu Krishnan is an undergraduate reading archaeology and anthropology at the University of Oxford, interested in digital anthropology and human-AI interaction. 

Press release: New playbook released to enable creation of images of AI using free and open licence digital heritage collections from around the world


  • Archival Images of AI project enables the creation of meaningful and compelling images of AI
  • New playbook includes 38 pages of guidance and sources of free to use archive images
  • Showcases methods and tips for remixing archive images which can be used by anyone 
  • Inspirational artists have created free-to-use examples of their own interpretations of AI 

LONDON / AMSTERDAM 4th December 2024: As AI continues to make headlines and evolve in ways that impact the general public, global critical AI research community AIxDESIGN has released a research-informed playbook for remixing free and open licence images to create better images of artificial intelligence. It uses techniques that anyone can apply without the use of AI image generators.

Producing accurate images of AI – whether this is technically accurate or suitable for any given narrative or situation, is not always easy without an illustrator or access to a wide variety of images that can be easily edited or remixed. AIxDESIGN, in partnership with Netherlands Institute for Sound & Vision with inspiration from Better Images of AI and support from We and AI have released a playbook as a guide to address this challenge by working with free images from consented archives around the world and artists immersed in expressing their experiences and understanding of the technology.

Archival Images of AI Playbook

The playbook includes vital information about the use of archive images as well as details about the creation and representation of artificial intelligence through visual narratives. The project builds on the principles outlined in Better Images of AI: A Guide for Users and Creators that explain why accuracy is important when it comes to communicating these technologies to the wider public. 

By making poor choices about how AI is visualised, communications from media to marketing often risk misinforming or misleading the public about how it works, what it means and the impact it can have. The playbook offers new ways to interpret images of AI by engaging with cultural archives to explore historical and social context. It also has sources of visual stimuli and motifs that can be used freely and with open licences by anyone seeking to illustrate their writing or communicate AI news and reflection. 

A highly creative and reflective selection of artists and researchers have contributed to the guide to offer tutorials and examples, including: 

Hanna Bakarat, researcher, activist and collage artist. She’s been deep in researching narratives of AI and exploring collage as an act of resistance. 

Cristóbal Ascencio, a Mexican visual artist. As a photographer, his practice explores new forms of image making such as virtual reality, data manipulation and photogrammetry. 

Zeina Saleem, graphic designer interested in data beautification and the aesthetics of algorithmic distortion. 

Dominika Čupková, interdisciplinary artist and researcher connecting the dots between AI, art, design and feminism.

Nadia Piet, Nadia is an independent researcher, designer, and co-founder and creative director of AIxDESIGN. 

The playbook is available for anyone to download and is accompanied by detailed artist logs available at https://aixdesign.co/posts/archival-images-of-ai. Readers can explore the works’ origins and development and input from Eryk Salvaggio, Cees Martens, Isabel Beirigo, Monique Groot, Danny van Zuijlen, Alice Isaac, Anne Fehres and Luke Conroy.

The playbook is launched at an interactive event where attendees have an opportunity to test and play with the techniques and interact with the artists. 

A varied and powerful selection of over 25 of the images created by the artists will be added to the free Better Images of AI image library where any individual or publication can use the images for free. 

The playbook can be downloaded at https://aixdesign.co/posts/archival-images-of-ai and https://thistle-oriole.pikapod.net/archival-images-of-ai-playbook/.

About Netherlands Sound & Vision

The Netherlands Institute for Sound & Vision is a knowledge institute in the field of media culture and audiovisual archiving. It specialises in cultural programming, educational offering and research that makes media heritage available, searchable and relevant. Learn more at https://www.beeldengeluid.nl/en. 

About AIxDESIGN 

​​​​​AIxDESIGN (AIxD) is a global community of designers, researchers, creative technologists, and activists using AI in pursuit of creativity, justice and joy and living lab exploring participatory, slow, and more-than-corporate AI. Learn more at aixdesign.co.

About Better Images of AI Better Images of AI is a global non-profit collaboration which curates and commissions stock images that avoid perpetuating unhelpful myths about artificial intelligence, downloadable for free. It provides guidelines and research and creates a space for imaging and creating more inclusive, transparent and realistic visual representations of AI themes and technologies, avoiding overused cliches and alienating, disempowering tropes. It was launched in 2021 with input from a global community of researchers, practitioners and institutions including BBC R&D and coordinated by We and AI.

Better images of AI can support AI literacy for more people

Marika Jonsson's book cover; a simple yellow cover with the title (in Swedish): "En bok om AI"

Marika Jonsson, doctoral student at KTH Royal Institute of Technology, reflects on overcoming the challenge of developing an Easy Read book on artificial intelligence (AI) with so few informative images about AI available.


There are many things that I take for granted. One of them is that I should be able to easily find information about things I want to know more about. Like artificial intelligence (AI). I find AI exciting, interesting; and I see the possibilities of AI helping me in everyday life. And thanks to the fact that I have been able to read about AI, I have also realised that AI can be used for bad things; that AI creates risks and can promote inequality in society.  Most of us use or are exposed to AI daily, sometimes without being aware of it.

Between May 2020 and June 2023, I participated in a project called AllAgeHub in Sweden, where one of the aims was to spread knowledge about how to use welfare technology to empower people in their everyday lives. The project included a course on AI for the participants, who worked in the public healthcare and social care sectors. The participants then wanted to spread knowledge about AI to clients in their respective sectors. The clients could be, for example, people working in adapted workplaces or living in supported housing. There was a demand for information in Easy Read format. Easy Read format is when you write in easy-to-read language, with common words, short sentences and in simple chronological order. The text should be spaced out and have short lines, and the texts are often supported by images. Easy Read is both about how you write and about how you present what is written. The only problem was that I found almost no Easy Read information about AI in Swedish. My view is that the lack of Easy Read information about AI is a serious matter.

