Artist contributions to the Better Images of AI library have always served a really important role in relation to fostering understanding and critical thinking about AI technologies and their context. Images facilitate deeper inquiries into the nature of AI, its history, and ethical, social, political and legal implications.
When artists create better images of AI, they often have to grapple with these narratives in their attempts to more realistically portray the technology and point towards its strengths and weaknesses. Furthermore, as artists freely share these images in our library, others can benefit from learning about the artist’s own internal motivations (which are provided in the descriptions) but the images can also inspire users’ own musings.
In this series of blog posts, some of our volunteer stewards are each taking turns to choose an image from the library and unpack the artist’s processes and explore what that image means to them.
Here, Joe Bourne explores Data Flock (digits) by Philipp Schmitt and reflects on how the image invites us to think about the subtleties in the relationships between AI, data, and humans. He draws attention to the image’s ambiguity that represents the complexity of data without trying to gloss over its nuances which can mislead us or prevent us from making our own judgments about information.
Philipp Schmitt / Better Images of AI / CC-BY 4.0
From Posters on Bedroom Walls to Da Vinci’s Notebooks
I assumed choosing my favourite image from the Better Images of AI collection would be a personal thing. What I didn’t expect was to find myself having to do some intense googling to track down a half-remembered exhibition poster from my teenage bedroom wall.
The image that sparked this trip down memory lane is Data Flock (digits) by Philipp Schmitt. Data Flock (digits) shows a machine learning dataset visualized spatially, in cloud-like clusters according to visual similarity of the data. Although visualizations like this one always simplify and fail to represent the data’s true complexity and nuance, they guide the researchers’ intuitions for their subject matter. The image is a ‘laptopogram’, created by exposing photographic paper using a computer screen and developed in the artist’s bathtub. The process preserves a digital artifact of AI research in silver crystals, returning a physical dimension to sterile data. Dust, scratches, and the marks left by the artist’s hands draw a connection to the role of the researchers’ subjectivity in making AI.
At first glance, it reminded me of the speculative models and scribblings on the poster for Panamarenko’s Bing of the Ferro Lusto 2000 exhibition from my teenage bedroom wall. Schmitt’s image has a similar hand-crafted and open-ended feel. Panamarenko’s sketches looked like fantastical vehicles or improbable machines, while Data flock (digits) evokes something more abstract and organic. To me, the blobs look like tiny grubs, or bacteria, maybe even buffalo from a great height. Others might see beans, or droplets, or brush marks. There’s no single right answer, and that’s part of what makes it compelling.
It also calls to mind da Vinci’s famous notebooks with flying machines and the vitruvian man: the yellowed backgrounds, the visible drafting marks and something simultaneously analytical and artistic. Like those sketches, Schmitt’s image sits at the intersection of science, art and science fiction: not to explain, but to explore. The data is clustered, sorted, and shaped, but the meaning remains open. This is what I find so captivating: that Data Flock (digits) captures the process of pattern recognition without forcing a conclusion. It’s a good reminder that even when AI or data analysis can spot patterns, we’re still the ones making sense of them. Or trying to, at least.
AI Metaphors and Meaning
There’s also something quietly organic in the image’s visual texture. To me, the ‘flocking’ resembles weather maps or wind currents: pressure systems moving across the frame. In my own research, I’ve written about the metaphors we reach for when trying to explain data-driven technologies. “The cloud” is one example: a term that implies something weightless and remote, when in fact it refers to very grounded, physical infrastructures. The language we use to describe AI is full of euphemism, metaphor and anthropomorphism, and while those can help us relate to the intangible and complex parts, systems and concepts behind data, AI and the internet, they also risk misleading us. Data flock (digits) plays with this tension: hinting at anthropomorphic movement, without giving in completely to any recognisable metaphor or cliche. The blobs in this data flock feel simultaneously natural and digital.
Something else that draws me to this image is how it reveals something of the process behind machine learning. The blobs are grouped according to visual similarity, but there’s no legend or key. You’re left to observe, to notice, to wonder. It’s an aesthetic representation of categorisation (one of the fundamental operations in data science) but without the usual gloss of objectivity or neatness. It invites ambiguity and curiosity. It shows us the work of sorting and learning. Schmitt’s own description of the image, that “visualizations like this one always simplify and fail to represent the data’s true complexity and nuance, [but] they guide the researchers’ intuitions”, gets to the heart of why I admire it. I’m always drawn to attempts to make AI or machine learning more tangible. Especially when they don’t try to smooth over the complexity. The best ones let you see the mess, the uncertainty, the weird edges that don’t quite line up. That’s where it gets interesting. This image does that. It reminds us that there is always a human: whether analysing data, interpreting visualisations, or deciding how best to communicate them. Even when making the image itself, captured by the marks, scratches and fingerprints.
Art for Art’s Sake
As well as sending me down memory lane, remembering having my mind expanded in the Hayward Gallery twenty-plus years ago, the image also led me down a wonderfully unexpected rabbit hole. I’d never heard of a laptopogram before reading Schmitt’s accompanying interpretation for this image. This discovery speaks to something that makes Better Images of AI so valuable. While its stated purpose is to improve the visuals used to represent AI in public life, it also functions as an art exhibition in its own right: Art for art’s sake. Through this project I’ve been introduced to all kinds of image-making techniques I didn’t know about before: digital collaging, archival remixing, glitch aesthetics. As someone who enjoys low-fi making and physical processes, I was delighted to learn that data flock (digits) was created by exposing photographic paper to a computer screen and developing it in a bathtub. You can see that process in the final image: in the specks, scratches, and smudges. It’s a tactile, analogue production that sits in refreshing contrast to the smooth, polished surfaces of AI-generated imagery.
The Value of Ambiguity
Finally, there’s a practical reason I keep returning to this image: it’s incredibly useful. Because it’s not tied to a specific AI use case, and because its aesthetic is so open-ended, I’ve found myself using it in presentations, slides, and publications across a range of contexts. It doesn’t tell the viewer what to think, but it allows them space to think. For a project like Better Images of AI, which aims to shift how these technologies are represented, that matters. Likelihood of adoption should be part of how we evaluate what makes an image “better.”
Data flock (digits) is a reminder that images don’t need to explain everything. Sometimes, they’re more powerful when they simply invite us to pay attention: to complexity, to process, and to the humans behind the scenes.
About the author
Joe Bourne (he/him) is doing a PhD in Speculative Design and Emerging Technologies at Imagination Lancaster, and he is a Partnership Development Lead at the Alan Turing Institute. Joe is particularly interested in public understanding and imaginings of emerging technology, and people’s hopes and fears associated to this.
If you want to contribute to our new blog series, ‘Through My Eyes’, by selecting an image from the Better Images of AI Library and exploring what the image means to you, get in touch (info@betterimagesofai.org).