Building Public Trust: A Conversation with CCF Distinguished Fellow Afua Bruce

A Career Built at the Intersection of Tech and Public Good

Afua Bruce joins Center for Civic Futures (CCF) as a Distinguished Fellow after more than a decade working at the intersection of technology, policy, and society. An engineer by training, she began her career as a software engineer at IBM before moving into government, where she held senior roles at the FBI and the White House Office of Science and Technology Policy. 

She later led engineering for the Public Interest Technology program at New America and served as Chief Program Officer at DataKind, a global nonprofit that applies data science to social good. Today she runs her own advisory practice, ANB Advisory Group, and is the co-author of The Tech That Comes Next, a book on building a more equitable world through technology.

Earlier this year she moderated comprehensive panel discussions with senior government executives at both our Tribal Innovation Summit and our State AI Officers Summit. 
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Turning Insight Into Practice

Afua's decade in public interest tech has left her most energized, these days, by the work of translation — taking insight and turning it into something decision-makers can actually use. 

"I've spent a decade in public interest tech, and right now what excites me most is helping decision-makers translate insight into practice," she said. She points to CCF's work with state leaders on AI as a rare opportunity to help shape agendas as they're being written, not after the fact.

That same instinct shows up in her enthusiasm for CCF's Public Benefit Innovation Fund. "I'm an engineer by training, and seeing people actually build something is what matters to me," she said. Tech for good, she added, can't be assumed — it has to be demonstrated, project by project, and the ideas surfacing through the Fund are proof that good work is already happening in the field.
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Making Room for Nuance

Afua sees a conversation dominated by extremes — one camp insisting AI adoption is inevitable and urgent, the other increasingly focused on real harms like job displacement, discrimination, and unaccountable tools. She'd like to see more room in between. 

First, a serious conversation about regulation: "I believe in AI, but let's be responsible about it — not just use it because it's there." Second, she wants more nuance about when adoption actually makes sense. 

Universal adoption isn't the goal, she argues; the harder and more useful questions are where AI should and shouldn't be used, and what accountability looks like when it is.
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Facilitating Hard Conversations

Afua's approach to facilitating dialogue among government leaders starts with the problem, not the technology: what are communities actually facing, and how are resources being distributed to serve them? 

From there, she works to translate technical concepts into plain language, on the theory that everyone — technical or not — should have a genuine say in how these systems get built and deployed. That includes an honest conversation about data itself, and what it means to lean on it for staffing and decision-making rather than on inconsistent human judgment. 

Finally, she believes that making change at scale requires pausing along the way to name what's working. "You have to find the wins worth celebrating," she said; a discipline she traces partly to her second career as a children's book author, where distilling big, complicated ideas into something clear and understandable is the entire job.
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Where to Look Next

Asked where the most promising work is happening, Afua is hesitant to point to just one place. Innovation is surfacing in rural communities and historically underinvested areas alike, across agencies of every size and region.

What she thinks deserves more attention is the harder, less visible work underneath the innovation: what it actually takes to build trust in automated systems, what recourse looks like when those systems get it wrong, and what it means to be a good steward of taxpayer dollars along the way. 

For Afua, it all comes back to one idea: that services delivered well don't just help people, they rebuild faith in government itself, and that principle should sit at the center of every AI adoption effort.

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