'Pretty revolutionary': a Brooklyn exhibit interrogates white-dominated AI to make it more inclusive

https://www.theguardian.com/artanddesign/2025/jul/23/stephanie-dinkins-ai-race-black-white-technology

‘Pretty revolutionary’: a Brooklyn exhibit interrogates white-dominated AI to make it more inclusive

Stephanie Dinkins challenges the racialized AI space by highlighting Black ethos and cultural cornerstones

Melissa Hellmann
Wed 23 Jul 2025 07.00 EDT

At the Plaza at 300 Ashland Place in downtown Brooklyn, patrons mill around a large yellow shipping container with black triangles painted on its side. A nod to the flying geese quilt pattern, which may have served as a coded message for enslaved people escaping to freedom along the Underground Railroad, the design and container serve as a bridge between the past and the future of the African diaspora. At the center of the art project by the Brooklyn-based transmedia artist Stephanie Dinkins, a large screen displays artificial intelligence (AI) generated images that showcase the diversity of the city.

Commissioned by the New York-based art non-profit More Art and designed in collaboration with the architects LOT-EK, the AI laboratory If We Don’t, Who Will? will be on display until 28 September. It seeks to challenge a white-dominated generative-AI space by highlighting Black ethos and cultural cornerstones.

During a time when society has become increasingly reliant on AI, Dinkins wants the models to learn the history, hopes and dreams of Black and brown people to more accurately represent US demographics. She sees her work as shifting the AI landscape, which has been trained on biased data and encapsulates a worldview that is not reflective of the global majority. Black people are underrepresented in the AI field, with Black workers composing just 7.4% of the hi-tech workforce. Research has shown that lack of representation in AI can lead to discriminatory outcomes, such as predictive policing tools that target Black communities and tenant screening programs that reject renters of color.

“What stories can we tell machines that will help them know us better from the inside of the community out, instead of the way that we’re often described, from outside in, which is often incorrect or misses a mark in some way, or knows us as a consumerist body, not as a human body,” Dinkins said. “I have this question: ‘Can we make systems of care and generosity?’”

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