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 glanceSummary, keypoints, and speakers overview

Summary

The India AI Impact Summit opened with Dr. Washima emphasizing that AI is the “next big thing after electricity” and calling for trust-based, collaborative ethical frameworks to guide fast-paced AI development for economic growth, social good, and human capital [4-10][11-13]. Chairperson Shubhavi S. Radha Chauhan reinforced the government’s human-centric AI vision, advocating small, sector-specific language models and a capacity-building agenda that equips officials with the skills to set data guardrails and evaluate outcomes [23-33][34-38].


India’s approach was illustrated by the Commission’s policy frameworks, operational guidelines, and the nation’s extensive digital public infrastructure, which together support a workforce of 5.8 million AI professionals and enable localized AI solutions such as tiny models for rural health and agriculture [73-78][92-98]. Panelist Anil Shivastava warned that AI cannot simply be layered onto legacy systems; it requires re-engineering of data silos, multilingual support, and new security considerations [122-138]. Guilherme Albusco Almeida highlighted Brazil-India collaboration opportunities in R&D, capacity-building platforms, and ethical-assessment frameworks, noting existing South-South partnerships [148-166]. Robin Scott identified major gaps: only 26 % of implementers understand their own ethical frameworks and many pilots lack evaluation plans, yet over 90 % remain optimistic about AI’s productivity gains [182-194].


Addressing environmental impact, Robin cited a new AI-climate course, Guilherme described “green AI” initiatives and AI-driven forest monitoring, and Anil noted Google’s pledge for carbon-neutral data centres by 2030 [201-203][204-213][215-218]. The summit culminated in the launch of a Digital Capacity Building Alliance-a global public-good model linking governments, industry, academia, and civil society to scale inclusive, ethical AI capacity building [247-270], reinforced by Minister Dr. Jitendra Singh’s keynote on dynamic governance, continuous learning, and the necessity of human-in-the-loop integrity [288-306]. The event closed with a call to translate the discussed frameworks into concrete actions for responsible AI deployment worldwide [387].


Keypoints


Major discussion points


Human-centric, ethical AI governance and the need for trust-based frameworks – The opening remarks stress “carve out trust-based collaborative ethical frameworks” for AI-DPD (dynamic AI) age [10]; the Chairperson reiterates the PM’s “human-centric framework for ethical, accountable and inclusive AI governance” [23-24]; the summit theme itself is “AI for economic development, social good, safe and trusted AI, and human capital” [11-13]; later, Robin highlights that only 26 % of implementers understand their own government’s ethical frameworks, exposing a major risk [182-188].


Building localized, sector-specific AI capabilities and competency pathways – Shubhavi argues that the future lies in “small language models, context-specific, sectoral, and decentralized” rather than monolithic models, requiring customized competency frameworks [30-33]; Anil explains that legacy IT systems must be re-engineered, data prepared, and multilingual support added to enable AI at the edge (e.g., ASHA workers) [126-135]; Ramadorai adds that the next billion AI users will interact with “tiny embedded AI in phones, tractors, classrooms, clinics and local government systems” [96-98].


International (Brazil-India) collaboration for AI capacity building – Guilherme describes existing Brazil-India exchanges, complementary R&D, and parallel capacity-building institutions, proposing a “South-South” partnership to scale knowledge for public servants [147-160]; Robin notes the joint effort with Brazil’s ENAP and Google.org to train a million public servants, emphasizing the strategic value of such collaborations [172-179]; the moderator’s question to Guilherme explicitly asks about deepening Brazil-India cooperation [143-144].


Technical and operational risks of integrating AI into legacy public systems – Anil points out that AI cannot simply be layered onto existing siloed systems; it requires re-engineering, data readiness, and attention to security and data-sovereignty vectors [126-138]; Robin’s survey data reveal a gap between pilots and evaluation plans (45 % have evaluation despite 72 % planning pilots) [188-190]; Ramadorai also warns that governance challenges extend beyond technology to ensure officials understand system limits and ethical use [99-101].


Environmental sustainability of AI deployment – The final panel question raises the climate footprint of AI; Robin mentions a dedicated “AI and climate” course developed with Stanford’s Doerr School of Sustainability [201-202]; Guilherme differentiates “AI for green” (energy-efficient GPUs) and using AI to support climate policy, citing Brazil’s AI-driven forest-monitoring system [204-213]; Anil adds Google’s commitment to carbon-neutral data centres by 2030 and the need for energy-efficient models [215-218].


Overall purpose / goal of the discussion


The event serves to launch and promote a Digital Capacity Building Alliance that will provide a global, non-proprietary framework for AI skill development, ethical standards, and public-service innovation. It aligns with the India AI Impact Summit’s theme of leveraging AI for economic development, social good, and safe, trusted deployment, and seeks to translate the Capacity Building Commission’s policy work into actionable, collaborative programs for India and partner nations [11-13][39-40][250-267].


Overall tone and its evolution


– The opening segment is formal and aspirational, emphasizing vision, responsibility, and collective purpose [4-13].


– As the panel proceeds, the tone becomes technical and problem-focused, with detailed discussion of legacy system challenges, data sovereignty, and competency design [126-138].


– Mid-session, the conversation shifts to a collaborative and optimistic mood, highlighting Brazil-India partnerships and shared training initiatives [147-179].


– Towards the end, the tone turns pragmatic and urgent, addressing gaps in ethical understanding, evaluation, and the environmental impact of AI [182-190][197-213].


– The closing remarks return to a celebratory and call-to-action tone, urging participants to seize the moment, uphold integrity, and implement the newly launched alliance [288-306][350-356].


