Building the Workforce_ AI for Viksit Bharat 2047
20 Feb 2026 14:00h - 15:00h
Building the Workforce_ AI for Viksit Bharat 2047
Session at a glance
Summary
This discussion centered on the launch of a Digital Capacity Building Alliance at the India AI Impact Summit, focusing on integrating artificial intelligence into public governance while maintaining human-centric approaches. Dr. Washima and Chairperson Shubhavi S. Radha Chauhan opened the session by emphasizing the need for ethical, accountable AI frameworks that serve citizens effectively, highlighting India’s Mission Karmayogi as a model for civil service transformation.
The panel discussion, moderated by Subramanian Ramadorai, brought together international experts to address AI implementation challenges in government systems. Anil Shivastava from Google Cloud emphasized that AI cannot simply be layered onto existing legacy systems, requiring fundamental reengineering of IT infrastructure and processes to harness AI’s full potential. He stressed the importance of contextual data, multilingual support, and enhanced security measures for effective AI deployment.
Guilherme Albusco Almeida from Brazil highlighted opportunities for Brazil-India collaboration in AI governance, particularly in research and development, capacity building, and creating ethical frameworks for AI implementation. He noted Brazil’s experience with training civil servants across different profiles and using AI for environmental monitoring and deforestation prevention.
Robin Scott from Apolitical Network identified critical gaps in AI readiness, revealing that 75% of government officials implementing AI don’t understand their own ethical frameworks, and many lack proper evaluation plans for AI pilots. Despite these challenges, she noted strong optimism among public servants about AI’s potential benefits.
The discussion addressed environmental concerns, with panelists advocating for both “green AI” (sustainable computing) and “AI for green” (using AI to address climate challenges). Minister Dr. Jitendra Singh concluded by introducing the MANAV framework – emphasizing moral systems, accountable governance, national sovereignty, accessibility, and validity. He stressed that while AI can substitute many functions, it cannot replace human integrity, advocating for a hybrid model that combines artificial intelligence with human intelligence. The event culminated in launching a blueprint for international collaboration in AI-enabled governance capacity building.
Keypoints
Major Discussion Points:
– AI-enabled governance and capacity building: The discussion centered on integrating artificial intelligence into public administration while ensuring human-centric approaches, with emphasis on the need for ethical frameworks and human oversight in AI-driven government services.
– Launch of Digital Capacity Building Alliance: A key announcement was the unveiling of a blueprint for a global alliance aimed at building AI capacity in public services, bringing together governments, industry, academia, and civil society to create shared standards and frameworks.
– Technical challenges of AI implementation in government: Panelists discussed the risks of layering AI systems onto legacy infrastructure without proper structural reform, emphasizing the need for data integration, security considerations, and reengineering of existing processes.
– International collaboration on AI governance: Significant focus on how countries like India and Brazil can collaborate to shape global conversations around trustworthy AI, sharing best practices in capacity building and creating South-South partnerships for responsible AI deployment.
– Environmental sustainability and AI: Discussion of the environmental footprint of AI technologies and the dual approach of “AI for green” (using AI for climate solutions) and “green AI” (making AI systems themselves more environmentally sustainable).
Overall Purpose:
The discussion aimed to launch and promote a global Digital Capacity Building Alliance focused on preparing public servants and government institutions for AI-enabled governance. The event sought to establish frameworks for ethical, inclusive, and human-centric AI implementation in public services while fostering international collaboration.
Overall Tone:
The tone was formal and optimistic throughout, maintaining a diplomatic and collaborative atmosphere. Speakers consistently emphasized hope and possibility while acknowledging challenges. The discussion remained constructive and forward-looking, with participants sharing expertise and expressing commitment to partnership. The tone became slightly more personal and reflective during Minister Dr. Jitendra Singh’s closing address, where he emphasized the importance of integrity and human values in AI implementation.
Speakers
Speakers from the provided list:
– Dr. Washima – Role/Title: Not specified, Area of expertise: Not specified
– Moderator – Role/Title: Event moderator, Area of expertise: Not specified
– Shubhavi S. Radha Chauhan – Role/Title: Chairperson of the Capacity Building Commission, Area of expertise: Public administration and capacity building
– Subramanian Ramadorai – Role/Title: Chairperson of Karni Nagi Bharat and former M.D. and CEO of Tata Consultancy Services, Area of expertise: Technology engineering and technology governments, intersection of technology and institutions
– Guilherme Albusco Almeida – Role/Title: Senior consultant at the Institute of Management and Corporation in Public Services, Government of Brazil, Area of expertise: Government reform and digital transformation
– Anil Shivastava – Role/Title: Chief Architect for Google’s work in the public sector, leads Public Policy Strategic AI Solution Engagements of Global Cloud in India, Area of expertise: AI solutions and public sector technology
– Robin Scott – Role/Title: Co-founder and CEO of Apolitical Network, Area of expertise: Global online network of public servants, AI training and capacity building
– Dr. Jitendra Singh – Role/Title: Honorable Minister, Minister of State for Personnel, Minister of State for Personal Grievances and Pensions, Area of expertise: Administrative reforms and India’s science and innovation agenda
– Audience – Role/Title: Professor Charu from Indian Institute of Public Administration (one identified audience member), Area of expertise: Public administration
– Speaker 1 – Role/Title: Not specified, Area of expertise: Not specified
– Speaker 3 – Role/Title: Not specified, Area of expertise: Not specified
Additional speakers:
None identified beyond the provided speakers names list.
Full session report
This discussion at the India AI Impact Summit marked the launch of a Digital Capacity Building Alliance, bringing together international experts to address the integration of artificial intelligence into public administration while maintaining human-centric approaches and ethical frameworks.
Opening Framework and Vision
Dr. Washima opened the session by establishing AI as “the next big thing after electricity” and emphasizing technology’s role as a great leveller. She highlighted the dual role individuals play in this transformation and stressed the need for trust-based collaborative ethical frameworks that can deliver faster, better, and safer public services.
Chairperson Shubhavi S. Radha Chauhan introduced the MANAV vision for human-centric AI governance, notably disclosing that her speech was “handcrafted” with “no AI in the process.” Her most significant contribution was asserting that “the future of AI, more precisely the agentic AIs, will not be in massive monolithic models. It will be in small language models, context-specific, sectoral, and decentralised.” This perspective challenged dominant narratives about AI development and emphasized localized, contextual solutions.
Technical Infrastructure Challenges
Anil Shivastava from Google Cloud addressed a critical misconception, emphasizing that “AI is not a layer that you could just put on existing systems.” He explained that existing IT systems were built with specific objectives creating data silos, while AI requires contextual data and holistic integration.
Shivastava outlined key requirements: reengineering existing IT systems, preparing data for training both large and small language models, ensuring multilingual support for frontline workers like ASHA workers, and addressing security and data sovereignty concerns. His analysis revealed that successful AI integration requires fundamental process reengineering, not just technological overlay.
International Collaboration and Brazil’s Experience
Guilherme Albusco Almeida from Brazil, noting his fifth trip to India, identified strong collaboration opportunities in research, capacity building, and ethical framework development. Brazil’s experience includes developing ethical assessment frameworks and comprehensive training programmes for civil servants across different profiles.
Brazil’s practical applications include AI for environmental monitoring, particularly a Rural Environmental Registry system using AI to detect deforestation. Almeida advocated for South-South collaboration, suggesting Brazil and India are “well positioned to conduct this conversation in a global perspective,” offering an alternative to the US-China binary framework.
Critical Gaps in AI Readiness
Robin Scott from Apolitical Network presented concerning data about AI readiness gaps. Her most striking finding: among those implementing AI in governments, only 26% understand their own government’s ethical frameworks, meaning 75% are “freestyling,” which “builds a great deal of risk into the system.”
Scott identified a gap between ambition and evaluation: while 72% of leaders have or plan AI pilots, only 45% have evaluation plans. She emphasized “there is no point piloting something without evaluation.” Despite these challenges, over 90% of public servants remain optimistic about AI’s potential.
India’s Strategic Vision and Third Way
Subramanian Ramadorai, drawing on five decades in technology, positioned AI as a “Sputnik moment” with power “not to do things better but to do better things.” He articulated India’s potential to offer a “third way” in AI development – a partnership-focused approach leveraging India’s IT professionals and trust-building capabilities, distinct from US market-led or Chinese state-led approaches.
Ramadorai emphasized India’s digital public infrastructure including Aadhaar, UPI, and DEPA as “trust architectures.” His vision suggested “the next billion AI users may not interact with GPT and parameter models. They may interact with tiny embedded AI in phones, tractors, classrooms, clinics and local government systems.”
Philosophical Foundations and Human-Centric Governance
Minister Dr. Jitendra Singh provided philosophical grounding, emphasizing that “digital public good” is synonymous with good governance – the digital aspect represents new means for established ends. He noted the government’s reform commitment, having eliminated almost 2,000 outdated rules while embracing new practices.
Dr. Singh’s key assertion was that “artificial intelligence can substitute everything on this planet but it cannot substitute integrity.” He advocated for hybrid models combining artificial and human intelligence, noting “one has to be intelligent enough to use artificial intelligence.” His example of rural clinics using both AI and human doctors illustrated this approach, where AI provides technical capabilities but human interaction remains essential for trust and satisfaction.
The Minister decoded the MANAV framework: Moral and ethical systems, Accountable governance, National sovereignty, Accessible and inclusivity, and Validity and legitimacy – providing comprehensive guidance for human-centric AI governance.
