Tariq Khan

‘AI will accelerate consequences, making misalignment more visible and success more dependent on trust, clarity and responsibility’

Part of the AI Leadership Index – a curated list of the most inspirational figures shaping the AI revolution.

Tariq Khan is an accomplished technology leader with a First-Class Master's degree in Artificial Intelligence and Ethics from the University of Cambridge. He leads a 400 strong team at the London Borough of Camden across Product, Data, IT and Customer Services, where he focuses on transforming public service delivery through the responsible use of technology and data.

His work includes co creating the UK's first public sector AI Campus in collaboration with Google and leading the development of Camden's ethical data and AI frameworks, which have been adopted by the Alan Turing Institute and the United Nations.

Alongside numerous AI trials he is also part of the development of Waves, an AI powered platform for large scale citizen deliberation, designed to strengthen democratic participation and ensure public voice is meaningfully reflected in decision making.

Earlier in his career, Tariq delivered innovative and increasingly AI driven digital products and services for major private sector organisations including the Financial Times, Accenture and Coty, shaping global consumer platforms and data driven experiences at scale.

Please share a case study of how you have you innovated with AI over the last year?

Waves is an AI powered platform designed to transform how citizens are involved in public decision making, enabling meaningful deliberation at a scale that traditional engagement methods struggle to achieve. Developed through a partnership between the London Borough of Camden and Demos, and funded by Google.org, Waves responds to a growing challenge faced by governments globally, how to listen to large, diverse populations in ways that are inclusive, representative and genuinely influential.

At its core, Waves uses advanced natural language processing and machine learning techniques to analyse large volumes of qualitative input from citizens. Rather than reducing participation to surveys or headline statistics, the platform identifies themes, areas of consensus, points of tension and minority perspectives, allowing decision makers to understand not just what people think, but why.

This enables richer, evidence-based policy development while preserving the nuance of public voice. What makes Waves particularly powerful is its ethical and democratic grounding. Inspired by digital democracy pioneers like Audrey Tang in Taiwan, the platform is designed to amplify citizen voice rather than automate decisions.

AI is used as an assistive tool, supporting human judgement and transparency rather than replacing it. Strong governance, explainability and bias mitigation are embedded by design, aligning the platform with emerging global standards for trustworthy AI.

Funding from Google.org has enabled Waves to move beyond a theoretical concept into a practical, scalable civic technology. Waves represents a new model for democratic innovation, one that combines cutting edge AI with public interest values. By making large scale deliberation feasible, inclusive and actionable, it offers governments a powerful tool to rebuild trust, improve policy outcomes and strengthen democratic participation in an increasingly complex digital age.

What is the biggest challenge you have faced with AI innovation and how you have overcome it?

One of the biggest challenges I have faced in AI innovation is building public trust while working with complex technologies that are often poorly understood and sometimes actively mistrusted. AI and data driven systems can feel abstract, exclusionary, or even threatening, particularly to communities already affected by digital exclusion. This creates a real risk that AI innovation becomes something done to people rather than with them, undermining legitimacy and long-term impact.

A second challenge is engagement in an environment where outrage often drives attention. When public debate is shaped by polarisation and misinformation, meaningful discussion about nuanced topics such as data use, algorithmic decision making and ethical trade-offs becomes difficult. Traditional consultation methods struggle to surface informed, representative views, especially at scale. To address these challenges, we adopted a deliberative democracy approach, positioning citizens as partners in the design of AI and data systems.

At Camden, this meant working with residents to co define the principles, rules and safeguards governing how data and AI are used, rather than relying solely on technical or legal expertise. Through long running resident panels and partnerships with organisations such as the Alan Turing Institute and Involve, we co created the Camden Data Charter, grounded in the belief that data rights are human rights.

We also focused on structural change within the organisation. This included a design led transformation to build in house capability that is deeply citizen centred, and the co definition of success metrics with communities, ensuring AI initiatives are measured on real world outcomes rather than narrow efficiency gains.

How do you balance innovation with ethical safeguards?

Balancing innovation with ethical safeguards requires breaking down long standing barriers between data professionals and the citizens affected by their work. One of the most persistent challenges in AI innovation is the distance between technical teams and lived experience, which can unintentionally create power imbalances, mistrust and risk blind spots in design decisions.

We addressed this by deliberately creating psychologically safe environments where citizens and data professionals can engage as equals. This means moving away from expert led explanations towards shared exploration, where questions, uncertainty and disagreement are actively welcomed. In practice, this involved structured deliberative spaces where residents could challenge assumptions, surface concerns and influence how AI and data systems are shaped, without fear of being dismissed or overwhelmed by technical language.

For our teams, it also required cultural change, encouraging humility, openness and a willingness to listen rather than defend solutions. Crucially, this approach reframes ethics as a shared responsibility rather than a compliance function giving our data professionals gain clearer mandate and confidence to innovate within agreed boundaries. This has enabled more ambitious use of AI, because trust is built through relationship, transparency and ongoing dialogue rather than control alone.

How do you believe the artificial intelligence space will change over the next 12-24 months?

Over the next 12 to 24 months, I expect AI to be less immediately transformative than many predict, but far more revealing. We consistently overestimate what technology can do in the short term, expecting AI to fix complex organisational problems, while underestimating its long-term impact on how work, decision making and power structures evolve.

Near term, AI will expose weaknesses rather than resolve them. Poor data quality, broken processes, & unclear accountability will become more visible as AI amplifies whatever intent and structure already exist. If AI initiatives underperform, it will often reflect organisational readiness rather than technological capability.

As AI becomes ubiquitous, it will fade into the background. The most important changes will not look like "AI projects" but will show up in how decisions are supported, how services are designed and how people interact with systems every day. This shift will require institutions to adapt their culture, governance and skills, not just deploy new tools.

Ultimately, I don't see AI as a shortcut to better outcomes. It will not compensate for poor choices or flawed systems. Instead, it will accelerate consequences, making misalignment more visible and success more dependent on trust, clarity and responsibility.