Overall, the discussion moves from high-level vision to concrete challenges, then to partnership opportunities, and finally to concrete commitments and a rallying call for collective action.


Speakers

Dr. Washima


Moderator – Event moderator (moderates the session) [S13]


Shubhavi S. Radha Chauhan – Chairperson of the Capacity Building Commission; expertise in public administration and capacity building [S7]


Guilherme Albusco Almeida – Senior Consultant, Institute of Management and Corporation in Public Services, Government of Brazil; expertise in government reform, digital transformation and AI ethics [S8]


Dr. Jitendra Singh – Honorable Minister of State for Personnel, Minister of State for Personal Grievances and Pensions; expertise in administrative reforms and India’s science & innovation agenda [S9]


Anil Shivastava – Chief Architect for Goodwill’s public-sector work; leads Public Policy Strategic AI Solution Engagements of Global Cloud in India; expertise in AI solutions, cloud computing and public-sector transformation (as described in the transcript)


Subramanian Ramadorai – Chairperson of Karni Nagi Bharat and former MD & CEO of Tata Consultancy Services; expertise in technology engineering and the intersection of technology with government institutions [S18]


Robin Scott – Co-founder and CEO of Apolitical; expertise in AI capacity-building programmes for public servants worldwide [S19]


Audience – Various audience members (e.g., Professor Charu, Indian Institute of Public Administration – public administration; Yuv from Senegal) [S1][S2]


Speaker 1 – Unnamed speaker who presented the AI-enabled government blueprint after the minister’s launch (role not specified)


Speaker 3 – Unnamed speaker who asked a follow-up question near the end of the session (role not specified)


Additional speakers not listed in the provided speakers list


Mr. Frager – Mentioned by the moderator when introducing the panel


Mr. S. Amogarai – Referred to as Chairperson of Karni Nagi Bharat (possible duplicate of Subramanian Ramadorai)


Mr. Schneider – Cited by the moderator in the opening remarks


Mr. Jeet Adani – Cited by the moderator in the opening remarks


Kirti Ardhan – Named by Dr. Jitendra Singh during his address


Other unnamed participants – Various individuals who spoke briefly or were referenced in the dialogue but are not part of the original speakers list.


Full session reportComprehensive analysis and detailed insights

The summit opened with Dr Washima reminding the audience that “technology is a great leveler, and AI, they say, is the next big thing after electricity” and urging participants to “carve out trust-based collaborative ethical frameworks” for the fast-paced AI-DPD age so that public services can be delivered faster, better, safer and more equitably [4-5][6][8-10][11-13]. He emphasized that AI must augment, not replace, human judgment-a point later echoed by Dr Jitendra Singh [10][324-327].


Chairperson Shubhavi S. Radha Chauhan of the Capacity Building Commission highlighted the Prime Minister’s “Mani Vision” – a human-centric framework for ethical, accountable and inclusive AI governance [23-24] – and argued that the future will lie in “small language models, context-specific, sectoral, and decentralised” rather than massive monolithic systems [30-31]. To operationalise this vision, the Commission has produced holistic policy frameworks, operational guidelines, personalised learning pathways and dynamic governance models that together support a workforce of 5.8 million professionals [34-38][73-78] and enable localised solutions such as tiny models for rural health and agriculture [92-98].


The moderator introduced the panel, naming the chairperson of the Capacity Building Commission, Mr S. Amogarai, and the three distinguished panelists – Prof Guilherme Albusco Almeida (Brazil), Anil Shivastava (Google Cloud), and Robin Scott (co-founder of a global public-servant network) [42-50].


Subramanian Ramadorai opened the discussion by reflecting on past technological revolutions, noting that “the most important question … is not how far we can scale AI but how we can recognise it as a movement that elevates humanity” [66-68]. He positioned India’s approach as a “third way” – a partnership model that sits between the US-led market race and China’s state-led techno-nationalism [73-76]. He underscored India’s extensive digital public infrastructure (RADAR, UPI, digital locker, etc.) as a “trust architecture” that can support the next billion AI users who will interact with “tiny embedded AI in phones, tractors, classrooms, clinics and local government systems” [92-98][96-98].


When asked about the technical risks of layering AI onto legacy systems, Anil Shivastava warned that existing IT platforms are “centred on silos of data and business logic” and cannot simply have an AI layer added [122-124]. He called for a re-engineering of data pipelines, multilingual data preparation for edge-AI (e.g., ASHA workers), and a renewed focus on security and data-sovereignty before any AI-driven decision-making can be trusted [126-138].


Prof Guilherme Albusco Almeida responded by outlining Brazil-India collaboration opportunities. He cited ongoing exchanges, complementary R&D capacities and parallel capacity-building institutions, proposing a “South-South” partnership that would scale knowledge for civil-service AI training across both nations [147-152][155-166]. He also mentioned Brazil’s ethical-assessment framework for AI and the potential to co-develop sector-specific models and procurement guidelines.


Robin Scott presented survey data that revealed a stark governance gap: only 26 % of public-sector AI implementers say they understand their own government’s ethical framework, meaning the majority are “freestyling” [182-188]. Moreover, while 72 % plan pilots, merely 45 % have an evaluation plan, highlighting a risk of unchecked deployments [188-190]. Despite these gaps, she noted that over 90 % of public servants remain optimistic about AI’s productivity gains, estimating a $1.75 trillion upside if the technology is harnessed responsibly [191-194].