Environmental Sustainability
The discussion addressed environmental concerns through Almeida’s framework of “AI for green” versus “green AI.” Brazil’s forest monitoring system exemplified using AI for environmental solutions, while Shivastava noted Google’s commitment to carbon-neutral operations, representing the need to make AI infrastructure itself sustainable.
Addressing Existential Urgency
An audience intervention referenced the Doomsday Clock at “85 seconds to midnight,” questioning whether the 2047 timeline for Viksit Bharat represents “procrastination of our responsibilities” and calling for a “concert of civilizations by 2026 itself.” This reframed discussions from incremental progress to civilizational survival, highlighting tension between methodical capacity building and urgent global coordination needs.
Launch of the Digital Capacity Building Alliance
The session culminated in launching the Digital Capacity Building Alliance blueprint, described as a “global public good for inclusive, ethical, capacity building.” The alliance aims to unite governments, industry, academia, civil society, and startups to create shared standards for AI-enabled governance.
The alliance represents a unique model combining demand, design, delivery, and evolution, steered by the Capacity Building Commission and Mission Karmayogi. It embodies “Sarva Jana Hitaya, Sarva Jana Sukhaya” (welfare for all, happiness for all), positioning capacity building as a global public good rather than competitive advantage.
Key Outcomes and Future Directions
The discussion revealed consensus on human-centric AI governance, capacity building importance, and international collaboration value, while acknowledging significant implementation challenges. Key unresolved issues include operationalizing the alliance, addressing the 75% of AI implementers lacking ethical framework understanding, and balancing urgent adoption needs with proper evaluation.
The session established that effective AI governance requires technical capacity, fundamental system redesign, global coordination, and unwavering focus on human values. The Digital Capacity Building Alliance represents an ambitious attempt to address these challenges through collaborative, inclusive approaches that maintain human-centric principles while harnessing AI’s transformative potential for public good.
Session transcript
and partnerships from the Capacity Building Commission to deliver welcome remarks. Good afternoon. Thank you, Mustafa. A very good afternoon to all of you, distinguished guests, panelists, fellow participants, colleagues from Karni Yogi Bharat and Capacity Building Commission, and a warm welcome to everyone. Technology, they say, is a great leveler, and AI, they say, is the next big thing after electricity. We as individuals are part of society as individuals and a dual role of individuals. And we are deeply impacted by these two to an extent that we cannot distinguish between these two anymore. As the popular Bollywood line says, Mayor Mary Panhai is actually me. And my AI, in certain context. This room carries the huge responsibility of making that distinction happen.
Responsibility is to carve out trust -based collaborative ethical frameworks so that the demands of fast -paced dynamic AI -DPD age, which constantly creates push -up demands for faster, better, safer public services, is met by a well -informed design and delivery model. Today we gather here as a first step, aligned with the India AI Impact Summit theme, AI for economic development, social good, safe and trusted AI, and human capital. The need for collective discourse at the policy level is crucial, whenever to harness equitable benefits, mitigate risks, and to ensure an inclusive governance transformation. To carry this foundation forward, we have our distinguished panelists, we have our chairperson, and we look forward to the next session. Thank you for listening today.
Welcome, everyone.
Thank you, Dr. Washima. I now invite our Chairperson of the Capacity Building Commission, Shubhavi S. Radha Chauhan, to deliver the opening address.
Thank you. Thank you, Mr. Sir. Namaskar. It’s my privilege to extend a very warm welcome to all of you on behalf of Team Mission Karni Yogi. And I must disclose that this speech that I’m going to read out is handcrafted. No AI in the process has been used. Yes, absolutely. Be compliant. Our Honorable PM yesterday outlined Mani Vision, a human -centric framework for ethical, accountable and inclusive AI governance. Mission Panayogi has and shall continue to relentlessly craft and embed these wish capabilities that will translate this vision into reality. Every service today must evolve at a pace, hitherto untraceable. It must learn continuously, develop deep competencies and dynamically adapt to eternally emerging work and workspaces. Underprivileged competency and skill is a humanistic capacity, that non -negotiable layer of intellect, diligence and values that has to flavor every decision made and every service delivered by governments and its systems.
From the community health worker delivering nutrition to an expecting mother to the balancing worker strategizing access to specialized healthcare. It is the quality of this human layer that will ultimately define the quality of service we deliver to our citizens. The future of AI, more precisely the agentic AIs, will not be in massive monolithic models. It will be in small language models, context -specific, sectoral, and decentralized. This would entail creating the customized, sector -specific competency framework that can suitably deploy AI agents to arrive at decision points that solve local needs and problems in its context. Capacity building must therefore focus on enabling our officials to deconstruct complexities, impose appropriate guardrails on data and its use, before evaluation benchmarks.
before using the authentic insights to taking decisions. In the past year, the Commission has developed holistic policy frameworks that have been tested and institutionalized, established operational guidelines, especially those for identifying competency gaps, leading to personalized learning pathways for each one of our learners. Dynamic governance models have evolved for stakeholders, especially our training institutions, ensuring they remain agile and responsive to competency demands. Continuous learner feedback loops, rigorously analyzed, have become integral to refining and strengthening the system. We are at the community portal’s times today as a testament to this remarkable trajectory. It has developed teamwork capacities effectively, at scale, and across the human race, to achieve this diversity of India’s governance ecosystem. It is in the context of this evolving journey that we see today’s event as an opportunity to take the plea, grounded in deep faith, that Mission for New Delhi, as a public good, must inform every other government that is on a similar and seminal mission to deliver inclusive, ethical and impactful public services.
I sincerely hope that this deliberation here produces a cohesive and common pathway for all of us to enter upon as global partners. Thank you so much.
Thank you so much, ma ‘am, for placing the panel through the address, placing everything into the context for the panel discussion. Thank you, Mr. Frager, and the remaining proceedings of the evening. Now I take your immediate pleasure in inviting your panelists for today’s discussion and also more later Mr. Professor Amogarai sir May I kindly request Professor Amogarai sir to join us on the rise The last panel discussion will be moderated by Mr. S. Amogarai Chairperson of Karni Nagi Bharat and former M.D. and CEO of Tata Consultancy Services Mr. Amogarai is of a specialty at the intersection of technology engineering and technology governments and institutions and he has worked at key institutions across academia, industry and public policy institutions including as advisor to the R.W .P.
Minister in the National Council on Scale Development We welcome you sir On the panel, we are joined by Guilherme Albusco Almeida from Brazil, a senior consultant at the Institute of Management and Corporation in Public Services, Government of Brazil, working at the intersection of government reform and digital transformation. Anil Shivastava, Chief Architect for Goodwill’s work in the public sector. He currently leads the Public Policy Strategic AI Solution Engagements of Global Cloud in India. And our final panelist for today, Robin Scott. She is the co -founder and CEO of A Political Network, a global online network of public servants. Thank you so much for joining us and taking time out for this session. With this, I hand it
Thank you. So, the mic’s there. Two minutes. Then I’ll say the second. No good answers. You got nothing to do. Before I begin, I want to extend a very warm welcome to the panelists. Thank you so much for agreeing to be a part of this. It will be a learning experience even for me, for sure. After spending over five decades in the technology industry, I’m probably the oldest here. It puts me with immense hope to sit alongside a group of young leaders who are shaping the next chapter of this global technology revolution. Thank you for being here and for looking forward to the exchange. If we look back at past technological revolutions, we rarely talk about the technologies themselves.
Instead, we talk about what they enable. Electricity is not celebrated because we built our plants. It is celebrated because we brought a revolutionary transformation into the world. It is a transformation to the quality of life. AI presences in the Sumedha moment. It gives us unprecedented power not to do things better but to do better things. We think how we explore, educate, govern, create, collaborate, heal and protect the people and the planet most importantly. But the most important question for this summit is not how far we can scale AI but how we can recognize it’s a movement in a direction that elevates humanity. Sometime ago I read an article titled Bridges as Humanity’s Greatest Legacy. It has spoken about the universalization instinct and how it has long leaned towards coexistence, cooperation and balance including.
shared progress. From Rupesh Mahatma Gandhi, India has consistently attempted to build robust and promote peace and harmony across the world. We are entering the era at a time when capitalism is increasingly intertwined with geopolitics and, of course, conflict. That reality demands deep reflection because the choices we make today will determine whether here becomes a nuclear race of the 21st century or the space race that will take humanity to the moon. Globally, AI is framed as a binary race, a market led by experimentation in the United States, versus state -led techno -nationalism in China. However, it might lend India offers a third way, in partnership, of course. For over five decades, India’s IT industry has built trust, reliability, and delivery capabilities across the world.
We know we have 5 .8 million professionals. This legacy gives India any strength to deploy technology safely and, of course, responsibly at every stage of the technology industry. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals. We know we have 5 .8 million professionals.
We know we have 5 .8 million professionals. For example, the Tata AI Saki Immersion Programme is empowering rural women artists to use AI as a tool for livelihood opportunity. India’s AI journey is also interested in the digital public infrastructure, which includes RADAR, identity payments, UPI, documents, digital locker and consent framework, the data empowerment and protection architecture, or DUPI as it is called, at a scale. These are not really platforms, they are trust architectures. The next billion AI users may not interact with 3D and parameter models. They may interact with tiny embedded AI in phones, tractors, classrooms, clinics and local government systems. India’s rural opportunity lies in small language models that are absolutely domain specific and can run on edge devices, operate in rural cities, overseas environments, solve real problems.
