Public sector automation and citizen trust

What if you could build a world class AI. Without ever seeing real data? For years, this has been the catch 22 of public sector transformation. We want to use AI to solve huge challenges like fraud, but the risk of exposing real citizen data has been a hard stop. Progress has been trapped between the promise of innovation and the duty of privacy. A new white paper from HM Revenue & Customs, however, offers a brilliant solution They are training advanced fraud detection models without ever using real taxpayer information, all thanks to synthetic data. It's artificially generated information that mirrors the statistical patterns of a real dataset, a high fidelity, privacy safe replica that allows teams to build, test, and innovate with complete freedom. This is a true game changer for government delivery. → It unlocks innovation, allowing teams to build models without navigating months of complex data access approvals. → It guarantees citizen privacy by design, building the public trust needed for wider AI adoption. → It accelerates project timelines, moving from theory to a functioning model in a fraction of the time. This update from HMRC sets out a new blueprint for responsible innovation across the public sector. It proves we can be both data driven and privacy centric. #AI #DataPrivacy #HMRC

The G7 Toolkit for Artificial Intelligence in the Public Sector, prepared by the OECD.AI and UNESCO, provides a structured framework for guiding governments in the responsible use of AI and aims to balance the opportunities & risks of AI across public services. ✅ a resource for public officials seeking to leverage AI while balancing risks. It emphasizes ethical, human-centric development w/appropriate governance frameworks, transparency,& public trust. ✅ promotes collaborative/flexible strategies to ensure AI's positive societal impact. ✅will influence policy decisions as governments aim to make public sectors more efficient, responsive, & accountable through AI. Key Insights/Recommendations: 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 & 𝐍𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬: ➡️importance of national AI strategies that integrate infrastructure, data governance, & ethical guidelines. ➡️ different G7 countries adopt diverse governance structures—some opt for decentralized governance; others have a single leading institution coordinating AI efforts. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 & 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 ➡️ AI can enhance public services, policymaking efficiency, & transparency, but governments to address concerns around security, privacy, bias, & misuse. ➡️ AI usage in areas like healthcare, welfare, & administrative efficiency demonstrates its potential; ethical risks like discrimination or lack of transparency are a challenge. 𝐄𝐭𝐡𝐢𝐜𝐚𝐥 𝐆𝐮𝐢𝐝𝐞𝐥𝐢𝐧𝐞𝐬 & 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 ➡️ focus on human-centric AI development while ensuring fairness, transparency, & privacy. ➡️Some members have adopted additional frameworks like algorithmic transparency standards & impact assessments to govern AI's role in decision-making. 𝐏𝐮𝐛𝐥𝐢𝐜 𝐒𝐞𝐜𝐭𝐨𝐫 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 ➡️provides a phased roadmap for developing AI solutions—from framing the problem, prototyping, & piloting solutions to scaling up and monitoring their outcomes. ➡️ engagement + stakeholder input is critical throughout this journey to ensure user needs are met & trust is built. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞𝐬 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐔𝐬𝐞 ➡️Use cases include AI tools in policy drafting, public service automation, & fraud prevention. The UK’s Algorithmic Transparency Recording Standard (ATRS) and Canada's AI impact assessments serve as examples of operational frameworks. 𝐃𝐚𝐭𝐚 & 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: ➡️G7 members to open up government datasets & ensure interoperability. ➡️Countries are investing in technical infrastructure to support digital transformation, such as shared data centers and cloud platforms. 𝐅𝐮𝐭𝐮𝐫𝐞 𝐎𝐮𝐭𝐥𝐨𝐨𝐤 & 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: ➡️ importance of collaboration across G7 members & international bodies like the EU and Global Partnership on Artificial Intelligence (GPAI) to advance responsible AI. ➡️Governments are encouraged to adopt incremental approaches, using pilot projects & regulatory sandboxes to mitigate risks & scale successful initiatives gradually.