The final panel question turned to environmental sustainability. Robin announced a new “AI-and-climate” course co-created with Stanford’s Doerr School of Sustainability [201-203]. Guilherme differentiated between “green AI” (energy-efficient hardware) and “AI for green” (using AI to support climate policy), citing Brazil’s Rural Environmental Registry that employs AI to monitor deforestation and guide reforestation [204-213]. Anil added that Google has pledged to make all its data centres carbon-neutral by 2030 and is ready to partner with India to embed similar targets in Indian facilities [215-218].


Audience members then raised concerns about timelines, invoking the Doomsday Clock metaphor and asking whether India could achieve its AI-driven governance vision by 2047 or even earlier [227-244]. One participant, Professor Charu, called for a “generic, hyper-localisable international AI impact framework assessment tool” to bridge the current lack of procurement and ethical guidelines [246].


The moderator announced the launch of the Digital Capacity Building Allowance, a non-proprietary, demand-driven framework that combines global AI principles, digital-public-good standards, and the Mission-Karmayogi model to fund and coordinate capacity-building activities across governments, industry, academia, civil society and start-ups [251-270][263-270].


Minister Dr Jitendra Singh delivered the keynote, stressing that governance, capacity building and AI are all “dynamic, continuous” processes that must be synchronised [292-298]. He praised India’s political dispensation for removing nearly 2 000 outdated rules in the past decade and for embracing “human-in-the-loop” integrity as non-negotiable [310-327]. He introduced the acronym M-A-N-A-A (M = Moral & ethical systems; A = Accountable governance; N = National sovereignty; A = Accessible & inclusive; A = Valid & legitimate) [370-376].


The session closed with the moderator thanking all participants, inviting a group photograph and urging attendees to “translate the discussed frameworks into concrete actions for responsible AI deployment worldwide” [387-389].


Across the discussion, there was strong consensus that ethical, human-centred AI governance is essential (Dr Washima, Robin Scott, Dr Singh) [10][182-188][324-327]; that AI can act as a catalyst for inclusive, citizen-centred development (Dr Washima, Dr Singh, Subramanian, Speaker 1) [4][66-68][258-262]; and that small, sector-specific models are preferable to monolithic systems (Shubhavi, Subramanian) [31-33][96-98]. Participants also agreed on the need for customised competency frameworks and personalised learning pathways (Shubhavi, Anil, Robin, Speaker 1, Subramanian) [33-35][126-135][201-203][258-262][104-105]. South-South collaboration, especially between Brazil and India, was highlighted as a viable “third way” to shape global AI norms (Guilherme, Subramanian) [147-152][155-166][73-76].


Notable disagreements emerged. Robin’s data showed a gap between the aspirational “trust-based collaborative ethical frameworks” and the reality that only a quarter of implementers understand them [182-188] versus Dr Washima’s call for such frameworks [10]. On climate-focused AI, Anil presented a well-funded corporate pledge for carbon-neutral data centres [215-218] while Robin suggested that the AI-climate course “has too much money”, indicating uncertainty about funding adequacy [201-203]. Finally, Anil argued for extensive re-engineering of legacy systems [126-138] whereas Subramanian emphasised the opportunity of deploying lightweight edge models without a full overhaul [96-98].


The event concluded with the launch of the Digital Capacity Building Allowance and a commitment by Google to achieve carbon-neutral data centres by 2030 [215-218][263-270]. A pledge was also made to develop sector-specific, edge-optimised language models for rural contexts [96-98] and to continue large-scale AI training for public servants (target of one million, 400 000 already achieved) [172-179]. Unresolved issues include the detailed operational design of the Allowance’s funding mechanisms, the precise steps needed to align legacy-infrastructure modernisation with workforce capability development, the establishment of standardised evaluation processes for AI pilots, and the creation of a universally applicable, hyper-localisable AI impact assessment tool [246][188-190][104-105].


In sum, the India AI Impact Summit reaffirmed that AI should be deployed as a human-centred, trustworthy technology that drives inclusive socio-economic development while respecting ethical norms and environmental limits. By coupling sector-specific capacity-building pathways with global South-South partnerships and a clear commitment to human-in-the-loop integrity, the participants charted a roadmap that moves from aspirational vision to actionable, collaborative implementation [4][66-68][324-327][258-262].


Session transcriptComplete transcript of the session
Dr. Washima

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.

Moderator

Thank you, Dr. Washima. I now invite our Chairperson of the Capacity Building Commission, Shubhavi S. Radha Chauhan, to deliver the opening address.

Shubhavi S. Radha Chauhan

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.

Moderator

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

Subramanian Ramadorai

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.

Anil Shivastava

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.

Subramanian Ramadorai

Guy, he told me it’s very easy to remember his name because Guy is a new word also.

Guilherme Albusco Almeida

Yes.

Subramanian Ramadorai

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?

Guilherme Albusco Almeida

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.

Subramanian Ramadorai

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?

Robin Scott

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.

Subramanian Ramadorai

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.

Robin Scott

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.

Guilherme Albusco Almeida

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.

Anil Shivastava

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.

Subramanian Ramadorai

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.

Audience

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.

Subramanian Ramadorai

I agree, yeah.

Audience

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?

Subramanian Ramadorai

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

Speaker 3

one more question here last question please thank you

Audience

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

Moderator

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

Speaker 1

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.

Moderator

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.

Shubhavi S. Radha Chauhan

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.

Dr. Jitendra Singh

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.

Moderator

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

Related ResourcesKnowledge base sources related to the discussion topics (44)
Factual NotesClaims verified against the Diplo knowledge base (7)
Confirmedhigh

“AI must augment, not replace, human judgment”

The knowledge base stresses that AI should enhance rather than replace humanity and that human oversight remains essential, confirming the report’s statement [S71] and [S127] and [S128].