But I would not squadron of these children going through. of the exhibitions, exhibits. As artificial intelligence becomes an embedded across public administration, the challenge for governance is not limited to technology or adoption. It extends to ensuring that public officials understand how the systems function, what their limitations lie and how human judgment responsibly and ethical consideration must guide this use. Vishen Karvayogi has established a model demonstrating that systemic technology -enabled civil services reform is achievable across diverse administrative contexts. Building on this institutional foundation, the next horizon is to embed AI within workforce transformation frameworks while contributing to the shaping of global norms on responsible AI in governance. In this context, the Summit Master launched a blueprint for digital capacity building and labs that sets out the share of fair work for developing AI and everything public could for public officials’ capacity.
Let us take this convention forward to see how the proposed alliance can be operationalized and diverse partners can work together to translate the blueprint into sustainable actions. I’ll turn over to the questions. For each of the panelists, I’ve got a couple of questions, but I’ll just start with one or two to each of you. And they’re slightly different for each, and none of them have been generated by, again, a disclosure. So let me start with that little shivastava, Google Cloud. Google is at the forefront of building global digital infrastructure and in many ways adoption across enterprises and public services. The question is, governments often adopt new technologies in fragmented ways. What technical and operational risks arise when any systems are layered onto the legacy infrastructure?
without structural reform, how can initiatives like Mission Community help align infrastructure modernization with workforce capability development? Before I ask you the next question, please.
So, first of all, thank you. Thank you so much. I’m honored to be here at Bharat Mandapam as part of the panel of esteemed experts. And we are talking about capacity building imperative for Vixit Parth 2047. You know, I think the question that, sir, as we said, is a very important question when we are in the journey of using AI in our day -to -day lives. And specifically, you know, governments, and especially Government of India, has a huge focus of using AI to improve the quality of life for the people of the world. And I think that’s a very important question. for making the lives of our citizens easier? And also the government, civil servants, you know, lives will be much, much easier than the work that they do today.
The kind of efforts that goes into Reni Server delivering citizen services, is there a way that we could actually leverage AI in Reni Server solving for that? Now to sir’s question, I think the key, it is a very important point that AI is not, you know, a layer that you could just put on existing systems. You know, the systems, the IT systems that were developed with the objective of solving specific problems. Please hear me out. Sure. Right. So, you know, the existing IT systems are very centric and they were built with the view to solve a specific problem for the kind of technology that we had at that time. With AI, we are sort of looking to change the way the humans interact with the AI systems.
The existing systems, they actually have silos of data, silos of business logic, whereas AI, as we sort of look at this as more holistically, you need to really have a contextual data for you to train models to make it useful for you. And so we need to really sort of look at reengineering some of our existing IT systems so that it can harness the potential of AI in solutions. And so that’s where we’re solving some of the problems. So that is one point of view. The other is to really sort of prepare data so that we can train models, whether it is the LLMs or the SLMs, whether it is at the edge that we would actually have AI in a small device, a mobile device.
ASHA worker could actually sort of go and can deliver services using AI in their own native language. So, you know, we need to ensure that we support the multilinguality, the in -depth languages to deliver on those services. Now, to build those systems, we really need to not only change the technology, the underlying technology, but also the process that needs to be re -engineered. So that is one aspect that we should think about. Also from a security perspective and data sovereignty perspective, we need to sort of re -look at the… the exposure that AI brings to our existing systems, the kind of vectors that we are, you know, the systems have been built today, we will need to have to re -look at it.
Some of the, you know, vectors or some of the issues that we have today needs to be resolved. So that would be my perspective, sir. Thank you.
Guy, he told me it’s very easy to remember his name because Guy is a new word also.
Yes.
How can countries like Brazil and India collaborate more closely in shaping the global conversation around care, trust, and alignment in AI? What do you think are the areas we can collaborate together which will have the greatest global impact as AI becomes more autonomous and more deeply embedded in society?
Well, that’s a fantastic question. I will try to bring some aspects of that, but I think we’ll keep answering that until at least 2047. But the point is, first, I think Brazil and India are really close and can collaborate a lot. I can testify that because it’s my fifth trip to India. We’ve been exchanging a lot technology -wise. When it relates to AI, I think we should consider different aspects. We just mentioned here data and data for training models, but I think there’s strong room for collaboration when you talk about R &D, right? Because there’s not only similarities but also complementarities. There are things that are complementary to one another. So I guess that there’s strong room for cooperation and collaboration.
But also in capacity building. I understand that I’m a great fan of Mission Kama Yogi and the Capacity Building Commission. We have similar organizations in Brazil. We have been training civil servants as well through an electronic and an online platform. And I believe that digital infrastructure approach to capacity building is also a way to bring this to more people to make this scalable in a way that we can actually change build knowledge build capacities and make things change within government. Of course we need to be careful about the risks of AI. In Brazil we have developed a framework for ethical assessment of AI implementation. We have also provided some guides explaining not only how AI works, but what caution should you have when you’re using AI within the public service?
Of course, we should consider boundaries and safeguards in AI implementation, but we should not prevent from using it for the betterment of people’s lives and to enhance our population. And I think that training and capacity building is crucial for that. In Brazil, we have at least four different profiles for capacity building, one for senior leaders, one for IT managers, one for data curators, and the other for general civil servants, in which we organize the knowledge you’re supposed to develop and to build in order to use AI properly and to build AI solutions. and I guess going back to the Brazil -India connection I guess both nations are well positioned to I would say lead but to conduct this conversation in a global perspective I think that we have great partnerships with Apolitical as well I’ve been working a lot with them and I think that coalition of willing organizations building knowledge for AI in public service is something that could be built and if you can bring a South -South flavor to that I think we’re better positioned to provide the transition we want to the government and to the world.
Thank you.
Robin you work with governments around the world what are the biggest gaps you see in AI readiness within public institutions? I think that how can we shift the global conversation towards work reinvention?
Thank you so much. That’s a big question. It is such an honor to be here. And this seating arrangement is particularly meaningful to me because we’re not only honored to partner with the Capacity Building Commission and Mission Kamiyagi, but we are longstanding partners of ENAP, the excellent Brazilian school of government. And Google .org has funded us to provide world -class training for free on AI to a million public servants, and we’re 400 ,000 into that goal, including in India. So this particular configuration is very meaningful. And I also want to say something about Brazil and India, which I think links the two nations. In our experience working with them, they both understand that capacity building is not something that should be pushed to the side.
It is an afterthought. It is an engine of innovation. ENAP has an innovation unit within its school, and it is strategic. and especially with AI, it’s more strategic because you don’t get intelligent technology unless you have people intelligently supported to work alongside and in partnership with that technology. So I really appreciate the ambition and vision that both countries bring to capacity building. I’ll point to just a couple of gaps. One is around ethical frameworks. You mentioned Brazil has one. Most countries have one. According to our data, this is an 8 ,000 -person global survey. Of those people implementing AI in their governments, these are people whose job it is to roll out the technology, only 26 % say they understand their own government’s ethical frameworks.
So in other words, 75 % are freestyling, and that builds a great deal of risk into the system. We also have a gap between talk and ambition and evaluation. So when you talk to leaders, 72 % say they have a pilot or will have one this year, but only 45 % of them say they have a plan to evaluate the performance of that pilot. And there is no point piloting something without evaluation. There is a lot more to say, but I just want to end on a note of optimism. Well over 90 % of public servants are very optimistic about the role that AI can play. And there’s a $1 .75 trillion productivity prize for getting this right, according to BCG.
So we’ve got the optimism, we’ve got the energy, and these gaps are big, but they’re not impossible to close. Thank you.
Just one final question, if you can answer. As we expand AI -centric capacity building, scaling digital platforms, increasing compute and embedding AI into public systems, all of us agree we must also confront the environmental footprint of these technologies. How can governments and AI companies work? How can governments and AI companies work together to ensure that the AI -driven public infrastructure is also aligned with climate responsibility? energy efficiency and sustainable growth. Anyone else? We can all agree with each other or confidently.
Well, I can just offer, we have developed a course on AI and climate and understanding the links with the Stanford Doerr School of Sustainability. So we literally have a program to answer your question. I’ll leave it. But it has too much money.
Well, I think there are two separate ways in which it could be framed. There’s AI for green and green AI. So aiming for sustainability on the power you provide for the GPUs and so on is crucial. But also we could use AI to leverage the potential of climate policies. If you put together data, meteorological data, data from forests and so on, you can bring intelligence and knowledge, which could lead to better informed decisions. In Brazil, we have a system in which we mapped all the forests in private lands. It’s the Rural Environmental Registry. And we’re using AI to understand whether forests have been cut down or not. So we can use different AI tools to promote not only fighting deforestation, but also promoting reforestation.
So there are several different potential tools, and they could be used. And if we can blend them together, we can make even more.
So I would actually say that, you know, Google, first of all, has committed that by 2030, all our data centers will be carbon neutral. And we want to make sure that we want to partner with the government of India to ensure that all the data centers that we are building in the country should have some sort of targets to ensure that they are carbon neutral. Thank you. and there are, you know, designed from a civil perspective but from a technology perspective, we can always build models which are energy efficient. So I would actually leave it at that but I think that’s a very important point for India as a country. Thank you.
Any one question from the audience? Go ahead. Oh, it doesn’t work? Somebody gave you the mic. But you should add ladies first. I don’t know why you… Go ahead, go ahead. Sorry.
and just take a metric of doomsday clock that was just received on 27th January at 85 seconds to midnight. Now, just simply translate that in a thousand mile downhill journey, an overloaded truck with weapons of mass destruction that aptly disperse our civilization today. We are at 80 meters to the edge of the precipice. You know, that dangerous. We are being so cannibalistic of the future of our children. My question is, should we see Bharat by 2047? It is actually procrastination of our responsibilities. We just don’t want to own up what’s happening today.
I agree, yeah.
