The initiative, Doing AI Differently, is led by The Alan Turing Institute, the University of Edinburgh and the UK’ s Arts & Humanities Research Council( AHRC- UKRI) in partnership with Lloyd’ s Register Foundation. Its newly published whitepaper outlines how humanities expertise can play a central role in shaping AI’ s future.

The paper argues that the outputs of today’ s AI systems – text, images and other media – resemble cultural artefacts more than mathematical equations or data tables. As such, their interpretation requires insights from the humanities to both understand their implications and design systems that reflect cultural nuance, context and multiple perspectives. sensitive domains – such as healthcare, climate action and democratic discourse – where cultural context and interpretive judgement are essential. Yet there is a fundamental gap. We need systems that can better engage with and represent the richness and diversity of human meaning. The last few years have made it clear that AI can be a formidable tool to solve modernday challenges. But these systems often fail when nuance and context matter most.”

The whitepaper outlines three core innovations needed to achieve this:

• Interpretive technologies – AI systems designed from the outset to handle ambiguity, context and plurality.

• Expanded AI architectures – models that move beyond today’ s narrow design approaches to embrace richer interpretive capacities.

• Human-AI ensembles – collaborations where AI augments human capabilities instead of replacing them.

DECISIONS BEING MADE TODAY ABOUT AI ARCHITECTURE WILL SHAPE THE SYSTEMS WE LIVE WITH FOR YEARS TO COME.

Professor Hemment added:“ We’ re at a pivotal moment for AI. Decisions being made today about AI architecture will shape the systems we live with for years to come. We have a narrowing window to build in interpretive capabilities from the ground up. This is our opportunity to shape a new generation of AI – one that amplifies rather than erodes human potential.” x

Drawing lessons from the early rollout of social media platforms, which were launched with minimal safeguards and measured against simplistic engagement metrics, the researchers warn of similar pitfalls if AI is deployed without cultural and contextual depth. They stress that as AI moves into sensitive domains such as healthcare, climate change mitigation and democratic discourse, it must be equipped to work with ambiguity and diversity of meaning.

Professor Drew Hemment, Theme Lead for Interpretive Technologies for Sustainability at The Alan Turing Institute, said:“ AI systems are increasingly operating in

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