!
Correctionhigh

“Prime Minister’s “Mani Vision” – a human‑centric framework for ethical, accountable and inclusive AI governance”

The official name of the framework is “MANAV Vision”, presented by Prime Minister Narendra Modi, not “Mani Vision” [S129].

Confirmedmedium

“Chairperson Shubhavi S. Radha Chauhan of the Capacity Building Commission highlighted the Vision”

The existence of the Capacity Building Commission and its role in AI workforce development is documented in the knowledge base [S2].

Confirmedmedium

“Prof Guilherme Albusco Almeida (Brazil) was a panelist”

Guilherme Albusco Almeida’s participation in the summit panel is recorded in the knowledge base [S16].

Additional Contextmedium

“India’s approach is a “third way” – a partnership model between the US‑led market race and China’s state‑led techno‑nationalism”

The knowledge base provides a definition of techno-nationalism, clarifying the contrast with the US market-driven model and supporting the report’s framing of India’s “third way” [S140].

Additional Contextlow

“India’s extensive digital public infrastructure (RADAR, UPI, digital locker, etc.) serves as a “trust architecture” for AI”

India’s digital public infrastructure initiatives, such as Mission Kalmaragi and related capacity-building efforts, are described in the knowledge base, giving background to the report’s claim [S2].

Additional Contextlow

“Future AI will rely on “small language models, context‑specific, sectoral, and decentralised” rather than massive monolithic systems”

The knowledge base mentions a push for frugal, low-carbon-footprint AI and the need for more lightweight models, which adds nuance to the report’s statement [S108].