So they have to come as a concert of civilizations by 2026. Go ahead, go ahead, sorry. Chairman, in three precedents of the Federation, I will just take a metric of doomsday clock that was just received on 27th January at 85 seconds to midnight. Now, just simply translate that in a thousand mile downhill journey, an overloaded truck with weapons of mass destruction that aptly disperse our civilization today. We are at 80 meters to the edge of the precipice. You know, that dangerous. We are being so cannibalistic of the future for children. Should Vixen Bharat, my question is, should Vixen Bharat by 2047, which is actually procrastination of our responsibilities, which I don’t want to own up, what’s happening today, and what happened to India, should they have to come as a concert of civilizations that by 2026 itself, right here, right now?
I think confrontation starts very early and a lot of activities are happening in the country 2047 is a dream extraordinary year of our independence what we need to achieve is a roadmap that’s what is important rather than saying nothing is happening and suddenly something will happen in 2047
one more question here last question please thank you
I’m professor Charu from Indian Institute of Public Administration we met some of you thanks in regards to the audience my question is with regard to a consolidated international lack of availability of frameworks in terms of AI procurement guidelines in terms of AI ethical frameworks in terms of competence frameworks we do have UNESCO competence framework for AI but we need to hyper localize it to context which Robin and I were talking in terms of various countries in another event so maybe we need to have something a more generic collaborative international AI impact framework assessment tool which could look into capabilities not just at the digital leadership level but across the whole organization or country thanks a lot
thank you any comment it was right okay thank you so much honorable minister thank you to all the panelists and participants we are also now joined by honorable minister Dr. Jitendra Singh sir minister of state for personnel minister of state for personal grievances and pensions a visionary leader who has been at the forefront of administrative reforms and India’s science and innovation agenda sir it’s a pleasure to have you with us . Thank you. Thank you so much, Mr. Minister, for joining us and taking time out of your busy schedule. What was just witnessed in the form of a panel discussion is a small reflection of what the Capacity Building Commission and Karnal Yogi Bharat are hoping to achieve through what we seek to announce today.
May I now request all of you, Mr. Minister, to kindly launch the building for holding a musical capacity building alliance by pressing the button
And to govern at this scale, this space, we need an ever -evolving system. So India built one. In 2020, our leader, Prime Minister Srinivasa Modi launched Mission Kalmaragi to build a future -ready citizen -centred civil services. At the heart of it, the capacity -building commission. The living capability with foundations of trust, empathy and inclusion. Part of this is our great Kalmaragi platform, India’s national digital learning platform, accessible anytime, anywhere. And now, the next two. AI -enabled governments, personalized learning paths, smart decision support, from reactive systems to adaptive capacity model. To both, all governments, especially in the global south, face the same challenge. Demand -driven and technology -destructive. Complex workflows. Move for Agile Institutional Capacity. India has a working model of unscannable cruising, a global public good.
Today, the Capacity Building Commission unveiled a proposal to forge Digital Capacity Building Allowance, an allowance that fuses global AI principles, digital public good standards, and the mission -cum -worthy model. A unique model for demand, design, delivery, and continued evolution. It wants in the mission to build a shape, non -proprietary foundation for capacity building across nations. This alliance aims to bring together a capacity building, a global funding, to drive policy design and standards, industry, to build digital commons and specialized solutions, academia, for the network of knowledge, research, and innovation. Civil Society, the champion systemic equity. and ethical accountability. DPG Partners, to orchestrate ecosystem for spirit impact, startups, to catalyze solutions and co -creation. Steered by the Capacity Building Commission and Karmayavi Bharat of Government of India, a global public good for inclusive, ethical, capacity building.
In the spirit of Selvajan Hithai, Selvajan Siddhai, Velsa for One, Happiness for One.
Thank you so much, sir, for launching the blueprint. May I kindly request Honourable Minister Sir and all the dignitaries on the desk to stand for photographs. Thank you. Thank you. Thank you, sir. May I invite Honourable Minister Sir to the podium to deliver the keynote address for the afternoon. Thank you.
Of course, you saw how it concluded and Dr. Ramadurai was giving the perspective of how does AI and its use payment for the public services, what are the challenges by way of capacity building. the learnings that we have had under Mission Karni Yogi, how valuable are they going to be to inform this whole journey that all the global partners, global governments, stakeholders are going to further take their steps towards. And the summit has seen the Honorable Prime Minister and the vision by Ruf Mano that he explained yesterday, which is totally bringing in the level of the need and importance of having a human -centric approach, the hands of the human in every decision that is being made that will impact citizens in every which way.
So I think the world capacity building is looking at that capacity and capability that we need to put in the hands of every public servant from the secretary at the policy level to the community level frontline worker. How do they use, navigate and… building the intellect that is needed to make the correct, ethical, modern value -based decisions when it’s going to impact the humankind in general. I think we have had a lot of fruitful insights from our partners, the panelists. And so this is almost a culmination of a long month, months that we have spent in discussing these issues with our stakeholders, whether it’s from the industry, the partners, our service providers, academia, startups. We were able to bring all of them together today.
And the document that has been unveiled by the minister just now is bringing all of those learnings and insights together to call for action in all of us who are working as experts in our fields to come together. collaborate, strengthen each other’s hands and responsibilities to forge that pathway with the human centricity that is required in handling the capacities that we have given to our baby, which is the alien and augmented intelligence. I think, sir, that is where your keynote now would give us the further needed guidance that you think at the political leadership level, how do they view the whole capacity building space? And like Robin said, this is very important that oft sidelined sector of public governance, but now we have the opportunity of bringing it center stage.
I don’t think we should lose this opportunity to take the leap with utter faith. Thank you, sir. Thank you.
thank you for reminding me that you needed my guidance. And more than me, reminding all the women in the room that they have to listen to my guidance. But I know you have already done enough of that task. But thanks for your kind words and trying to encourage me to stand before this program. Now we are simultaneously talking about two, three things this afternoon. We are talking about governance, we are talking about capacity building, and we are also trying to bring in an artificial intelligence interface, which of course, in any case, we like it or not, we don’t have to do it, it’s all good. You know, we fear of life in every domain that we work in.
Now governance, if you take, governance is a dynamic process, like many other processes in every domain that we are engaged in. So also is capacity building. It’s dynamic. It’s continuous, doesn’t it? And the time would be such a fast track movement that by the time you bare yourself tomorrow, when tomorrow happens you realize that you were only to worry about yesterday. And then upon that, the artificial intelligence. And the role of both in capacity building as well as in governance. And you talk in the context of India today, when you talk of a framework which invocates the best of all the three, I think the most encouraging feature is that we have a government in place, a political dispensation in place, which is supportive of all these ideas and all these initiatives.
Till about maybe 15 years back, we wouldn’t have ever thought of a theme like this gaining priority in an economy. We would have never thought of a dynamic room of this nature. And therefore, this is a dispensation of the Prime Minister Modi, which is not only ready for futuristic ideas and initiatives, but also for future -ready ideas. And that means, while it looks very fanciful, romantic, talking about artificial intelligence, even if a grocer shop puts on a banner outside, they hear my items are sold through AI, I’m sure he’ll at least be able to attract some number of customers. So that’s a new nature. But at the same time, being unrealistic and pragmatic, and Mrs. Radha had also been secretly DOP’d before she took over her present assignment, we are also free to shed away some of the old baggage.
So while we are running into what is new, we should also… We also have the capacity, and we should be non -possessive enough to unbend something which goes to our chest for so many years. And I’m proud to say that in the last one decade, this government has done away with almost 2 ,000 rules. And that sin has not been committed alone by me. Madam Radha is me equally. Kirti Ardhan. And let’s recall, many of the rules were designed for the times that they were designed. They didn’t have thought of artificial intelligence about 100 years back. They were having rules which were haunting us for more than a century. Getting our certificates, documents attested by the economy before.
We didn’t even know that. We have our means. And we also have now means to trust each other. So at the same time, also we have opened up to learn the new practices. And to also, while learning new practices, to be able to learn new practices. So very capacity. Two building, commission sitting with the governors. because when you learn the practices, you must also learn to bring capacity to learn. So artificial intelligence, the basic mantra is to learn to be a good learner. And if you have not learned, then to learn to be a good learner. And capacity building condition is one instrument which helps you do that. And this also was the idea which first came from Dr. Moti.
I think quite a novel idea for a government sector because usually governments are used to work in a status quo mode. So we have a flow of a private sector. Bandhu is there, and here we have Agam there. Because now we have also got over the barriers of private and public sectors. Unless we learn to learn from each other and also give up our sceptical, we will not be actually building up capacity to the optimum. We will be building up capacities which are limited by certain barriers. And that will not be an unbridled learning. So, capacity building commission was there, mission current lobby was being talked about, was also there, creation, IE God, and all these are testament to the governance reforms being accomplished through optimum technologies.
Now, this lies, which is being lodged. Now, when we talk of digital public good, fortunately or unfortunately, I am one of the few who are from the school of science and business. So, if you take out the first word, digital, and just concentrate on public good, you will realize that non -governance is synonymous with public good. So, public good, essentially, would be at the core of the good governance. It is just that now it is started using digital means, so it is fanciful. I am known because now we are adding to the age of human epitome. So we say DPG. So now we are adding DPG. But to a hardcore old fashioned scientist student, if you ask me, I would say nothing.
It is just the same. Good governments, family good. I am just going to write how the day one has been, because I think the Prime Minister himself, one of the earliest declaration was, maximum or minimum government, which another word means, a government which is citizen centric, which is accountable as far as possible, which is transparent, and the ultimate human stress effort is to bring in ease of living. So all that DPG was happening earlier, only the announcement is being made today. Now we see that there are kind of events now. I think the Prachinidhi Commission developed appreciation because they were very independent. They were very much instrumental in taking us when they got these. frameworks.
