Digital Public Services

INDIA GOES OFFLINE, DIGITALLY! The Reserve Bank of India has launched the Offline Digital Rupee, a Central Bank Digital Currency that can move from one wallet to another even without internet or mobile network. Imagine paying for a cup of tea in the Himalayas or for groceries in a rural market where connectivity is zero and still completing the transaction in seconds. ✅ Digital trust has reached a new level. Money that works without the internet is not a product of convenience. It is the evolution of trust. When the value can move offline yet remain verified and authentic, we are witnessing the future of financial inclusion, not just technology. ✅ It solves the last-mile problem. For years, digital payments depended on networks, servers, and gateways. Rural India, remote areas, and even disaster zones were often left behind. The Offline Digital Rupee removes that dependency and gives digital money a physical character. This changes how we think of accessibility forever. ✅ It is faster, cheaper, and smarter. No third-party switches. No failed connections. No dependency on payment gateways. The value moves directly from one device to another, just like cash, but secured by blockchain-based architecture and backed by the central bank. The power of digital efficiency now exists without digital dependence. ✅ Programmable money means purposeful money. The RBI’s Programmable Central Bank Digital Currency model means money can be coded for a reason. Subsidies can be released only for their intended use. Corporate payouts can have specific validity. Social benefits can be tracked transparently. It adds responsibility to the currency itself. ✅ It redefines how economies will interact. Offline CBDC is not just a domestic innovation. It opens the door for new models of cross-border settlements, disaster-resilient financial systems, and new layers of fintech innovation. The world will look at this model as a live example of how technology can merge with human need, not just convenience. ✅ It reminds us what innovation truly means. The right innovation is not when a feature gets smarter, but when it becomes more inclusive. When a person in a no-network zone can transact as easily as someone in a metro city, that is when digital transformation turns into social transformation.

In much of the world, digital financial tools are a daily reality—used to process paychecks, pay for dinner, buy groceries, and more. But 1.4 billion adults in low- and middle-income countries still lack access to these tools.    This isn’t just an inconvenience for them; it's a barrier to economic growth and empowerment. According to a 2023 UN analysis, digital public infrastructure—including digital ID, payments, and data exchange—could accelerate GDP growth in these countries by 20 to 33 percent.    That’s where Mojaloop Foundation comes in: Their open-source software makes it possible for countries to build inclusive digital payment systems that allow anyone with a mobile phone to send and receive money securely, instantly, and affordably. This has the potential to drive economic inclusion—and open the doors to financial freedom—for billions.

Australia ❤️ is good at digital govt. But in a world of rapid change, good isn’t good enough 🤷♂️ When people think of world-leading digital nations, they point to Singapore, Estonia, and increasingly, the UAE. Yes - they’re small, agile, and highly coordinated. But size is no excuse. 🇺🇦 Ukraine (pop. ~40 million) is racing toward Gov 3.0 maturity via its Diia platform - even during a war. 🇮🇳 India (pop. 1.5 billion 🤯) is delivering digital transformation at national scale. The India Stack, anchored by Aadhaar, is enabling inclusion, innovation, and economic uplift for over a billion people. ✳️ Why does this matter? One word: Productivity As population growth and participation rates flatten, productivity becomes the key to prosperity. Treasurer Jim Chalmers is right ✅ to put it front and centre - he’s convening a national productivity roundtable on 25 August to build consensus for reform. Last year, I co-led a productivity roadshow across Australia and New Zealand, asking: Which govt services would deliver the biggest productivity dividend if digitised at scale? The result? The GX5 : Five digital initiatives with the biggest productivity upside We assessed 24 govt digitalisation opportunities and filtered them through three lenses: 1. Citizen-facing – high visibility and public benefit 2. Deployment-ready – proven globally, good to go 3. High productivity impact – across govt, business, and individuals The top five: 🟦 Digital ID – secure, streamlined identity verification 🟦 Digital Skills Wallet – verified, portable credentials 🟦 Digital Front Door – one-stop access to govt services 🟦 Digital Health Record – accessible, coordinated medical data 🟦 Digital Licences & Permits – instantly verifiable credentials 📊 According to the attached GX5 report, Digital ID alone could unlock $19–32 billion per year in economic benefits - up to 1.2% of GDP - based on results from Singpass (Singapore) and Aadhaar (India) . Importantly, the Federal Govt passed legislation last year 🙏 to enable an opt-in digital ID system - a critical reform that will boost security, privacy, and service delivery across the country. This attached report was a collaboration between Ember Advisors and ServiceGen, with support from Amazon Web Services (AWS). If we want to stay globally competitive, we must build and embrace public digital infrastructure. It’s how we move from good to great 🙏🏼