External Sources (140)
S1
WS #280 the DNS Trust Horizon Safeguarding Digital Identity — – **Audience** – Individual from Senegal named Yuv (role/title not specified)
S2
Building the Workforce_ AI for Viksit Bharat 2047 — -Audience- Role/Title: Professor Charu from Indian Institute of Public Administration (one identified audience member), …
S3
Nri Collaborative Session Navigating Global Cyber Threats Via Local Practices — – **Audience** – Dr. Nazar (specific role/title not clearly mentioned)
S4
Building the Workforce_ AI for Viksit Bharat 2047 — -Speaker 1- Role/Title: Not specified, Area of expertise: Not specified -Speaker 3- Role/Title: Not specified, Area of …
S5
S6
Advancing Scientific AI with Safety Ethics and Responsibility — – Speaker 1- Speaker 2- Speaker 3 – Speaker 1- Speaker 3- Moderator
S7
Building the Workforce_ AI for Viksit Bharat 2047 — -Shubhavi S. Radha Chauhan- Role/Title: Chairperson of the Capacity Building Commission, Area of expertise: Public admin…
S8
Building the Workforce_ AI for Viksit Bharat 2047 — Guilherme Albusco Almeida from Brazil, noting his fifth trip to India, identified strong collaboration opportunities in …
S9
Building the Workforce_ AI for Viksit Bharat 2047 — -Dr. Jitendra Singh- Role/Title: Honorable Minister, Minister of State for Personnel, Minister of State for Personal Gri…
S10
Keynote-Martin Schroeter — -Speaker 1: Role/Title: Not specified, Area of expertise: Not specified (appears to be an event moderator or host introd…
S11
Responsible AI for Children Safe Playful and Empowering Learning — -Speaker 1: Role/title not specified – appears to be a student or child participant in educational videos/demonstrations…
S12
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Vijay Shekar Sharma Paytm — -Speaker 1: Role/Title: Not mentioned, Area of expertise: Not mentioned (appears to be an event host or moderator introd…
S13
Keynote-Olivier Blum — -Moderator: Role/Title: Conference Moderator; Area of Expertise: Not mentioned -Mr. Schneider: Role/Title: Not mentione…
S14
Keynote-Vinod Khosla — -Moderator: Role/Title: Moderator of the event; Area of Expertise: Not mentioned -Mr. Jeet Adani: Role/Title: Not menti…
S15
Day 0 Event #250 Building Trust and Combatting Fraud in the Internet Ecosystem — – **Frode Sørensen** – Role/Title: Online moderator, colleague of Johannes Vallesverd, Area of Expertise: Online session…
S16
https://dig.watch/event/india-ai-impact-summit-2026/building-the-workforce_-ai-for-viksit-bharat-2047 — Minister in the National Council on Scale Development We welcome you sir On the panel, we are joined by Guilherme Albusc…
S17
Building the Workforce_ AI for Viksit Bharat 2047 — – Anil Shivastava- Dr. Jitendra Singh – Anil Shivastava- Subramanian Ramadorai
S18
Building the Workforce_ AI for Viksit Bharat 2047 — -Subramanian Ramadorai- Role/Title: Chairperson of Karni Nagi Bharat and former M.D. and CEO of Tata Consultancy Service…
S19
https://dig.watch/event/india-ai-impact-summit-2026/how-ai-is-transforming-diplomacy-and-conflict-management — And the MOVE 37 initiative that we’re here to talk to you about today. is a part of that program. As you can imagine, in…
S20
How AI Is Transforming Diplomacy and Conflict Management — And the MOVE 37 initiative that we’re here to talk to you about today. is a part of that program. As you can imagine, in…
S21
Building the Workforce_ AI for Viksit Bharat 2047 — -Dr. Washima- Role/Title: Not specified, Area of expertise: Not specified
S22
PLAN NATIONAL DU NUMÉRIQUE HORIZON 2025 — | N° | NOMS | INSTITUTION | | 67 …
S23
Authors of this report — Trust builds on shared assumptions about material and immaterial values, about what is important and what is expendable….
S24
High-Level Session 3: Exploring Transparency and Explainability in AI: An Ethical Imperative — 1. Trust, safety, and accountability: His Excellency Dr. Abdullah bin Sharaf Alghamdi emphasised the need to focus on th…
S25
AI Impact Summit 2026: Global Ministerial Discussions on Inclusive AI Development — Excellency, thank you very much first and foremost I would like to thank India for hosting this excellent event Malaysia…
S26
How can Artificial Intelligence (AI) improve digital accessibility for persons with disabilities? — Furthermore, the synthesis highlights the positive role of multi-sectoral collaboration in driving disability inclusion….
S27
Closing Ceremony — This argument positions artificial intelligence as a transformative force rather than merely a technological tool. It su…
S28
https://dig.watch/event/india-ai-impact-summit-2026/the-foundation-of-ai-democratizing-compute-data-infrastructure — Given the volume of funds available, I would focus a lot more on capability development of people to be able, their abil…
S29
AI Meets Agriculture Building Food Security and Climate Resilien — The World Bank’s Johannes Zutt stressed the importance of collaborative ecosystems where government provides foundationa…
S30
Building Scalable AI Through Global South Partnerships — This comment elevated the discussion by providing a philosophical foundation for South-South cooperation based on shared…
S31
Climate change and Technology implementation | IGF 2023 WS #570 — João Vitor Andrade:Hi, everyone. I’d like to thank you all to be present here today. My name is João Vitor, I’m from Bra…
S32
Judiciary engagement — – Adel Maged- Maureen Fondo- Slyvia Chirawu- Audience Legal and Regulatory Framework Needs Legal and regulatory | Huma…
S33
WS #438 Digital Dilemmaai Ethical Foresight Vs Regulatory Roulette — Deloitte consultant: Good morning everyone. My name is Yasmin Alduri. I’m an AI governance consultant at Deloitte and I’…
S34
Main Topic 2 – Empowering communities: partnerships for access to services  — Arturas Piliponis:Thank you, nice examples. Ieva, anything or others to add? If not, I can share just building on what y…
S35
Veronica Cretu — Experiences from around the world have demonstrated that using information on the performance of service providers by bo…
S36
Green AI and the battle between progress and sustainability — AI is increasingly recognised for its transformative potential and growing environmental footprint across industries. Th…
S37
Smaller Footprint Bigger Impact Building Sustainable AI for the Future — Thank you so much. And I’ll be very quick because I can see the ticker. There are a couple of things. One is that we’re …
S38
Survival Tech Harnessing AI to Manage Global Climate Extremes — “We are introducing, you know, IP and other innovations to drive translation”[99]. “In some of our programs, we have put…
S39
Day 0 Event #173 Building Ethical AI: Policy Tool for Human Centric and Responsible AI Governance — Alaa Abdulaal concluded the session by emphasizing DCO’s commitment to a multi-stakeholder approach in addressing ethica…
S40
MahaAI Building Safe Secure & Smart Governance — His solution advocated for “intelligent governance” built upon five core principles: human-centred design, transparency …
S41
AI & Child Rights: Implementing UNICEF Policy Guidance | IGF 2023 WS #469 — Incidents such as the arrest of a young man near Windsor Castle, who was influenced by his AI assistant to harm the Quee…