And I must also congratulate Madam Radha and her team for this launch of digital capacity building allies. But the idea is, yes, even perhaps. But the guiding principle ultimately all of us would agree would be to build at a scale which is optimally inclusive to give as much inclusion as possible and these are others to learn and also to adopt. Otherwise the very purpose of the allies would not have been achieved. And therefore for that purpose artificial intelligence could be a powerful tool. But certainly not around itself. Now the same ministry would be already using it from the experience of the world where the optimum mix is something which is why would I put in a silver at this audience human record of AI plus HIV artificial intelligence plus human intelligence and we learned that in a hard way while being under the CP grams we are feeling very proud that our disposal weight of legions has increased to more than 95 % almost 100 % per week sometimes but everybody went back to the long phase so I told him then secondly we answered greenness disposal 100 % happiness disposal 0 % when we looked back and said I said no that’s something you call happiness index being discussed in the West so we actually had to introduce a human desk over there because everything was happening all night AI and the control would come before you expected it so that the person would end up saying, so somebody there to construct, so that kind of, so I think that hybrid model is something which is ultimately going to be effective in my own means.
As far as I’m concerned, the morning I was listening to the IMF chief, she said India’s progress in the AI initiative is phenomenal. So I think we have already received recognition from the global judges of global benchmarks. But that’s the part what is suited to our conditions. Because a country bar sitting in Gaurav may not be used to talking. We are not used to talking. For example, another example of hybrid model I will give, we have, I think I’m going to leave, who has the voluntary clinic in my constituency. and there were two doctors one was surgically sitting there the other was an AI doctor she is a lady then they take the history they do it right do all the assessment connect it to one of the leading hospitals you are planning 3 -4 of them connect to the super specialist there I know where the prescription is published just about 40 -50 minutes it’s a very new creative health startup now but of course we are not in the school of therapy so when the patient comes the physical doctor talks to him and he feels more gratified than the AI doctor talks to him but she talks exactly the same dialect or better than what he talks so now he speaks Bhojpuri she would speak better Bhojpuri so the debate is over and I am not talking without the udders because in medical partners we have something called placebo effect and Indians are very used to placebo effect you should get the placebo effect if you don’t get well if you don’t get well what should I do?
So you have such a whole new world to question. So it may be bad in government context. So as they say, Indian data, Indian solutions, Indian systems are important. So we need to have a very much digitalized vehicle. Maybe other nations or cultivators may not require that, but we will always be driving it. And I think with this alliance, the Peter model that Radha has suggested, we would be able to engage more in valuation than by preparing this draft chapter with the content standard and the evaluation framework that is required. But in the end, I will just pick up on what she said, the Manav part of it, which the Prime Minister spoke yesterday. Now, how many in this room actually, I mean, have been able to decipher what was meant by that Manav?
not a single hand has gone across hospitals so I think before you leave this room if you have a iPad or a notebook, you can say it out M stands for moral and ethical systems A stands for accountable governance N stands for national sovereignty and second A stands for accessible and inclusivity and finally A stands for validity and legitimacy now when we don’t have the capacity to learn the term, we have the capacity to learn the acronyms and very soon the artificial intelligence will take up this much capacity also we need to be present we need to be present what is the amount of the other day when I was watching this large -length model and we were going to send the language back to the Zohar.
So I said, no need. But along with that, we have also buried that beautiful breed of English that we had in the early age of mission. We can’t see people who know more than five languages, because we know them more than six languages, so many of them. Now we are at the risk of even forgetting our own language. We have someone else to do it for us. So that’s the why, in the end, I think the two years, because what I’ve done, I’ve been into this AI business quite deeply. For the last, it was half a decade, I’ve been trying it in different fields. So ultimately, I think the moral which I draw from myself, because these people can’t be enjoying for others because we have to learn for themselves, is that one has to be intelligent enough to use artificial intelligence.
Otherwise, you don’t get into this business. And we are which is I think the tagline also for some of the media persons which they are there. Artificial intelligence can substitute everything on this planet but it cannot substitute integrity. Now whatever you do the other day the law in this study was writing two days back somebody said now you will be able to get rid of these people it is like this is happening I said no because the doctor is sitting thousands of kilometers away doing an ultrasound on a lady who is thousands of kilometers away so you would not be able to actually do any I said now if I am a doctor and I am smart enough I will then be percentage to my brother’s side when the media peers who have to do the sex determination just sound around me and do that.
So that is integrity. So I think I think that is the most important thing if we are not able to use this with integrity we might run the risk of ending up also not putting to active use so much of other government’s models that came to us but got ruined away not because of reasons attributable to them but the reasons attributable to more of us who had been assigned to handle them. Thank you very much.
Thank you so much sir for that insightful address and laying emphasis on the need for integrity which is only possible through the idea of having human in the loop something which also finds mention in the blueprint that we have just launched. with this we come to the conclusion of the event I extend my heartfelt gratitude on behalf of capacity building commission and Karmel Kiwara thank you so much Honourable Minister Sir dignitaries on the rise and all those present here thank you so much I now request the panellists also to just stay back for a quick minute for a photograph with Honourable Minister Sir and the dignitaries on the rise also all present I would like to take this opportunity to invite you to motion Karmel Kiwara in all the five thank you again Sir please thank you so much thank you thank you
Dr. Washima
Speech speed
122 words per minute
Speech length
251 words
Speech time
122 seconds
Trust‑based collaborative ethical frameworks
Explanation
Dr. Washima stresses that AI deployment must be underpinned by trust‑based collaborative ethical frameworks to ensure fast‑paced AI services are safe, inclusive and well‑designed. This framing sets the foundation for responsible AI governance.
Evidence
“Responsibility is to carve out trust‑based collaborative ethical frameworks so that the demands of fast‑paced dynamic AI‑DPD age, which constantly creates push‑up demands for faster, better, safer public services, is met by a well‑informed design and delivery model.” [1]. “Today we gather here as a first step, aligned with the India AI Impact Summit theme, AI for economic development, social good, safe and trusted AI, and human capital.” [9].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Human rights and the ethical dimensions of the information society
Moderator
Speech speed
96 words per minute
Speech length
632 words
Speech time
393 seconds
Urgency of integrity and human‑in‑the‑loop
Explanation
The Moderator highlights that the panel’s framing underscores the urgent need for integrity in AI systems, achievable only through a human‑in‑the‑loop approach, which is central to the summit’s blueprint.
Evidence
“Thank you so much sir for that insightful address and laying emphasis on the need for integrity which is only possible through the idea of having human in the loop something which also finds mention in the blueprint that we have just launched.” [11]. “What was just witnessed in the form of a panel discussion is a small reflection of what the Capacity Building Commission and Karnal Yogi Bharat are hoping to achieve through what we seek to announce today.” [96].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Capacity development
Shubhavi S. Radha Chauhan
Speech speed
115 words per minute
Speech length
886 words
Speech time
460 seconds
Human‑centric AI vision with sector‑specific small language models
Explanation
Chauhan outlines the Prime Minister’s human‑centric AI vision, calling for customized, sector‑specific competency frameworks and small, context‑specific language models that can be deployed locally to solve community problems.
Evidence
“Our Honorable PM yesterday outlined Mani Vision, a human‑centric framework for ethical, accountable and inclusive AI governance.” [7]. “This would entail creating the customized, sector‑specific competency framework that can suitably deploy AI agents to arrive at decision points that solve local needs and problems in its context.” [10]. “It will be in small language models, context‑specific, sectoral, and decentralized.” [16].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Capacity development
Human‑in‑the‑loop as a core principle
Explanation
Chauhan reiterates that every AI decision must retain human oversight, reinforcing the ethical and inclusive nature of the government’s AI strategy.
Evidence
“And the summit has seen the Honorable Prime Minister and the vision by Ruf Mano that he explained yesterday, which is totally bringing in the level of the need and importance of having a human‑centric approach, the hands of the human in every decision that is being made that will impact citizens in every which way.” [25].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Human rights and the ethical dimensions of the information society
Subramanian Ramadorai
Speech speed
140 words per minute
Speech length
1223 words
Speech time
520 seconds
AI as a movement that elevates humanity and a “third way” partnership
Explanation
Ramadorai frames AI not merely as a technology but as a movement that must elevate humanity, calling for inclusive governance and a “third way” partnership model between nations and the private sector.
Evidence
“But the most important question for this summit is not how far we can scale AI but how we can recognize it’s a movement in a direction that elevates humanity.” [29]. “However, it might lend India offers a third way, in partnership, of course.” [30].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Human rights and the ethical dimensions of the information society
Environmental footprint of AI must be addressed
Explanation
Ramadorai stresses that as AI becomes embedded in public administration, its environmental impact must be considered alongside governance and capacity‑building efforts.
Evidence
“As we expand AI‑centric capacity building, scaling digital platforms, increasing compute and embedding AI into public systems, all of us agree we must also confront the environmental footprint of these technologies.” [33].
Major discussion point
Environmental Sustainability and Green AI
Topics
Environmental impacts | Artificial intelligence
Anil Shivastava
Speech speed
145 words per minute
Speech length
671 words
Speech time
275 seconds
Technical and operational challenges of layering AI onto legacy systems
Explanation
Shivastava argues that AI cannot simply be added as a layer on existing siloed IT; legacy systems need to be re‑engineered to provide contextual, multilingual data and to address security and process changes.
