Doing AI Differently: A Human-Centered Vision for the Future

A coalition of leading researchers is reimagining the future of artificial intelligence with a bold new initiative called “Doing AI Differently”—and their message is clear: the next generation of AI must be built around people, not just math.

The project, driven by experts from The Alan Turing Institute, the University of Edinburgh, AHRC-UKRI, and the Lloyd’s Register Foundation, challenges the prevailing view of AI as a purely computational tool. Instead, they argue, AI’s outputs are closer to cultural artifacts—more like novels, films, or paintings than spreadsheets.

Why Current AI Falls Short

Today’s AI systems generate content without truly understanding it, much like someone who memorizes a dictionary but can’t hold a meaningful conversation. This lack of “interpretive depth,” says Professor Drew Hemment of The Alan Turing Institute, is why AI often stumbles when nuance and context matter most.

Worse still, the majority of AI tools are built from just a handful of similar architectures—a phenomenon the team calls “the homogenisation problem.” If every baker used the same recipe, the world would be full of identical, uninspired cakes. In AI, that means the same blind spots, biases, and design flaws are replicated across thousands of applications.

We’ve already seen the consequences of uniform tech design in social media—platforms launched with simple goals but later plagued by complex societal impacts. The team warns that unless we act now, AI could follow the same path.

Enter Interpretive AI

The group’s solution is Interpretive AI—a fundamentally new approach to AI design that embraces ambiguity, multiple perspectives, and context from the very start. Rather than aiming for one “correct” answer, these systems would present multiple valid viewpoints, enabling richer, more human-like understanding.

This shift would require breaking away from current AI blueprints and experimenting with entirely new architectures. The goal isn’t to replace humans but to create human–AI partnerships—ensembles that combine human creativity with AI’s computational strengths to tackle the world’s toughest challenges.

Real-World Impact

The vision has tangible, transformative potential:

• Healthcare: Instead of reducing a medical consultation to a list of symptoms, Interpretive AI could capture the patient’s full story, leading to better diagnoses and stronger trust between patients and providers.

• Climate Action: By translating global climate data into solutions that fit local cultural and political realities, Interpretive AI could create actionable plans that truly work on the ground.

Global Collaboration and Urgency

To accelerate progress, a new international funding call will unite researchers from the UK and Canada in building these next-generation systems. But time is short.

“We’re at a pivotal moment for AI,” warns Professor Hemment. “We have a narrowing window to build in interpretive capabilities from the ground up.”

For partners like the Lloyd’s Register Foundation, the mission aligns closely with their core values.

“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,” says Jan Przydatek, the foundation’s Director of Technologies.

Beyond Technology—Towards Humanity

Ultimately, Doing AI Differently is about more than better algorithms. It’s about building AI that amplifies our best human qualities—creativity, empathy, and wisdom—while helping to solve the complex problems that define our era.

If the team’s vision succeeds, the AI of the future won’t just calculate—it will understand.