Doing AI Differently launches a push for human-centered AI development.
Researchers from The Alan Turing Institute, University of Edinburgh, AHRC-UKRI, and Lloyd’s Register Foundation want a fresh take on how AI is built.
Their new initiative says AI outputs aren’t just math answers—they’re cultural artifacts. Right now, AI doesn’t really get context or nuance. It’s like a dictionary memorizer with no idea how to talk. 
The team calls out the “homogenisation problem”: most AI tech runs on nearly identical designs. That makes AI tools everywhere share the same blind spots and biases. Like identical cakes baked by every baker using the same recipe.
They warn this could lead to more issues like social media’s unintended consequences. The team’s mission: build AI that thinks more like people. That handles ambiguity, multiple viewpoints, and deep context.
Their vision is “Interpretive AI.” This new breed of AI offers multiple perspectives, not single rigid answers. It explores alternative designs to break current AI molds. The goal is human-AI teams boosting creativity and problem-solving.
Real-world use cases include healthcare and climate action. For example, interpretive AI could capture the full story of a patient’s experience or tailor climate solutions for specific communities.
An international funders call is launching to bring UK and Canadian researchers together on this. But time is tight.
Professor Drew Hemment from The Alan Turing Institute said:
“We’re at a pivotal moment for AI.”
“We have a narrowing window to build in interpretive capabilities from the ground up”.
Lloyd’s Register Foundation wants AI systems to be safe and reliable. Their Director of Technologies Jan Przydatek stated:
“As a global safety charity, our priority is to ensure future AI systems, whatever shape they take, are deployed in a safe and reliable manner.”
This project aims to help AI solve big challenges while amplifying humanity’s best parts.
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