Evidence
“The existing systems, they actually have silos of data, silos of business logic, whereas AI, as we sort of look at this as more holistically, you need to really have a contextual data for you to train models to make it useful for you.” [22]. “And so we need to really sort of look at reengineering some of our existing IT systems so that it can harness the potential of AI in solutions.” [23]. “Now to sir’s question, I think the key, it is a very important point that AI is not, you know, a layer that you could just put on existing systems.” [36]. “Now, to build those systems, we really need to not only change the technology, the underlying technology, but also the process that needs to be re‑engineered.” [57].
Major discussion point
Technical and Operational Challenges of Integrating AI with Legacy Systems
Topics
Artificial intelligence | Building confidence and security in the use of ICTs
Commitment to carbon‑neutral data centres and energy‑efficient AI models
Explanation
Shivastava notes Google’s pledge to achieve carbon‑neutral data centres by 2030 and its focus on building energy‑efficient AI models, aligning AI development with climate goals.
Evidence
“Google, first of all, has committed that by 2030, all our data centers will be carbon neutral.” [86]. “And we want to make sure that we want to partner with the government of India to ensure that all the data centers that we are building in the country should have some sort of targets to ensure that they are carbon neutral.” [87]. “Also from a security perspective and data sovereignty perspective, we need to sort of re‑look at the… the exposure that AI brings to our existing systems, the kind of vectors that we are, you know, the systems have been built today, we will need to have to re‑look at it.” [58].
Major discussion point
Environmental Sustainability and Green AI
Topics
Environmental impacts | Artificial intelligence
Guilherme Albusco Almeida
Speech speed
121 words per minute
Speech length
613 words
Speech time
302 seconds
India–Brazil South‑South collaboration on AI R&D and capacity building
Explanation
Almeida highlights the complementary strengths of Brazil and India, proposing joint R&D, capacity‑building programmes and shared ethical assessment frameworks to lead global AI conversations.
Evidence
“But the point is, first, I think Brazil and India are really close and can collaborate a lot.” [62]. “In Brazil we have developed a framework for ethical assessment of AI implementation.” [3]. “We have at least four different profiles for capacity building, one for senior leaders, one for IT managers, one for data curators, and the other for general civil servants…” [63]. “I think the Brazil‑India connection… we have great partnerships with Apolitical… a South‑South flavor…” [34].
Major discussion point
International Collaboration on AI (India–Brazil and South‑South Partnerships)
Topics
Artificial intelligence | Capacity development | Enabling environment for digital development
Green AI and climate‑focused applications
Explanation
Almeida points out that AI can support climate policies, such as forest monitoring, and stresses the need for energy‑efficient models.
Evidence
“There’s AI for green and green AI.” [24]. “But also we could use AI to leverage the potential of climate policies.” [47]. “And we’re using AI to understand whether forests have been cut down or not.” [84]. “If you put together data, meteorological data, data from forests and so on, you can bring intelligence and knowledge, which could lead to better informed decisions.” [85].
Major discussion point
Environmental Sustainability and Green AI
Topics
Environmental impacts | Artificial intelligence
Robin Scott
Speech speed
150 words per minute
Speech length
452 words
Speech time
180 seconds
Gaps in AI readiness and ethical framework understanding
Explanation
Scott reveals that a large majority of public‑sector AI implementers lack knowledge of their own ethical guidelines and have no evaluation plans for pilots, creating significant risk.
Evidence
“Of those people implementing AI in their governments, these are people whose job it is to roll out the technology, only 26 % say they understand their own government’s ethical frameworks.” [38]. “So in other words, 75 % are freestyling, and that builds a great deal of risk into the system.” [76]. “So when you talk to leaders, 72 % say they have a pilot or will have one this year, but only 45 % of them say they have a plan to evaluate the performance of that pilot.” [75]. “We also have a gap between talk and ambition and evaluation.” [77].
Major discussion point
Gaps in AI Readiness within Public Institutions
Topics
Artificial intelligence | Capacity development | Human rights and the ethical dimensions of the information society
AI and climate education initiative
Explanation
Scott mentions a newly developed course linking AI with climate science, aiming to train public servants on sustainable AI practices.
Evidence
“Well, I can just offer, we have developed a course on AI and climate and understanding the links with the Stanford Doerr School of Sustainability.” [81].
Major discussion point
Environmental Sustainability and Green AI
Topics
Environmental impacts | Capacity development
Audience
Speech speed
144 words per minute
Speech length
364 words
Speech time
151 seconds
Need for a hyper‑localized international AI impact assessment tool
Explanation
An audience member proposes creating a generic, collaborative international AI impact assessment framework that is hyper‑localized to national contexts, complementing UNESCO’s competence framework.
Evidence
“I’m professor Charu from Indian Institute of Public Administration… we need to have something a more generic collaborative international AI impact framework assessment tool which could look into capabilities not just at the digital leadership level but across the whole organization or country thanks a lot” [6].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Enabling environment for digital development
Speaker 1
Speech speed
114 words per minute
Speech length
284 words
Speech time
149 seconds
Political leadership and Digital Capacity Building Alliance as a global public good
Explanation
Speaker 1 describes Mission Karni Yogi, the Kalmaragi platform, and the launch of the Digital Capacity Building Alliance, positioning them as a citizen‑centred, AI‑enabled public service model and a global public‑good initiative.
Evidence
“In 2020, our leader, Prime Minister Srinivasa Modi launched Mission Kalmaragi to build a future‑ready citizen‑centred civil services.” [92]. “Part of this is our great Kalmaragi platform, India’s national digital learning platform, accessible anytime, anywhere.” [93]. “Steered by the Capacity Building Commission and Karmayavi Bharat of Government of India, a global public good for inclusive, ethical, capacity building.” [70]. “The summit’s launch of the Digital Capacity Building Alliance formalizes a global public‑good model for inclusive AI capacity building.” [91].
Major discussion point
Political Leadership, Policy Vision, and Digital Public Good
Topics
Information and communication technologies for development | Capacity development | Artificial intelligence
Speaker 3
Speech speed
77 words per minute
Speech length
9 words
Speech time
6 seconds
Call for agile institutional capacity
Explanation
Speaker 3 emphasizes the need for agile institutional capacity to effectively adopt AI and digital technologies within government structures.
Evidence
“Move for Agile Institutional Capacity.” [54].
Major discussion point
Capacity Development and Institutional Reform
Topics
Capacity development | Enabling environment for digital development
Dr. Jitendra Singh
Speech speed
144 words per minute
Speech length
2236 words
Speech time
927 seconds
Integrity and MANAA framework as non‑negotiable for AI governance
Explanation
Dr. Singh introduces the MANAA acronym—Moral, Accountable, National, Accessible, Valid—as essential pillars for trustworthy AI, stressing that integrity cannot be compromised.
Evidence
“not a single hand has gone across hospitals so I think before you leave this room if you have a iPad or a notebook, you can say it out M stands for moral and ethical systems A stands for accountable governance N stands for national sovereignty and second A stands for accessible and inclusivity and finally A stands for validity and legitimacy…” [49]. “Artificial intelligence can substitute everything on this planet but it cannot substitute integrity.” [50]. “So that is integrity.” [52].
Major discussion point
AI Capacity Building and Ethical Governance
Topics
Artificial intelligence | Human rights and the ethical dimensions of the information society
Political support enables AI initiatives
Explanation
Dr. Singh notes that the current government’s reforms—removing outdated rules, embracing digital public goods, and promoting AI for public good—provide the political backing necessary for AI projects.
Evidence
“I think the most important thing if we are not able to use this with integrity we might run the risk of ending up also not putting to active use so much of other government’s models that we came to us but got ruined away not because of reasons attributable to them but the reasons attributable to more of us who had been assigned to handle them.” [41]. “So, capacity building commission was there, mission current lobby was being talked about, was also there, creation, IE God, and all these are testament to the governance reforms being accomplished through optimum technologies.” [55].