S42
WS #205 Contextualising Fairness: AI Governance in Asia — 4. Community-based models: Chin mentioned the potential of community-based small models to serve specific needs. Milton…
S43
Open Forum #64 Local AI Policy Pathways for Sustainable Digital Economies — Abhishek Singh: One part is that, of course, the way the technology is evolving, there is IP-driven solutions and there …
S44
Building Population-Scale Digital Public Infrastructure for AI — The Brazilian experience illustrates the systemic nature of the challenge, requiring coordinated changes in legal framew…
S45
AI as critical infrastructure for continuity in public services — Data silos emerged as a primary barrier, with organizations struggling to integrate data across different systems and de…
S46
WS #123 Responsible AI in Security Governance Risks and Innovation — This comment elevated the technical discussion to a more sophisticated understanding of systemic governance challenges. …
S47
Pre 10: Regulation of Autonomous Weapon Systems: Navigating the Legal and Ethical Imperative — Issues particularly evident in joint or cross-force environments where systems must function across organizational, nati…
S48
Open Forum #58 Collaborating for Trustworthy AI an Oecd Toolkit and Spotlight on AI in Government — ### Scaling from Pilots to Systems Government AI carries higher risks than private sector applications, including ethic…
S49
Navigating the Double-Edged Sword: ICT’s and AI’s Impact on Energy Consumption, GHG Emissions, and Environmental Sustainability — An expert panel convened to examine the complex relationship between Information and Communication Technologies (ICTs) a…
S50
Networking Session #50 AI and Environment: Sustainable Development | IGF 2023 — Artificial Intelligence (AI) technologies have the potential to significantly contribute to creating greener cities and …
S51
Building the Workforce_ AI for Viksit Bharat 2047 — Capacity building should be treated as an engine of innovation rather than an afterthought, with personalized learning p…
S52
Agenda item 6 — Ghana:Mr. Chair, thank you for giving me the floor. I would like to join others before me in wishing us all a happy Wome…
S53
Opening of the session — Kazakhstan: Thank you, Chair, for giving the floor. Mr. Chair, distinguished delegates, as it’s our first time taking th…
S54
Networking Session #50 AI and Environment: Sustainable Development | IGF 2023 — In addition to supporting climate action, AI is expected to play a significant role in digitally managed energy systems….
S55
High-Level Session 3: Exploring Transparency and Explainability in AI: An Ethical Imperative — Li discusses the potential of AI-driven models in climate prediction and resource mobilization. He highlights the import…
S56
Open Forum #27 Make Your AI Greener a Workshop on Sustainable AI Solutions — Development | Human rights | Sustainable development Funding and Policy Mechanisms Mark Gachara emphasized that climat…
S57
Artificial Intelligence Strategy of the German Federal Government — The Federal Government will continue and expand the successfully launched funding initiative AI Flagship Projects for th…
S58
Closing remarks – Charting the path forward — Bouverot emphasizes that AI governance must address environmental concerns by incorporating sustainability measures. Thi…
S59
WS #466 AI at a Crossroads Between Sovereignty and Sustainability — Environmental Impact and Climate Justice Moltzau argues that given the current climate crisis and multiple global chall…
S60
UNESCO links AI development with climate responsibility — UNESCO hasrenewed calls for stronger international cooperationto ensure AI supports rather than undermines climate goals…
S61
Green AI and the battle between progress and sustainability — AI is increasingly recognised for its transformative potential and growing environmental footprint across industries. Th…
S62
DC-DNSI: Beyond Borders – NIS2’s Impact on Global South — Guangyu Qiao-Franco: So my contribution is co-hosted with Mr. Mahmoud Javadi of Free University Brussels, who is also pr…
S63
AI Impact Summit 2026: Global Ministerial Discussions on Inclusive AI Development — Ante este panorama, los países del sur global debemos priorizar estrategias y normativas para un uso ético y responsable…
S64
Can (generative) AI be compatible with Data Protection? | IGF 2023 #24 — Armando José Manzueta-Peña:Well, thank you, Luca, for the presentation. I’m more than thrilled to be present here and to…
S65
Engineering Accountable AI Agents in a Global Arms Race: A Panel Discussion Report — Economic and Labor Market Impact Examples of relieving employees from 4-hour internet searches and policy drafting, add…
S66
WS #288 An AI Policy Research Roadmap for Evidence-Based AI Policy — Development | Legal and regulatory Evidence-Based Policymaking and Research Integration Part of the roadmap emphasizes…
S67
Reinventing Digital Inclusion / DAVOS 2025 — Importance of local leadership and tailored solutions Paula Ingabire discusses Rwanda’s focus on identifying AI use cas…
S68
Strengthening Corporate Accountability on Inclusive, Trustworthy, and Rights-based Approach to Ethical Digital Transformation — Moderate disagreement with significant implications. While speakers generally agreed on the importance of digital inclus…
S69
Open Forum #66 the Ecosystem for Digital Cooperation in Development — This comment cuts to the heart of development challenges by highlighting the implementation gap between policy and pract…
S70
Dynamic Coalition Collaborative Session — The discussion frequently referenced the Global Digital Compact as an example of well-intentioned policy that lacks clea…
S71
Enhancing rather than replacing humanity with AI — AI development is not some unstoppable force beyond our control. It’s shaped by developers, institutions, policymakers, …
S72
How AI Drives Innovation and Economic Growth — The speakers show broad agreement on AI’s transformative potential for development but significant disagreements on impl…
S73
Ethics in the Age of AI — In conclusion, the conversation with Michael B. Jordan shed light on various aspects of contemporary issues surrounding …
S74
From Innovation to Impact_ Bringing AI to the Public — Whilst maintaining an optimistic outlook, the discussion acknowledges important limitations and risks. Sharma emphasises…
S75
Inclusive AI For A Better World, Through Cross-Cultural And Multi-Generational Dialogue — Larissa Zutter stands out as a senior AI policy advisor, closely studying the socio-economic implications of artificial …
S76
The Role of Government and Innovators in Citizen-Centric AI — “we are developing an ecosystem which is really brilliant, self‑reliant, sufficient in terms of good company producing o…
S77
Open Forum #64 Local AI Policy Pathways for Sustainable Digital Economies — Achieving inclusive AI requires addressing inequalities across three fundamental areas: access to computing infrastructu…
S78