“𝐂𝐚𝐧 𝐈 𝐭𝐚𝐥𝐤 𝐭𝐨 𝐚 𝐡𝐮𝐦𝐚𝐧, 𝐩𝐥𝐞𝐚𝐬𝐞?” 𝐓𝐡𝐢𝐬 𝐢𝐬 𝐬𝐭𝐢𝐥𝐥 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐜𝐨𝐦𝐦𝐨𝐧 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐧 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐬𝐲𝐬𝐭𝐞𝐦𝐬. Not because technology is slow. But because trust is missing. The numbers are clear: 👉 37% of people have never used a digital assistant. 👉 74% prefer a human - even for simple questions. 👉 Only 27% trust digital systems when advice or judgment is needed. That is not an adoption problem. It is a confidence problem. A simple example. You ask a system: “𝐈𝐬 𝐭𝐡𝐢𝐬 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐟𝐨𝐫 𝐦𝐞?” It answers instantly. Sounds confident. Uses perfect language. But it cannot explain why. It cannot say where it might be wrong. And 𝐢𝐭 𝐜𝐚𝐧𝐧𝐨𝐭 𝐭𝐚𝐤𝐞 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲. That is the moment people pull back. Most digital systems work well for: ✅ status checks ✅ simple questions ✅ saving time But they struggle when: ❌ context changes ❌ emotions matter ❌ consequences are real And this is where leadership matters. For years, automation was built to reduce cost. Users experience it as a risk. 𝐒𝐩𝐞𝐞𝐝 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐨𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩 𝐟𝐞𝐞𝐥𝐬 𝐮𝐧𝐬𝐚𝐟𝐞. Correct answers without empathy feel cold. Decisions without escalation feel dangerous. The next generation of digital systems will not win because they are smarter. They will win because they know: ✔️ when to answer ✔️ when to explain ✔️ and when to bring in a human This is not about replacing people. It is about building systems people can rely on. So here is the real question for leaders: 𝐈𝐟 𝐩𝐞𝐨𝐩𝐥𝐞 𝐝𝐨𝐧’𝐭 𝐭𝐫𝐮𝐬𝐭 𝐲𝐨𝐮𝐫 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐯𝐨𝐢𝐜𝐞, 𝐰𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐚𝐭 𝐬𝐚𝐲 𝐚𝐛𝐨𝐮𝐭 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐝𝐞𝐬𝐢𝐠𝐧 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲? What builds trust faster today: better answers - or clearer ownership? 𝘛𝘳𝘶𝘴𝘵 𝘪𝘴 𝘭𝘪𝘬𝘦 𝘨𝘭𝘢𝘴𝘴. 𝘌𝘢𝘴𝘺 𝘵𝘰 𝘣𝘳𝘦𝘢𝘬. 𝘏𝘢𝘳𝘥 𝘵𝘰 𝘴𝘩𝘢𝘱𝘦. 𝘗𝘰𝘸𝘦𝘳𝘧𝘶𝘭 𝘸𝘩𝘦𝘯 𝘥𝘰𝘯𝘦 𝘳𝘪𝘨𝘩𝘵. 𝘈𝘳𝘵 𝘣𝘺 𝘚𝘪𝘮𝘰𝘯 𝘉𝘦𝘳𝘨𝘦𝘳.

When I was teaching infodemic management at the WHO during the pandemic, we asked the CDC colleagues to discuss five communication failures that consistently derail public health efforts: - Mixed messages from multiple experts - Information released too late - Paternalistic messaging - Failing to counter rumors in real-time - Public-facing power struggles and confusion   In the US, all five are now happening at once.   Public trust in health institutions is unraveling. People are adapting by building decentralized, multi-source, often crowdsourced “trust ecosystems.”   This is what the New York Times comment section revealed after a recent article recommended credible health information sources. The comments were not fringe. They reflected skepticism, discernment, and a shift toward self-curated information strategies.   Readers reported: - Turning to Mayo Clinic, Cleveland Clinic, Wikipedia, and NHS UK over US government sites. - Avoiding .gov domains due to perceived politicization. - Using AI cautiously, as a first filter, not a final word. - Proposing solutions like health site trust ratings, simplified printouts, and community-led education.   Public health needs to meet this moment. Not by restoring the old systems, but by fostering something new for health information search, access and use: - Transparent, independent curation - Tools for triangulation and critical analysis - Localized, multilingual resource hubs - Responsible AI-supported health navigation - Community-led health literacy models   Each of these comes with ethical, practical, and equity challenges.   We need to think big picture and hyper-local at the same time.   I don’t have all the answers. But I believe we need to build—together—a health information ecosystem for a fragmented, fractal, globalized, and crisis-prone world.

#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.