Major discussion point
Political Leadership, Policy Vision, and Digital Public Good
Topics
Information and communication technologies for development | Artificial intelligence
Agreements
Agreement points
Human-centric approach to AI governance
Speakers
– Dr. Washima
– Dr. Jitendra Singh
– Robin Scott
Arguments
AI should be human-centric with ethical, accountable and inclusive governance frameworks
Need for hybrid model combining artificial intelligence with human intelligence for effective governance
Capacity building should not be sidelined but treated as an engine of innovation that is strategic for intelligent technology implementation
Summary
All speakers emphasized that AI implementation must maintain human oversight, ethical considerations, and human-centered decision making rather than replacing human judgment entirely
Topics
Artificial intelligence | Human rights and the ethical dimensions of the information society
Importance of capacity building as strategic priority
Speakers
– Shubhavi S. Radha Chauhan
– Robin Scott
– Guilherme Albusco Almeida
Arguments
Capacity building must focus on enabling officials to deconstruct complexities and impose appropriate guardrails on data use
Capacity building should not be sidelined but treated as an engine of innovation that is strategic for intelligent technology implementation
Brazil and India can collaborate in R&D, capacity building, and shaping global AI conversation due to similarities and complementarities
Summary
Speakers agreed that capacity building is not a secondary concern but a central strategic element for successful AI implementation in government
Topics
Capacity development | Artificial intelligence
Need for small, context-specific AI models rather than large monolithic systems
Speakers
– Shubhavi S. Radha Chauhan
– Subramanian Ramadorai
Arguments
Future AI will be in small language models that are context-specific, sectoral, and decentralized rather than massive monolithic models
Next billion AI users may interact with small embedded AI in phones, tractors, classrooms, and local government systems
Summary
Both speakers advocated for decentralized, domain-specific AI solutions that can address local needs and operate on edge devices rather than relying on large centralized models
Topics
Artificial intelligence | Closing all digital divides
Environmental sustainability in AI development
Speakers
– Anil Shivastava
– Guilherme Albusco Almeida
Arguments
Google committed to carbon neutral data centers by 2030 and building energy-efficient models
Two approaches: AI for green (using AI for climate policies) and green AI (sustainable power for AI infrastructure)
Summary
Both speakers acknowledged the importance of addressing AI’s environmental impact through sustainable infrastructure and using AI for environmental monitoring and protection
Topics
Environmental impacts | Artificial intelligence
Trust architectures as foundation for AI implementation
Speakers
– Dr. Washima
– Subramanian Ramadorai
Arguments
Need for trust-based collaborative ethical frameworks to meet demands of AI-driven public services
These are not just platforms but trust architectures that can serve as foundation for AI implementation
Summary
Both speakers emphasized that successful AI deployment requires robust trust frameworks and collaborative approaches rather than just technical platforms
Topics
Building confidence and security in the use of ICTs | Artificial intelligence
Similar viewpoints
Both speakers recognized the critical importance of ethical frameworks for AI implementation in government, with Brazil providing a positive example while Robin highlighted the global gap in understanding such frameworks
Speakers
– Guilherme Albusco Almeida
– Robin Scott
Arguments
Brazil has developed framework for ethical assessment of AI implementation and guides for safe AI use in public service
Only 26% of AI implementers understand their government’s ethical frameworks, with 75% operating without proper guidance
Topics
Human rights and the ethical dimensions of the information society | Artificial intelligence
Both speakers emphasized the need for inclusive, personalized approaches that accommodate diverse linguistic and learning needs to ensure AI systems serve all users effectively
Speakers
– Anil Shivastava
– Shubhavi S. Radha Chauhan
Arguments
Systems must support multilinguality and native languages for frontline workers like ASHA workers
Need for personalized learning pathways and continuous learner feedback loops in capacity building systems
Topics
Closing all digital divides | Capacity development
Both speakers highlighted the Indian government’s successful modernization efforts, demonstrating that comprehensive administrative reform through technology is both necessary and achievable
Speakers
– Subramanian Ramadorai
– Dr. Jitendra Singh
Arguments
Mission Karmayogi demonstrates that systemic technology-enabled civil services reform is achievable across diverse contexts
Government has done away with almost 2,000 outdated rules while opening up to learn new practices
Topics
Social and economic development | The enabling environment for digital development
Unexpected consensus
Multi-stakeholder global collaboration approach
Speakers
– Guilherme Albusco Almeida
– Speaker 1
– Audience
Arguments
Both nations are well-positioned to lead global AI governance conversations with a South-South collaboration approach
Digital Capacity Building Alliance aims to bring together global partners including governments, industry, academia, and civil society
Need for consolidated international frameworks for AI procurement guidelines, ethical frameworks, and competency frameworks
Explanation
There was unexpected strong consensus on the need for comprehensive international collaboration involving diverse stakeholders, moving beyond traditional bilateral or regional approaches to include South-South cooperation and multi-sector partnerships
Topics
The enabling environment for digital development | Artificial intelligence
Integration challenges requiring system reengineering
Speakers
– Anil Shivastava
– Dr. Jitendra Singh
Arguments
AI cannot simply be layered onto existing legacy systems without structural reform and reengineering
Need for hybrid model combining artificial intelligence with human intelligence for effective governance
Explanation
Both technical and policy perspectives converged on the understanding that AI implementation requires fundamental system changes rather than simple additions, showing alignment between technical and governance viewpoints
Topics
Artificial intelligence | The enabling environment for digital development
Overall assessment
Summary
The speakers demonstrated strong consensus on key principles including human-centric AI governance, strategic importance of capacity building, need for decentralized AI solutions, environmental sustainability, and trust-based frameworks. There was also alignment on the challenges of AI integration and the importance of international collaboration.
Consensus level
High level of consensus with complementary perspectives rather than conflicting viewpoints. The agreement spans technical, policy, and implementation aspects, suggesting a mature understanding of AI governance challenges and a shared vision for solutions. This consensus provides a strong foundation for the Digital Capacity Building Alliance and indicates readiness for collaborative action on AI governance frameworks.
Differences
Different viewpoints
Approach to AI integration in existing systems
Speakers
– Anil Shivastava
– Dr. Jitendra Singh
Arguments
AI cannot simply be layered onto existing legacy systems without structural reform and reengineering
Digital public good is essentially the same as good governance, just using digital means
Summary
Shivastava emphasizes the need for fundamental system reengineering to integrate AI effectively, while Dr. Singh suggests that digital transformation is more about applying new tools to existing governance principles without necessarily requiring structural overhaul
Topics
Artificial intelligence | The enabling environment for digital development
Scale and complexity of required changes for AI implementation
Speakers
– Anil Shivastava
– Subramanian Ramadorai
Arguments
Existing IT systems have data silos and business logic silos, while AI requires contextual data for training models
Next billion AI users may interact with small embedded AI in phones, tractors, classrooms, and local government systems
Summary
Shivastava focuses on the complex infrastructure challenges requiring comprehensive data integration, while Ramadorai envisions a more distributed approach using small, embedded AI systems that may not require such extensive integration
Topics
Artificial intelligence | Information and communication technologies for development
Unexpected differences
Timeline and urgency for AI governance action
Speakers
– Audience
– Subramanian Ramadorai
Arguments
Need for consolidated international frameworks for AI procurement guidelines, ethical frameworks, and competency frameworks
India offers a third way in AI development focused on partnership rather than binary competition between US and China
Explanation
An audience member urgently called for immediate action by 2026 citing the ‘doomsday clock at 85 seconds to midnight’, while Ramadorai presented a more measured approach focused on India’s long-term strategic positioning. This disagreement on urgency versus strategic patience was unexpected given the general consensus on AI’s importance
Topics
Artificial intelligence | The enabling environment for digital development
Overall assessment
Summary
The discussion showed remarkable consensus on core principles of human-centric AI governance, ethical frameworks, and the importance of capacity building. Main disagreements centered on technical implementation approaches and the pace of required changes rather than fundamental goals
Disagreement level
Low to moderate disagreement level with high strategic alignment. The disagreements were primarily technical and methodological rather than philosophical, suggesting strong potential for collaborative implementation of the Digital Capacity Building Alliance despite different approaches to achieving shared objectives
Partial agreements
Partial agreements
Both agree on the importance of smaller, context-specific AI models, but Chauhan emphasizes sectoral customization and competency frameworks while Ramadorai focuses on embedded systems and edge devices for widespread accessibility
Speakers
– Shubhavi S. Radha Chauhan
– Subramanian Ramadorai
Arguments
Future AI will be in small language models that are context-specific, sectoral, and decentralized rather than massive monolithic models
Next billion AI users may interact with small embedded AI in phones, tractors, classrooms, and local government systems
Topics
Artificial intelligence | Closing all digital divides
Both recognize the critical importance of human oversight and ethical considerations in AI implementation, but Scott focuses on systemic gaps in framework understanding while Dr. Singh emphasizes the irreplaceable nature of human integrity
Speakers
– Robin Scott
– Dr. Jitendra Singh
Arguments
Only 26% of AI implementers understand their government’s ethical frameworks, with 75% operating without proper guidance
Artificial intelligence can substitute many things but cannot substitute integrity
Topics
Human rights and the ethical dimensions of the information society | Artificial intelligence
Both acknowledge the need to address environmental sustainability in AI, but Almeida presents a comprehensive dual framework while Shivastava focuses specifically on corporate commitments to infrastructure sustainability
Speakers
– Guilherme Albusco Almeida
– Anil Shivastava
Arguments
Two approaches: AI for green (using AI for climate policies) and green AI (sustainable power for AI infrastructure)
Google committed to carbon neutral data centers by 2030 and building energy-efficient models
Topics
Environmental impacts | Artificial intelligence
Similar viewpoints
Both speakers recognized the critical importance of ethical frameworks for AI implementation in government, with Brazil providing a positive example while Robin highlighted the global gap in understanding such frameworks
Speakers
– Guilherme Albusco Almeida
– Robin Scott
Arguments
Brazil has developed framework for ethical assessment of AI implementation and guides for safe AI use in public service
Only 26% of AI implementers understand their government’s ethical frameworks, with 75% operating without proper guidance
Topics
Human rights and the ethical dimensions of the information society | Artificial intelligence
Both speakers emphasized the need for inclusive, personalized approaches that accommodate diverse linguistic and learning needs to ensure AI systems serve all users effectively
Speakers
– Anil Shivastava
– Shubhavi S. Radha Chauhan
Arguments
Systems must support multilinguality and native languages for frontline workers like ASHA workers
Need for personalized learning pathways and continuous learner feedback loops in capacity building systems
Topics
Closing all digital divides | Capacity development
Both speakers highlighted the Indian government’s successful modernization efforts, demonstrating that comprehensive administrative reform through technology is both necessary and achievable
Speakers
– Subramanian Ramadorai
– Dr. Jitendra Singh
Arguments
Mission Karmayogi demonstrates that systemic technology-enabled civil services reform is achievable across diverse contexts
Government has done away with almost 2,000 outdated rules while opening up to learn new practices
Topics
Social and economic development | The enabling environment for digital development
Takeaways
Key takeaways
AI governance must be human-centric with ethical, accountable and inclusive frameworks, requiring a hybrid model that combines artificial intelligence with human intelligence
AI cannot simply be layered onto existing legacy systems – structural reform and reengineering of IT infrastructure is necessary to harness AI’s full potential
Capacity building should be treated as an engine of innovation rather than an afterthought, with personalized learning pathways and continuous feedback loops
India offers a ‘third way’ in AI development focused on partnership and collaboration, leveraging its digital public infrastructure as trust architectures
Small language models that are context-specific, sectoral, and decentralized will be more important than massive monolithic models for serving the next billion AI users
International collaboration, particularly South-South partnerships between countries like Brazil and India, is crucial for shaping global AI governance conversations
Environmental sustainability must be addressed through both ‘AI for green’ (using AI for climate policies) and ‘green AI’ (sustainable AI infrastructure)
There is a significant gap between AI implementation ambition and proper evaluation – only 45% of those with AI pilots have evaluation plans
Integrity cannot be substituted by artificial intelligence and remains fundamental to effective AI governance
Resolutions and action items
Launch of the Digital Capacity Building Alliance blueprint to forge global partnerships for AI-enabled governance
Establishment of alliance bringing together governments, industry, academia, civil society, and startups for collaborative capacity building
Development of sector-specific competency frameworks for deploying AI agents to solve local problems
Implementation of personalized learning pathways through platforms like Mission Karmayogi
Creation of evaluation frameworks and benchmarks for AI implementation in public services
Commitment to carbon-neutral data centers by 2030 and development of energy-efficient AI models
Continued collaboration between Brazil and India on R&D, capacity building, and global AI governance frameworks
Unresolved issues
How to effectively scale AI readiness across diverse public institutions globally while maintaining ethical standards
Specific mechanisms for implementing the proposed Digital Capacity Building Alliance and ensuring sustainable funding
Detailed frameworks for AI procurement guidelines and competency assessment tools that can be adapted across different national contexts
How to balance the urgency of AI adoption with the need for proper evaluation and risk management
Addressing the 75% of AI implementers who don’t understand their government’s ethical frameworks
Specific technical solutions for integrating AI with legacy government systems while maintaining security and data sovereignty
How to ensure equitable access to AI benefits across different socioeconomic groups and geographic regions
Suggested compromises
Hybrid model combining artificial intelligence with human intelligence rather than full automation, ensuring human oversight in decision-making
Gradual reengineering of existing IT systems rather than complete replacement, allowing for phased AI integration
Focus on small language models and edge computing rather than massive centralized AI systems to balance capability with accessibility
South-South collaboration approach that complements rather than competes with existing US-China AI development models
Balancing rapid AI adoption with proper evaluation frameworks – piloting with built-in assessment mechanisms
Addressing both ‘AI for green’ and ‘green AI’ approaches simultaneously to balance innovation with environmental responsibility
Creating flexible international frameworks that can be localized to different national contexts while maintaining global standards
Thought provoking comments
The future of AI, more precisely the agentic AIs, will not be in massive monolithic models. It will be in small language models, context-specific, sectoral, and decentralized. This would entail creating the customized, sector-specific competency framework that can suitably deploy AI agents to arrive at decision points that solve local needs and problems in its context.