Is AI a catalyst for development? — The Economist argues that AI has the potential to revolutionise developing countries by transforming their economies and…
S79
Day 0 Event #173 Building Ethical AI: Policy Tool for Human Centric and Responsible AI Governance — Chris Martin: Hiya, how are you doing? Check, check. Is that better? Cool. Again, hello. Welcome. My name is Chri…
S80
How AI Is Transforming Diplomacy and Conflict Management — So that’s a pretty big gap to close and we see gaps like this all the time. One of the biggest gaps is leaders not using…
S81
WS #110 AI Innovation Responsible Development Ethical Imperatives — Ethical Concerns and Risk Mitigation Human rights principles | Development Zhang emphasizes that human-centric princip…
S82
MahaAI Building Safe Secure & Smart Governance — His solution advocated for “intelligent governance” built upon five core principles: human-centred design, transparency …
S83
S84
Building the Workforce_ AI for Viksit Bharat 2047 — From the community health worker delivering nutrition to an expecting mother to the balancing worker strategizing access…
S85
https://dig.watch/event/india-ai-impact-summit-2026/building-the-workforce_-ai-for-viksit-bharat-2047 — From the community health worker delivering nutrition to an expecting mother to the balancing worker strategizing access…
S86
Open Forum #64 Local AI Policy Pathways for Sustainable Digital Economies — Abhishek Singh: One part is that, of course, the way the technology is evolving, there is IP-driven solutions and there …
S87
[Parliamentary Session 3] Researching at the frontier: Insights from the private sector in developing large-scale AI systems — Ammari highlighted META’s open-source approach to large language models, explaining, “META has adopted an open source me…
S88
Building Population-Scale Digital Public Infrastructure for AI — Excellent point. Excellent point, Trevor. And I think you brought out the inherent stress in the phrase diffusion pathwa…
S89
Signature Panel: Building Cyber Resilience for Sustainable Development by Bridging the Global Capacity Gap — Brazil:Thank you, Robin. Distinguished Delegates, it’s an honor to be here today at the Global Roundtable on Building Ca…
S90
Open Forum #58 Collaborating for Trustworthy AI an Oecd Toolkit and Spotlight on AI in Government — Five identified risks: ethical risk, operational risk, exclusion risk, public resistance, and widened gaps between publi…
S91
Pre 10: Regulation of Autonomous Weapon Systems: Navigating the Legal and Ethical Imperative — Issues particularly evident in joint or cross-force environments where systems must function across organizational, nati…
S92
WS #123 Responsible AI in Security Governance Risks and Innovation — This comment elevated the technical discussion to a more sophisticated understanding of systemic governance challenges. …
S93
AI as critical infrastructure for continuity in public services — This statistic provides concrete evidence of the implementation gap between AI pilots and production systems. It challen…
S94
Navigating the Double-Edged Sword: ICT’s and AI’s Impact on Energy Consumption, GHG Emissions, and Environmental Sustainability — An expert panel convened to examine the complex relationship between Information and Communication Technologies (ICTs) a…
S95
Networking Session #50 AI and Environment: Sustainable Development | IGF 2023 — Artificial intelligence (AI) is improving the ways we live, work and solve problems. It can also help us fight climate c…
S96
Smaller Footprint Bigger Impact Building Sustainable AI for the Future — AI’s energy demands. Threaten to outpace green energy progress. Model providers face a stark reality. AI’s energy needs …
S97
Green AI and the battle between progress and sustainability — AI is increasingly recognised for its transformative potential and growing environmental footprint across industries. Th…
S98
Summit Opening Session — The tone throughout is consistently formal, diplomatic, and collaborative. Speakers maintain an optimistic and forward-l…
S99
Keynote-António Guterres — The tone is formal, diplomatic, and aspirational throughout, maintaining a consistent message of urgency mixed with opti…
S100
Opening remarks — In conclusion, the speaker hopes for a constructive meeting, reminding attendees of the global imperative for openness, …
S101
Opening — The overall tone was formal yet optimistic. Speakers acknowledged the serious challenges posed by rapid technological ch…
S102
Parliamentary Roundtable Safeguarding Democracy in the Digital Age Legislative Priorities and Policy Pathways — The discussion maintained a serious but collaborative tone throughout. It began with formal opening remarks emphasizing …
S103
Day 0 Event #188 Top Business and Technology Trends in Government for 2024 — A significant point emphasized in the presentation was the challenge posed by legacy systems:
S104
Prosperity Through Data Infrastructure — However, there are arguments suggesting that legacy systems present challenges in the journey of digitalisation. One vie…
S105
WS #279 AI: Guardian for Critical Infrastructure in Developing World — Hafiz Muhammad Farooq: First of all, thank you very much for inviting me today for this great panel discussion. I’m H…
S106
Agenda item 6: other matters/OEWG 2025 — The overall tone was constructive and diplomatic, with most delegations expressing willingness to compromise and find co…
S107
Open Forum #29 Advancing Digital Inclusion Through Segmented Monitoring — The discussion maintained a collaborative and constructive tone throughout, with panelists building on each other’s insi…
S108
Scaling Trusted AI_ How France and India Are Building Industrial & Innovation Bridges — The discussion maintained a consistently optimistic and collaborative tone throughout, characterized by mutual respect b…
S109
Any other business /Adoption of the report/ Closure of the session — In conclusion, the delegate’s remarks highlighted the enduring spirit of solidarity and collaboration, while also convey…
S110
Dynamic Coalition Collaborative Session — The discussion began with an optimistic, collaborative tone as panelists shared their expertise and perspectives. Howeve…
S111
How Multilingual AI Bridges the Gap to Inclusive Access — The tone was consistently collaborative, optimistic, and mission-driven throughout the conversation. Speakers demonstrat…
S112
Partnering on American AI Exports Powering the Future India AI Impact Summit 2026 — The tone is consistently optimistic, collaborative, and forward-looking throughout the discussion. Speakers emphasize “l…
S113
New Technologies and the Impact on Human Rights — The discussion maintained a collaborative and constructive tone throughout, despite addressing complex and sometimes con…
S114
AI and Human Connection: Navigating Trust and Reality in a Fragmented World — The tone began optimistically with audience engagement but became increasingly concerned and urgent as panelists reveale…
S115
Comprehensive Summary: AI Governance and Societal Transformation – A Keynote Discussion — The tone begins confrontational and personal as Hunter-Torricke distances himself from his tech industry past, then shif…
