Hanna Barakat’s image collection & the paradoxes of depicting diversity in AI history

A black-and-white image depicting the early computer, Bombe Machine, during World War II. In the foreground, the shadow of a woman in vintage clothing is cast on a man changing the machine's cable.

As part of a collaboration between Better Images of AI and Cambridge University’s Diversity Fund, Hanna Barakat was commissioned to create a digital collage series to depict diverse images about the learning and education of AI at Cambridge. Hanna’s series of images complement our competition that we opened up to the public at the end of last year which invited submissions for better images of AI from the wider community –  you can see the winning entries here.

In the blog post below, Hanna Barakat talks about her artistic process and reflections upon contributing to this collection. Hanna provides her thoughts on the challenges of creating images that communicate about AI histories and the inherent contradictions that arise when engaging in this work.

The purpose behind the collection

As outlined by the Better Images of AI project, normative depictions of AI continue to perpetuate negative gender and racial stereotypes about the creators, users, and beneficiaries of AI. Moreover, they misdirect attention from the harms implicit in the real-life applications of the technology. The lack of diversity—and the problematic interpretation of diversity—in AI-generated images is not merely an ‘output’ issue that can be easily fixed. Instead, it stems from deep-rooted systemic issues that reflect a long history of bias in data science.

As a result, even so-called ‘diverse’ images created by AI often end up reinforcing these harms [Fig.1]. The image below has adopted token diversity tropes like a wheelchair, different skin tones and a mix of genders – superficially appearing diverse without addressing deeper issues like context, intersectionality, and the inclusion of underrepresented groups in leadership roles. The teacher remains to be an older, able-bodied white male and the students all appear to be conventionally attractive, similarly sized individuals wearing almost matching types of clothing. The image also shows a fictional blue holographic image of a robot in the centre – misrepresenting what generative AI is and exaggerating the capabilities of the technology.

Figure 1. Image depicting an educational course on Generative AI.

As academic institutions like the Leverhulme Centre for the Future of Intelligence are exploring “vital questions about the risks and opportunities emerging with AI,” they commissioned images that reflect a more nuanced depiction of the risks and opportunities. Specifically, they requested seven images that represent the diversity in Cambridge’s teaching about AI, with the intention to use these images for courses, websites, and events programs.

Hanna’s artistic process

My process takes a holistic approach to “diversity” – aiming to avoid the “DEI-washing” images that reduce diversity to a gradient of brown bodies or tokenization of marginalized groups in the name of “inclusion” but often fail to acknowledge the positionality of the institutions utilizing such images.

Instead, my approach interrogates the development of AI technology, its history of computing in the UK, and the positionality of elite institutions such as Cambridge University to create thoughtful images about the education of AI at Cambridge.

Analog Lecture on Computing by Hanna Barakat & Cambridge Diversity Fund and Pas(t)imes in the Computer Lab by Hanna Barakat & Cambridge Diversity Fund

Through digital collages of open-source archival images, this series offers a critical visual depiction of education about AI. Collage is a way of moving against the archival grain– reinserting, for example, the overlooked women who ran cryptanalysis of the Enigma Machine at Bletchley Park to surrealist depictions of a historically contextualized lecture about AI. By combining mixed media layers, my artistic process seeks to weave together historical narratives and investigate the voices systemically overlooked and/or left out. 

I carefully navigated the archive and relied on visual motifs of hands, strings, shadows, and data points. Throughout the series, these elements engage with the histories of UK computing as a starting point to expose the broader sociotechnical nature of AI. The use of anonymous hands becomes a way of encouraging reflection upon the human labor that underpins all machines. The use of shadows symbolizes the unacknowledged labor of marginalized communities throughout the Global Majority.

Turning Threads of Cognition by Hanna Barakat & Cambridge Diversity Fund

It is these communities upon which technological “process” has relied upon and at whose expense “progress” has been achieved. I use an abstract interpretation of data points to symbolize the exchange of information and learning on university campuses. I was inspired by Ada Lovelace, Cavendish Labs archive (physics laboratories), which depicts photos of early histories of computing, the stories of Cambridge Language Research Unit (CLRU) run by Margaret Masterman, Jean Valentine, and the many other Cambridge-educated women at Bletchley Park that made Alan Turing’s achievements possible.

