How young people can shape AI in public services

Technology is reshaping the relationship between citizens and governments, creating opportunities to transform public services into systems that are proactive, responsive and centred on people.

Artificial Intelligence (AI) and data could help governments move beyond reactive delivery towards anticipatory models. However, insights gathered from a workshop with Hub Leaders from the Global Shapers Community in Geneva this summer highlight that, from a youth perspective, this transformation must place responsibility and local value creation at its core.

Otherwise, AI risks reinforcing inefficiency or narrowing innovation through misplaced metrics of accuracy and performance over human impact and social value, a scenario that arises precisely when humans are not kept at the centre of design and decision-making.

Global trends indicate that governments are already underway in publishing their AI strategies – the Artificial Intelligence Index Report 2024 found that of legislation containing “artificial intelligence” in 128 countries, between 2016 and 2023, 32 countries have enacted at least one AI-related bill.

However, many lack frameworks for monitoring outcomes or assessing risks.

The OECD has warned that digital government adoption is advancing unevenly. Many countries still struggle with interoperability and governance capacity, meaning that their systems often lack the structure to share data effectively, limiting coordination, efficiency and the ability to deliver seamless public services.

From a youth standpoint, urgency arises not only from the scale of adoption but also from the opportunity to reimagine governance itself. The July workshop also found that AI is arriving in public systems just as younger generations are demanding transparency, inclusivity and measurable, positive impact.

The possible benefits of technology in government are numerous: reduced bureaucracy, faster access to health and social services, increased responsiveness to citizen concerns and even the application of AI to develop, evaluate and implement more effective policies.

Data-driven systems can preserve institutional memory, inform decisions and make service performance transparent. However, unlocking these gains requires governments to be citizen-first, not system-first.

Consider Germany, where digital health projects such as electronic health records have been introduced to empower patients by giving them direct access to their personal health data, enabling informed choices and greater control over their care. Yet, implementation has been undermined by fragmented governance, leaving its elektronische Patientenakte (ePA) system complex and underused.

Even basic access to unified records – so that all of an individual’s health data is held in one place – remains difficult. The challenge is not unique to Europe. In the Philippines, siloed databases and fragmented open data portals prevent agencies from interoperating effectively.

Meanwhile, in Latin America, countries such as Chile lack a central framework for tracking digital government investments, with oversight dispersed across agencies and no integrated monitoring system. Therefore, beyond infrastructure, governance, design and accountability would help make systems work for their service users.

What are the risks of over-reliance on technology without adequate innovation strategies?

Building critical public systems that are perpetually dependent on AI is risky, as it can expose citizens to service disruptions, privacy breaches and power imbalances, underscoring the need to design AI in public services around human oversight, accountability and resilience.

Digital sovereignty is often framed around where data is stored but sovereignty also means having capacity through skilled teams, resilient infrastructure and governance frameworks that allow states to use data in the public interest.

Publishing open data, for instance, is insufficient if citizens lack the tools or literacy to use it meaningfully. When it is accessible, open data can empower communities to scrutinize government actions, foster accountability and build trust. However, these benefits are lost without the capacity to interpret and apply the information.

The EU’s approach under the Data Governance Act demonstrates that establishing legal frameworks for data sharing must go hand-in-hand with investments in local talent, reliable technical infrastructure and sufficient operational funding to ensure data is truly usable across borders and sectors.

Otherwise, sovereignty becomes symbolic, leaving governments dependent on external vendors or concentrating control in narrow centres of power.

Security and resilience are equally relevant. Public infrastructures must be designed to resist cyberattacks, safeguard citizen data and continuously measure performance, because without these protections, citizens cannot trust or benefit from AI-enabled public services.

The US-based GovTech initiative, Propel, which develops tools for evaluating AI models in public assistance programmes, demonstrates how continuous measurement frameworks can strengthen accountability by monitoring performance, detecting bias and ensuring that AI-driven decisions serve citizens fairly and transparently.

However, to significantly transform citizen interactions with government services, we must make complex systems transparent by providing clear explanations of AI decisions, auditing algorithms for fairness and enabling oversight.

A pertinent example is Mexico’s initiative to introduce a biometric CURP (Clave Única de Registro de Población), which will incorporate fingerprint and iris data into a unified digital identity system. This raised significant concerns among digital rights groups, who warn that the system could lead to mass surveillance and potential human rights violations.