The Cabinet Office publishes brilliant digital standards. So why do so many programmes struggle to follow them? I've worked on enough Whitehall programmes to see the pattern. Teams start with the best intentions, armed with the Service Manual, Technology Code of Practice, and Data Standards. Then reality hits. Departmental politics. Legacy constraints. Procurement timelines that don't align with agile principles. The standards aren't wrong. They're excellent frameworks built on hard-won lessons from GOV.UK and digital pioneers. But they were written for ideal conditions.  Most departments don't operate in ideal conditions. The gap between what the playbook says and what actually works in your specific department kills momentum. Teams either ignore the standards entirely or follow them so rigidly they miss the point. There's a better path. Understanding when to adapt the standards without abandoning their core principles. This carousel breaks down where theory meets delivery reality and how to bridge that gap pragmatically. Swipe to see how to follow the spirit of the standards, not just the letter. #GovTech #DigitalTransformation #PublicSector #ProgrammeDelivery

🇺🇦 More lessons from 4 years of Ukrainian resistance to Russian warfare : « information defence for democratic resilience » By the Digital Policy Hub & Centre for International Governance Innovation (CIGI) By Halyna Padalko, PhD 🛡️ On the defensive side, government centres, venture-backed start-ups and non-governmental organization (NGO) watchdogs run machine-learning (ML) pipelines that produce real-time alerts on coordinated inauthentic behaviour, deepfake videos and narrative shifts. ⚔️ On the offensive side, ministries employ generative media, from multilingual subtitling to synthetic spokespeople such as “Victoria Shi” to deliver rapid, values-aligned messages that galvanize support abroad and bolster morale at home, while precision deepfake “counterpunches” sow confusion in hostile audiences. 🇺🇦 Ukraine’s response is effective because it is deliberately plural: 🔹military intelligence and stratcom units plug directly into AI platforms built by start-ups such as Osavul, LetsData, Open Minds and Mantis Analytics, while investigative newsrooms Texty.org.ua and fact-checking NGOs such as VoxUkraine and Detector Media use similar tools to contextualize or debunk falsehoods. 🔹This networked architecture accelerates innovation and diffuses verification capacity across society, creating an “information shield” that denies Russia’s disinformation campaigns the “oxygen” of surprise. 🔹Rapid legislative reform (for example, Media Law 2022, Advertising Law 2023) and alignment with the EU Digital Services Act (DSA) provide legal scaffolding for transparency, user rights and platform accountability. In parallel, the Ukraine’s Ministry of Digital Transformation’s WINWIN AI Centre of Excellence is spearheading a Ukrainian-language large language model (LLM) to anchor domestic AI services and reduce dependence on foreign tech. 🎓Ukraine treats education as national security. Media literacy rates surged, driven by state programs (Filter), massive open online courses (Diia.Education) and hands-on academies (PROMPTO). 🔹Grassroots hackathons and EU-supported training translate civic awareness into professional skill sets, ensuring that technical advances are matched by a population capable of critical consumption.

"The rapid evolution and swift adoption of generative AI have prompted governments to keep pace and prepare for future developments and impacts. Policy-makers are considering how generative artificial intelligence (AI) can be used in the public interest, balancing economic and social opportunities while mitigating risks. To achieve this purpose, this paper provides a comprehensive 360° governance framework: 1 Harness past: Use existing regulations and address gaps introduced by generative AI. The effectiveness of national strategies for promoting AI innovation and responsible practices depends on the timely assessment of the regulatory levers at hand to tackle the unique challenges and opportunities presented by the technology. Prior to developing new AI regulations or authorities, governments should: – Assess existing regulations for tensions and gaps caused by generative AI, coordinating across the policy objectives of multiple regulatory instruments – Clarify responsibility allocation through legal and regulatory precedents and supplement efforts where gaps are found – Evaluate existing regulatory authorities for capacity to tackle generative AI challenges and consider the trade-offs for centralizing authority within a dedicated agency 2 Build present: Cultivate whole-of-society generative AI governance and cross-sector knowledge sharing. Government policy-makers and regulators cannot independently ensure the resilient governance of generative AI – additional stakeholder groups from across industry, civil society and academia are also needed. Governments must use a broader set of governance tools, beyond regulations, to: – Address challenges unique to each stakeholder group in contributing to whole-of-society generative AI governance – Cultivate multistakeholder knowledge-sharing and encourage interdisciplinary thinking – Lead by example by adopting responsible AI practices 3 Plan future: Incorporate preparedness and agility into generative AI governance and cultivate international cooperation. Generative AI’s capabilities are evolving alongside other technologies. Governments need to develop national strategies that consider limited resources and global uncertainties, and that feature foresight mechanisms to adapt policies and regulations to technological advancements and emerging risks. This necessitates the following key actions: – Targeted investments for AI upskilling and recruitment in government – Horizon scanning of generative AI innovation and foreseeable risks associated with emerging capabilities, convergence with other technologies and interactions with humans – Foresight exercises to prepare for multiple possible futures – Impact assessment and agile regulations to prepare for the downstream effects of existing regulation and for future AI developments – International cooperation to align standards and risk taxonomies and facilitate the sharing of knowledge and infrastructure"