Lovelace GPU by Hanna Barakat & Cambridge Diversity Fund

The challenges of creating images relating to the diverse history of AI

Nonetheless, I remain cautious about imbuing these images with too much subversive power. Like any nuanced undertaking, this project grapples with tension, including navigating the challenge of representing diverse bodies without tokenizing them; drawing from archival material while recognizing the imperialist incentives that shape their creation; portraying education about AI in ways that are both literal and critically reflective, particularly in contexts where racial and ethnic diversity (in the histories of UK) are not necessarily commonplace; and balancing a respect for the critical efforts of the CFI with an awareness of its positionality as an elite institution. On a practical level, I encountered challenges in accessing the limited number of images available, as many were not fully licensed for open access.

I list these tensions not to imply as a means of demonstrating hypocrisy, but, quite the opposite—to illuminate the complexities and inherent contradictions that arise when engaging in this work. By highlighting these points of friction, I am able to acknowledge the layered positionality that shapes both the process and the outcomes, emphasizing that such tensions are not obstacles to be avoided but rather essential facets of critically engaged practice.

If you want to read more about the processes behind Hanna’s work, view her Artist Log on the AIxDESIGN site. You can also learn how to make your own archival images of AI by exploring our Playbook that we released at the end of 2024 with AIxDESIGN and the Netherlands Sound and Vision Institute.

Dr Aisha Sobey was behind the project which was commissioned with funding from Cambridge Diversity Fund

This project grew from the desire of CFI and multiple collaborations with Better Images of AI to have better images of AI in relation to the teaching and learning we do at the Centre, and from my research into the ‘lookism’ of generative AI image models. I knew that asking for the combination of criteria to show anonymous, diverse people in images of AI learning would be tricky, but even as the project evolved to take a historical lens to reclaim lost histories, this proved to be a really difficult task for the artists.

The images created by Hanna and the entries to the prize competition showed some brilliant and unique takes on the prompt. Still, they often struggled to bring diverse people and Cambridge together. It points to the barriers of showing difference in an ethical way that doesn’t tokenise or exploit already marginalised groups and we didn’t solve that challenge in these images, and the need for more diverse people in places like Cambridge to make these stories. However, I am hopeful that the process has been valuable to illuminate different challenges of doing this kind of work and further that the images offer alternative and exciting perspectives to the representation of diversity in learning and teaching AI at the University.”

Artist Subjectivity Statement

In creating these images which seek to depict diversity, it is imperative to address the “experience of the knower.” Thus, consistent with a critical feminist framework, I feel it is important to share my identity and positionality as it undoubtedly shapes my artistic practice and influences my approach to digital technologies.

My name is Hanna Barakat. I am a 25-year-old science & technology studies researcher and collage artist.  I am a female-identifying Palestinian-American. While I was raised in Los Angeles, California, I am from Anabta, Palestine. Growing up in the Palestinian diaspora, my experience is informed by layers of systemic violence that traverse the digital-physical “divide.” I received my education from Brown University, a reputable university in the United States.

Brown University’s founders and benefactors participated in and benefited from the transatlantic slave trade. Brown University is built on the stolen lands of the Narragansett, Wôpanâak, and Pokanoket communities. In this light, I materially benefit from, and to some degree am harmed by, my location within systems of settler colonialism, whiteness, racial capitalism, Islamophobia, heteropatriarchy, and education inequality. My identity, lived experiences, and fraught relationship with technology inform my approach to artist practice–which uses visual language as a tool to (1) critically challenge normative narratives about technology development and (2) imagine cultural contextualized and localized digital futures. 

Winners of public competition with Cambridge Diversity Fund announced

An image with the text 'Winners Announced!" at the top in maroon. Below it in slightly lighter purple text it states: 'Reihaneh Golpayegani for Women and AI' and 'Janet Turra for Ground Up and Spat Out'. Their two images are positioned on the image at a slant each in opposite directions. At the bottom, there is a maroon banner with the text 'University Diversity Fund' in white, the CFI logo in white, and the Better Images of AI logo.

At the end of 2024, we launched a public competition with Cambridge Diversity Fund calling for images that reclaimed and recentred the history of diversity in AI education at the University of Cambridge.

We were so grateful to receive such a diverse range of submissions that provided rich interpretations of the brief and focused on really interesting elements of AI history.