A basic principle behind democracy is that all people are equal and should have the same rights. Therefore, I believe we must have access to information in an understandable way. How else can you express your opinion, vote or consent to something in an informed way? That was the reason I decided to write an Easy Read book about AI. My ambition was to write concretely and support the text with pictures. Then I stumbled on the huge problem of finding informative pictures about AI. The images I found were often abstract or inaccurate. The images could also be depicting AI as robots and conveyed the impression that AI is a creature that can take over the earth and destroy humanity. With images like that, it was hard to explain that, for example, personalised ads, which can entice me to buy things I don’t really need, are based on AI technology. Many people don’t know that we are exposed to AI that affects us in everyday life through cookie choices on the internet. The aforementioned images might also make people afraid of using practical AI tools that can make everyday life easier, such as natural language processing (NLP) tools that convert speech to text or reads text aloud. So, I had to create my own pictures.

I must confess, it was difficult to create clear images that explain AI. I chose to create images that show situations where AI is used, and tried to visualise how certain kinds of AI might operate. One example is that I visualised why a chatbot might give the wrong answer by showing how a word can mean two different things with a picture of each word’s meaning. The two different meanings give the AI tool two possible interpretations about what issue is at hand. The images are by no means perfect, but they are an attempt at explaining some aspects of AI.

Two images with Swedish text explaining the images. 1. A box of raspberries. 2. symbol of person carriying a bag. The Swedish word ”bär” is present in both explanations.
The word for carry and berry is the same in Swedish. The text says: “The word berry can mean two things. Berries that you eat. A person carrying a bag.”

The work of creating concrete, comprehensible images that support our understanding of AI can strengthen democracy by giving more people the opportunity to understand information about the tools they use in their day-to-day lives. I hope more people will be inspired to write about AI in Easy Read, and create and share clear and descriptive images of AI.

As they say,  ”a picture is worth a thousand words,” so we need to choose images that tell the same story as the words we use. At the time I write this blog post, I feel there are very few images to choose from. I am hopeful we can change this, together!


The Easy Read book about AI includes a study guide. It is in Swedish, and is available for free as a pdf on AllAgeHub’s website:

https://allagehub.se/2023/06/29/nu-finns-en-lattlast-bok-om-ai-att-ta-del-av/

Three new Better Images of AI research workshops announced

LCFI Research Project l FINAL WORKSHOPS ANNOUNCED! Calling all journalists, AI practitioners, communicators and creatives! (Event poster in Better Images of AI blue and purple colours, with logos)

Three new workshops have been announced in September and October by the Better Images of AI project team. We will once again bring a range of AI practitioners and communicators together with artists and designers working in different creative fields,  to explore in small groups how to represent artificial intelligence technologies and impacts in more helpful ways.

Following a first insightful initial workshop in July, we’re inviting anyone in relevant fields to apply to join the remaining workshops,- taking place both online and in person. We are particularly interested in hearing from journalists who write about AI. However if you are interested in critiquing and exploring new images in an attempt to find more inclusive, varied and realistic visual representations of AI, we would like to hear from you!

Our next workshops will be held on:

  • Monday 12 September, 3.30 – 5.30pm UTC+1 – ONLINE
  • Wednesday 28 September, 3 – 5pm UTC+1 – ONLINE
  • Thursday 6 October, 2:30 – 4:30pm UTC+1 – IN PERSON – The Alan Turing Institute, British Library 96 Euston Road London NW1 2DB

If you would like to attend or know anyone in these fields, email research@betterimagesofai.org, specifying which date. Please include some information about your current field and ideally a link to an online profile or portfolio.

The workshops will look at approaches to meet the criteria of being a ‘better image of AI’, identified by stakeholders at earlier roundtable sessions. 

The discussions in all four workshops will inform an Arts and Humanities Research Council-funded research project undertaken by the Leverhulme Centre for the Future of Intelligence, the University of Cambridge and organised by We and AI. 

Our first workshop was held on 25 July, and brought together over 20 individuals from creative arts, communications, technology and academia to discuss sets of curated and created images of AI and to explore the next steps in meeting the needs identified in providing better images of AI moving forward. 

The four workshops follow a series of roundtable discussions, which set out to examine and identify user requirements for helpfully communicating visual narratives, metaphors, information and stories related to AI. 

The first workshop was incredibly rich in terms of generating creative ideas and giving feedback on gaps in current imagery. Not only has it surfaced lots of new concepts for the wider Better Images of AI to work on, but the series of workshops will also form part of a research paper to be published in January 2023. This process is really critical to ensuring that our mission to communicate AI in more inclusive, realistic and transparent ways is informed by a variety of stakeholders and underpinned by good evidence.

Dagmar Monett, Head of the Computer Science Department at Berlin School of Economics and Law and one of the July workshop attendees, said: “”Better Images of AI also means better AI: coming forward in AI as a field also means creating and using narratives that don’t distort its goals nor obscure what is possible from its actual capacities. Better Images of AI is an excellent example of how to do it the right way.”

The academic research project is being led by Dr Kanta Dihal, who has published many related books, journal articles and papers related to emerging technology narratives and public perceptions.

The workshops will ultimately contribute to research-informed design brief guidance, which will then be made freely available to anyone commissioning or selecting images to accompany communications – such as news articles, press releases, web communications, and research papers related to AI technologies and their impacts. 

They will also be used to identify and commission new stock images for the Better Images of AI free library.

To register interest: Email our team at research@betterimagesofai.org, letting us know which date you’d like to attend and giving us some information about your current field as well as a link to your LinkedIn profile or similar.