#AI in the public sector? And yet it moves! And it’s a prime example of how technological advancement requires the highest social and ethical standards. “Ethical Integration in Public Sector AI”: the new IAB X Center for Responsible AI Technologies study is out. It addresses the ethical design of AI in the public sector, with a focus on #PublicEmploymentServices (PES). While AI is increasingly employed to streamline administrative processes and improve service delivery, its application in employment mediation raises fundamental concerns regarding #fairness, accountability, and democratic legitimacy. The EU AI Act has further underscored the urgency of addressing these challenges by classifying employment-related AI systems as high-risk. We examine how ethical and social considerations can be systematically embedded in the development and implementation of public sector AI. Using the German PES as a case study, we introduce the “Embedded #Ethics and Social Sciences” approach, which integrates ethical reflection and practitioner involvement from the outset. Qualitative insights from interviews with caseworkers highlight the socio-technical challenges of implementation, particularly the need to reconcile efficiency with citizen trust. We propose concrete design elements emerging from the integration of ethical and social considerations into system development: data ethics, bias, fairness, explainable AI. The approach supports compliance with new regulatory requirements but also strengthens human oversight and shared decision-making.

In an era where data is the new oil, will governments settle for static dashboards — or build living, self-improving systems that shape the future? The UAE has answered this question boldly. Under the leadership of HH Sheikh Mohammed Bin Rashid Al Maktoum, the UAE has launched an AI-powered federal performance measurement system that moves beyond simply tracking progress it engineers national resilience and long-term competitive advantage. Why is this necessary? Global trends demand urgent government transformation: • By 2030, AI will add USD 15.7 trillion to the global economy through efficiency and innovation. • Up to 70% of public sector processes can be automated, cutting errors and manual work. • Inefficiencies cost governments USD 3 trillion annually, draining resources needed for strategic priorities • Crises now escalate five times faster than two decades ago, making static systems obsolete (OECD). What is the UAE doing differently? Unlike most governments that rely on periodic, historical data reviews, the UAE’s system focuses on real-time intelligence and predictive foresight. Key components include: • Advanced AI algorithms analyzing billions of data points across economic, health, environmental, and security indicators. • Predictive modeling to simulate policy impacts and stress-test national strategies. • Dynamic dashboards integrating data across ministries, providing leaders with a real-time, unified national operating picture. • Adaptive resource allocation, enabling budget and manpower shifts within days, not months. What are the concrete outcomes? • Economic resilience: AI to add AED 335 billion (USD 91 billion) to GDP by 2030 (13.6% of total output). • Service efficiency: Up to 30% cost savings, 40–60% faster services, and 90% fewer errors. • Resource optimization: 25–35% more efficient cross-ministry budgets, freeing billions. • Policy agility: Policy cycle times cut by up to 50% for rapid response. • Citizen satisfaction: Up to 35% higher satisfaction and stronger public trust. • Global competitiveness: UAE ranks top 10 worldwide in AI readiness, reinforcing digital leadership. How does this shape the future? The UAE is not just measuring performance: it is building a living, adaptive system of governance that: • Anticipates and mitigates disruptions before they escalate. • Dynamically reallocates resources for maximum national impact. • Designs policies with deep societal and economic insight. • Strengthens trust through transparent, citizen-focused services. “Continuous improvement is a core habit of government work, because stopping the development of our tools means falling behind. Our motto: ‘There is no perfect system, but everything can be developed and improved.’” — HH Sheikh Mohammed Bin Rashid Al Maktoum The UAE is not just building a nation it is setting a global standard for excellence, resilience, and future-ready leadership. The UAE has made its choice. The world is watching.