Speaker
Shubhavi S. Radha Chauhan
Reason
This comment challenges the dominant narrative about AI development focusing on large language models and instead proposes a decentralized, context-specific approach. It’s particularly insightful because it connects AI architecture decisions directly to governance needs and local problem-solving, suggesting a more democratic and accessible AI future.
Impact
This comment set the technical foundation for the entire discussion, shifting focus from generic AI adoption to contextual, localized AI solutions. It influenced subsequent speakers to discuss edge computing, multilingual support, and domain-specific applications rather than broad AI implementation.
AI is not a layer that you could just put on existing systems… The existing systems, they actually have silos of data, silos of business logic, whereas AI, as we sort of look at this as more holistically, you need to really have a contextual data for you to train models to make it useful for you. And so we need to really sort of look at reengineering some of our existing IT systems.
Speaker
Anil Shivastava
Reason
This comment directly addresses a critical misconception about AI implementation in government systems. It’s thought-provoking because it challenges the common assumption that AI can be easily integrated into legacy systems and instead calls for fundamental system redesign.
Impact
This technical insight shifted the conversation from theoretical AI benefits to practical implementation challenges. It prompted discussion about data sovereignty, security vectors, and the need for process reengineering, making the conversation more grounded in operational realities.
Of those people implementing AI in their governments, these are people whose job it is to roll out the technology, only 26% say they understand their own government’s ethical frameworks. So in other words, 75% are freestyling, and that builds a great deal of risk into the system.
Speaker
Robin Scott
Reason
This statistic is startling and reveals a dangerous gap between policy creation and implementation. It’s particularly insightful because it exposes that even those responsible for AI deployment lack understanding of ethical guidelines, suggesting systemic capacity building failures.
Impact
This data point created a sense of urgency in the discussion and validated the need for the capacity building alliance being proposed. It shifted the conversation from aspirational AI goals to addressing fundamental knowledge gaps in government AI implementation.
We are at 80 meters to the edge of the precipice… Should we see Bharat by 2047? It is actually procrastination of our responsibilities. We just don’t want to own up what’s happening today… should they have to come as a concert of civilizations by 2026 itself, right here, right now?
Speaker
Audience member
Reason
This comment introduces existential urgency to the discussion, referencing the Doomsday Clock and challenging the 2047 timeline as potentially too slow given current global risks. It’s thought-provoking because it reframes the entire AI governance discussion in terms of civilizational survival rather than incremental progress.
Impact
This intervention dramatically shifted the tone from technical and policy discussions to existential concerns. It forced speakers to address the tension between careful, methodical capacity building and the urgent need for global coordination on AI risks.
Artificial intelligence can substitute everything on this planet but it cannot substitute integrity… one has to be intelligent enough to use artificial intelligence. Otherwise, you don’t get into this business.
Speaker
Dr. Jitendra Singh
Reason
This comment cuts to the philosophical heart of AI governance by identifying integrity as the irreplaceable human element. It’s insightful because it suggests that technical AI capabilities are secondary to the moral and ethical capacity of those who deploy them.
Impact
This comment provided a philosophical anchor for the entire discussion, reinforcing the ‘human-in-the-loop’ principle and validating the focus on capacity building as fundamentally about developing human judgment rather than just technical skills.
There’s AI for green and green AI. So aiming for sustainability on the power you provide for the GPUs and so on is crucial. But also we could use AI to leverage the potential of climate policies.
Speaker
Guilherme Albusco Almeida
Reason
This comment introduces a crucial dual perspective on AI and sustainability that hadn’t been explicitly articulated before. It’s insightful because it reframes environmental concerns from being just about AI’s carbon footprint to AI as a tool for environmental solutions.
Impact
This distinction helped broaden the discussion beyond immediate technical concerns to longer-term sustainability considerations, influencing how other speakers framed AI’s role in addressing global challenges rather than just creating them.
Overall assessment
These key comments fundamentally shaped the discussion by introducing multiple layers of complexity and urgency to AI governance. The conversation evolved from initial technical and policy frameworks to deeper questions about system architecture, implementation gaps, existential risks, and philosophical foundations. The most impactful comments challenged assumptions (AI as a simple overlay, 2047 timelines as adequate, technical solutions as sufficient) and introduced data-driven reality checks (75% of implementers lacking ethical framework understanding). The discussion’s trajectory moved from aspirational AI adoption to practical implementation challenges, then to existential concerns, and finally to philosophical anchoring around human integrity. This progression created a more nuanced understanding that effective AI governance requires not just technical capacity but fundamental system redesign, urgent global coordination, and unwavering focus on human values and judgment.
Follow-up questions
How can the proposed Digital Capacity Building Alliance be operationalized and how can diverse partners work together to translate the blueprint into sustainable actions?
Speaker
Subramanian Ramadorai
Explanation
This is crucial for moving from conceptual framework to practical implementation of the alliance across different countries and organizations
How can governments and AI companies work together to ensure that AI-driven public infrastructure is aligned with climate responsibility, energy efficiency and sustainable growth?
Speaker
Subramanian Ramadorai
Explanation
This addresses the environmental impact of AI technologies and the need for sustainable development in AI implementation
How can we develop a consolidated international framework including AI procurement guidelines, AI ethical frameworks, and competency frameworks that can be hyper-localized to different country contexts?
Speaker
Professor Charu from Indian Institute of Public Administration
Explanation
This addresses the gap in standardized international frameworks while allowing for local adaptation and implementation
How can we develop a more generic collaborative international AI impact framework assessment tool that looks at capabilities across whole organizations or countries, not just at digital leadership level?
Speaker
Professor Charu from Indian Institute of Public Administration
Explanation
This would provide comprehensive assessment capabilities for AI readiness and impact measurement across different organizational levels
How can we ensure public officials understand their own government’s ethical frameworks for AI implementation?
Speaker
Robin Scott
Explanation
Critical gap identified where only 26% of AI implementers understand their government’s ethical frameworks, creating significant risk
How can we develop better evaluation mechanisms for AI pilots in government, given that only 45% have evaluation plans?
Speaker
Robin Scott
Explanation
Essential for measuring success and learning from AI implementation efforts in public sector
How can small language models be developed that are domain-specific, can run on edge devices, operate in rural environments, and solve real local problems?
Speaker
Subramanian Ramadorai
Explanation
Important for making AI accessible and relevant to rural and underserved populations, particularly in developing countries
How can we re-engineer existing IT systems and processes to harness AI potential while addressing security and data sovereignty concerns?
Speaker
Anil Shivastava
Explanation
Critical technical challenge for integrating AI into legacy government systems without compromising security
How can we develop AI systems that support multilingual capabilities for frontline workers like ASHA workers to deliver services in native languages?
Speaker
Anil Shivastava
Explanation
Essential for inclusive AI deployment that serves diverse linguistic populations effectively
Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.
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