Dr Aisha Sobey set and judged the challenge, which was enabled by funding from Cambridge Diversity Fund. Entries were judged on meeting the brief, the forms of representation reflected in the image, appropriateness, relevance, uniqueness, and visual appeal.

We are delighted to announce the winners and their winning entries:

First Place Prize

Awarded to Reihaneh Golpayegani for ‘Women and AI’

The left side incorporates a digital interface, showing code snippets, search queries, and comments referencing Woolf’s ideas, including discussions about Shakespeare’s fictional sister, Judith. The overlay of coding elements highlights modern interpretations of Woolf’s work through the lens of data and AI.

The center depicts a dimly lit, minimalist room with a window, dessk, and wooden floors and cupboards. The right side features a collage of Cambridge landmarks, historical photographs of women, and a black and white figure in Edwardian attire. There is a map of Cambridge in the background, which is overlayed with images of old fountain pens and ink, books, and a handwritten letter.

This image is inspired by Virginia Woolf’s A Room of One’s Own. According to this essay, which is based on her lectures at Newnham College and Girton College, Cambridge University, two things are essential for a woman to write fiction: money and a room of her own. This image adds a new layer to this concept by bringing it into the Al era.

Just as Woolf explored the meaning of “women and fiction”, defining “women and AI” is quite complex. It could refer to algorithms’ responses to inquiries involving women, the influence of trending comments on machine stereotypes, or the share of women in big tech. The list can go on and involve many different experiences of women with AI as developers, users, investors, and beyond. With all its complexity, Woolf’s ideas offer us insight: Allocating financial resources and providing safe spaces-in reality and online- is necessary for women to have positive interactions with AI and to be well-represented in this field.

Download ‘Women and AI’ from the Better Images of AI library here

About the artist:

Reihaneh Golpayegani is a law graduate and digital art enthusiast. Reihaneh is interested in exploring the intersection of law, art, and technology by creating expressive artworks and pursuing my master’s studies in this area.

Commendation Prize

Awarded to Janet Turra for ‘Ground Up and Spat Out’

The outputs of Large Language Models do seem uncanny often leading people to compare the abilities of these systems to thinking, dreaming or hallucinating. This image is intended to be a tongue-in-cheek dig, suggesting that AI is at its core, just a simple information ‘meat grinder,’ feeding off the words, ideas and images on the internet, chopping them up and spitting them back out. The collage also makes the point that when we train these models on our biased, inequitable world the responses we get cannot possibly differ from the biased and inequitable world that made them.

Download ‘Ground up and Spat Out’ from the Better Images of AI library here.

About the artist:

Janet Turra is a photographer, ceramicist and mixed media artist based in East Cork, Ireland. Her fine arts career spans over 25 years, a career which has taken many turns in rhythm with the changing phases of her life. Continually challenging the concept of perception, however, her art has taken on many themes including self, identity, motherhood and more recently our perception of AI and how it relates to the female body. 

Background to the competition

Cambridge and LCFI researchers have played key roles in identifying how current stock images of AI can perpetuate negative gender and racial stereotypes about the creators, users, and beneficiaries of AI.

The winning entries will be used for outward-facing posting on social media, University of Cambridge websites, internal communications on student sites and Virtual Learning Environments. They will also be made available for wider Cambridge programs to use for their teaching and events materials. They are also both available in the Better Images of AI library here and here for anyone to freely download and use under a Creative Commons License.

“This project grew from the desire of CFI and multiple collaborations with Better Images of AI to have better images of AI in relation to the teaching and learning we do at the Centre, and from my research into the ‘lookism’ of generative AI image models. I am hopeful that the process has been valuable to illuminate different challenges of doing this kind of work and further that the images offer alternative and exciting perspectives to the representation of diversity in learning and teaching AI at the University.” – Aisha Sobey, University of Cambridge (Postdoctoral Researcher)

An additional collection of images from Hanna

As part of this project, collage artist and scholar, Hanna Barakat, was commissioned to design a collection of images which draw upon her work researching AI narratives and marginalised communities to uncover and reclaim diverse histories. You can find the collection in the Better Images of AI library and we’ll also be releasing an additional blog post which focuses on Hanna’s collection as well as the challenges/reflections on this competition brief.