Artificial Intelligence is rapidly reshaping public services. From predictive analytics in healthcare to automation in local government, the potential for AI to improve lives is enormous. But the real question isn’t just what AI can do, it’s how we build and use it responsibly, inclusively, and effectively.
One answer lies the simple yet powerful mindset of collaborating out loud.
Moving Beyond Closed Innovation
Too often, innovation in public services happens behind closed doors. Teams work in silos, solutions are developed in isolation, and lessons learned are lost between organisations.
AI amplifies both the risks and rewards of this approach. When done poorly, it can reinforce bias, erode trust, and miss the needs of the communities it aims to serve. But when done well and openly it can accelerate learning, improve transparency, and deliver meaningful social impact at scale.
Collaborating out loud offers a practical framework for “doing AI differently”.
Work Out Loud and Amplify
AI projects shouldn’t be hidden until they’re “perfect”. By sharing progress openly, successes, failures, ethical dilemmas, public service teams can accelerate collective learning.
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- Share prototypes early
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- Publish insights and challenges
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- Acknowledge contributors and inspiration
This not only builds momentum but fosters trust. When citizens and peers can see how decisions are made, confidence in AI systems grows.
Build Communities, Not Just Systems
AI is not just a technical challenge; it’s a human one.
Creating space for collaboration across departments, sectors, and communities ensures that solutions are shaped by diverse voices. Public services must intentionally nurture trust, empathy, and shared purpose.
This could look like:
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- Cross-sector design sessions
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- Open forums with citizens
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- Communities of practice around ethical AI
The stronger the community, the more resilient and inclusive the outcomes.
Embrace Difference and Collective Intelligence
The best AI systems are informed by a wide range of perspectives.
Collaborating out loud encourages us to seek out difference across disciplines, lived experience, and geography and draw on the “wisdom of the crowd”.
For public services, this means:
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- Co-designing with users, not for them
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- Including underrepresented voices
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- Making decisions transparently and, where possible, democratically
AI should not be imposed; it should be co-created.
Lead with Generosity and Kindness
In a fast-moving field like AI, it can be tempting to compete rather than collaborate. But public value is maximised when organisations share what they’ve learned.
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- Open-source tools and models
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- Share data responsibly where possible
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- Document lessons learned
Generosity creates a virtuous cycle: the more we give, the more collective capacity we build. And kindness often overlooked is essential in creating safe environments where people feel able to contribute.
Make It Real: Test, Learn, and Adapt
AI for social good doesn’t happen in theory. It happens in practice.
Collaborating out loud encourages us to work in the spaces “between” where formal systems meet informal experimentation.
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- Pilot ideas quickly
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- Learn in the open
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- Scale what works, share what doesn’t
This iterative, social approach helps avoid costly mistakes and ensures solutions are grounded in reality.
Why This Matters Now
Public trust in AI is fragile. At the same time, the demand for better, faster, and fairer public services has never been higher.
Collaborating out loud helps bridge this gap:
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- It builds transparency
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- It fosters accountability
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- It enables collective problem-solving
Most importantly, it keeps people not technology at the centre.
A Call to Action
If we want AI to truly serve the public good, we need to rethink how we work. We need to:
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- Share more openly
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- Collaborate beyond organisational boundaries
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- Include diverse voices
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- Learn together in public
AI is not just a tool, it’s a shared endeavour. Let’s build it out loud.