The OECD’s Governing with Artificial Intelligence report provides one of the most comprehensive examinations of how governments are moving from experimenting with AI to governing with it. The report makes clear that technology alone is not enough. Institutions, leadership, and trust determine whether AI improves public value or erodes it. What the paper outlines • The report draws from case studies across OECD countries and partner economies showing how AI is being used in policymaking, service delivery, and public administration • It identifies three main areas of focus: strategic leadership and policy coherence, responsible and trustworthy use, and enabling infrastructure and skills • The report stresses that fairness, accountability, and inclusion are essential to maintaining public trust • Building institutional capacity, improving data governance, and developing skilled workforces are critical for scaling AI responsibly Why this matters • AI is becoming a key capability for governments in policy design and service delivery • Responsible use frameworks protect rights, enhance accountability, and ensure fairness in automated decision-making • Institutional readiness, including leadership and legal frameworks, determines whether AI strengthens or weakens democratic governance • Public sector governance sets the tone for responsible AI use across society Key takeaways • Strategic coordination across government ensures coherence in AI use and oversight • Risk management, transparency, and explainability should be built into every stage of AI development and deployment • Training public servants in data literacy and ethical AI improves decision quality and accountability • Shared infrastructure and collaboration across borders can accelerate responsible innovation Who should act • Senior government leaders developing national strategies for AI and digital transformation • Policy and ethics teams embedding fairness and human oversight in design and deployment • Technical and data teams creating robust infrastructure and governance mechanisms • International organizations and partners working to harmonize standards and share best practices Action items • Develop whole-of-government frameworks that integrate transparency and accountability • Strengthen algorithmic governance and clear communication about how AI is used in public services • Invest in workforce training and institutional capacity for AI oversight and evaluation • Foster cooperation across governments to share evidence, tools, and lessons learned Bottom line The OECD’s Governing with Artificial Intelligence report shows that the question is no longer whether governments will use AI but how they will govern with it. Success depends on turning capability into accountability and ensuring that AI serves people transparently, responsibly, and with trust at its core.

Rushing headlong into AI without clear guardrails puts people at risk. The stakes in government are higher and the consequences far greater than in Silicon Valley. When government systems break, real people suffer. The question before us isn't whether AI can improve government services - it's whether we have the will to do it the right way. We need: • Transparency in how AI systems make decisions that affect people's lives • Strong ethical frameworks to prevent bias and protect privacy  • True public accountability, not just private sector oversight • Human-centered design that puts people first We've seen what works when government innovates responsibly - delivering services that are accessible, efficient and trusted. This takes bringing the right voices to the table - technologists who understand government complexity, civil servants who know their communities, and the people these systems will serve. The future of government AI isn't about replacing human judgment. It's about augmenting it thoughtfully to deliver better outcomes for everyone. Let's focus on building AI that strengthens democracy and public trust, not undermines it. #ResponsibleAI #GovTech #PublicService

AI is transforming how government operates — but how do we know it’s working for the people we serve? The new M-25-21 memo from the Office of Management and Budget lays out a bold path for accelerating the responsible use of AI in federal agencies. Included in this policy is a powerful reminder: if we’re not listening to the public, we’re not doing it right. Section 8 of the memo directs agencies to actively solicit feedback from the public — not just during design, but throughout the entire lifecycle of an AI system powering service delivery and more. It calls for usability testing, post-transaction, “Tell Us About Your Experience” prompts, public meetings, and more. Customer experience (CX) is central to AI governance and service delivery. Today’s most forward-leaning agencies are operationalizing CX — not just measuring satisfaction, but embedding real-time feedback loops into the systems that power everyday interactions. With the rise of AI, these feedback mechanisms are more critical than ever. Why? Because while AI can scale decisions, CX ensures we scale the right ones. And to do that you need nervous system of experience. Operational CX platforms allow us to: - Track the impact of AI on service quality to understand effeciency and effectiveness with great fidelity - Identify friction and failure points in real time - Enable continuous learning from the voice of the customer and employee - Build trust through transparency, responsiveness, and accountability This is mission-critical. As we invest in modernizing government through AI, we must also modernize the way we listen. Feedback is the fastest path to efficiency, effectiveness, productivity, innovation, performance, trust, and better outcomes. AI moves fast. Trust moves at the speed of experience. Embracing operational CX will help build and transform systems that work for the people. #Leadership #AI #CX #ServiceDelivery #OperationalCX #CustomerExperience #PublicTrust #Technology #Innovation #Government