S116
AI and Digital Developments Forecast for 2026 — The tone begins as analytical and educational but becomes increasingly cautionary and urgent throughout the conversation…
S117
WSIS Action Line C10: Ethics in AI: Shaping a Human-Centred Future in the Digital Age — The discussion maintained a collaborative and constructive tone throughout, with speakers building upon each other’s ins…
S118
Closing Ceremony — The discussion maintains a consistently positive and collaborative tone throughout, characterized by gratitude, celebrat…
S119
Closing Session  — The tone throughout the discussion was consistently formal, collaborative, and optimistic. It maintained a celebratory y…
S120
Closing remarks — The tone is consistently celebratory, optimistic, and forward-looking throughout the discussion. It maintains an enthusi…
S121
Open Mic & Closing Ceremony — Hajia Sani: Hmm. Another round of applause, please. Another round of applause. Thank you so much. He just offered that t…
S122
Parliamentary Closing Closing Remarks and Key Messages From the Parliamentary Track — The discussion maintained a collaborative and constructive tone throughout, characterized by diplomatic language and mut…
S123
Bridging the AI innovation gap — LJ Rich: to invite our opening keynote. It’s a pleasure to invite to the stage the director of the Telecommunications St…
S124
AI Policy Summit Opening Remarks: Discussion Report — “The only way you could see that he was communicating with us is that there was a little bit of a tear coming out of his…
S125
Leaders TalkX: WSIS towards the Summit of the Future/GDC and beyond — In the address, the speaker opens by acknowledging and expressing gratitude to prominent individuals and organisations, …
S126
(Plenary segment) Summit of the Future – General Assembly, 4th plenary meeting, 79th session — Sovereign Order of Malta: Mr. Speaker, Heads of State and Government, Excellencies, ladies and gentlemen. The Sovereig…
S127
WS #184 AI in Warfare – Role of AI in upholding International Law — Mohamed Sheikh-Ali emphasizes the necessity of human oversight and control in AI-powered weapons systems. He argues that…
S128
WS #219 Generative AI Llms in Content Moderation Rights Risks — All speakers agree that despite technological advances, human oversight and involvement in content moderation remains cr…
S129
India unveils MANAV Vision as new global pathway for ethical AI — Narendra Modipresentedthe new MANAV Vision during the India AI Impact Summit 2026 in New Delhi, setting out a human-cent…
S130
GLOBAL COMMISSION ON THE FUTURE OF WORK — A strong lifelong learning system, combined with universal social protection, enables workers to assume their responsibi…
S131
Policies and platforms in support of learning: towards more coherence, coordination and convergence — 30. The learning policies of the United Nations system originate in the conditions set out in Article 101 of the Charter…
S132
WSIS+20 High-Level Dialogue: WSIS Legacy in Motion: Honoring the Past, Shaping the Future — Policy frameworks should take a holistic approach across economic, technical, socio-cultural and governance factors
S133
E U R O P E A N E C O N O M I C A R E A — 29 Several EU social partners in different economic sectors have also made joint pledges under the Alliance for Apprenti…
S134
Agenda item 5: discussions on substantive issues contained inparagraph 1 of General Assembly resolution 75/240 (continued)/ part 4 — Islamic Republic of Iran: Thank you, Mr. Chair. We would like to express our sincere appreciation to you, your team, and…
S135
Panel discussion: International law, cyber-norms, CBMs, capacity building,institutional dialogue — Dr Katherine Getao:I do apologize, distinguished delegates, if I was not clear. My fourth one was capacity building, whi…
S136
Opening Ceremony — This comment introduced a critical counternarrative to tech industry talking points and provided a concrete framework fo…
S137
Scaling AI Beyond Pilots: A World Economic Forum Panel Discussion — It find a lot of startups across the world. These startups, they want the injection of funds, but the most important thi…
S138
Keynote-HE Emmanuel Macron — The speech concluded with a powerful reaffirmation of the central thesis: that the future of AI will be built by those w…
S139
Comprehensive Report: “Converging with Technology to Win” Panel Discussion — The discussion began by comparing two major technology ecosystem models: the U.S. approach, driven by university-industr…
S140
Digital Technologies in Emerging Countries Edited by Francis Fukuyama and Marietje Schaake — Techno-nationalism can be broken down into two subcomponents: political-informational and politicaleconomic. Political-i…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
D
Dr. Washima
2 arguments122 words per minute251 words122 seconds
Argument 1
Trust‑based collaborative ethical frameworks (Dr. Washima)
EXPLANATION
Dr. Washima emphasizes that the responsibility of the gathering is to develop trust‑based collaborative ethical frameworks that can guide AI deployment in fast‑paced public services. These frameworks are intended to ensure safety, fairness, and public trust in AI‑driven governance.
EVIDENCE
She states, “Responsibility is to carve out trust-based collaborative ethical frameworks so that the demands of fast-paced dynamic AI-DPD age … is met by a well-informed design and delivery model” [10].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Trust-based frameworks are grounded in shared values and norms as described in [S23], and the emphasis on trust, safety, and accountability in AI governance is highlighted in [S24].
MAJOR DISCUSSION POINT
Trust‑based collaborative ethical frameworks (Dr. Washima)
AGREED WITH
Robin Scott, Dr. Jitendra Singh
DISAGREED WITH
Robin Scott
Argument 2
AI as a transformative tool for improving quality of life, public services, and inclusive growth (Dr. Washima)
EXPLANATION
Dr. Washima likens AI to electricity, describing it as a great leveler that can transform quality of life, governance, and societal progress. She argues that AI should be harnessed to elevate humanity rather than merely scaling technology.
EVIDENCE
She remarks, “Technology, they say, is a great leveler, and AI, they say, is the next big thing after electricity” [4] and later notes that AI gives “unprecedented power not to do things better but to do better things” for education, governance, health, and the planet [66-68].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI is portrayed as a transformative force shaping economies and societies in [S27], and its characterization as a ‘great leveler’ comparable to electricity is echoed in [S2].
MAJOR DISCUSSION POINT
AI as a transformative tool for improving quality of life, public services, and inclusive growth (Dr. Washima)
AGREED WITH
Dr. Jitendra Singh, Subramanian Ramadorai, Speaker 1
S
Shubhavi S. Radha Chauhan
2 arguments115 words per minute886 words460 seconds
Argument 1
Human‑centric “Mani Vision” and sector‑specific small models (Shubhavi S. Radha Chauhan)
EXPLANATION
She highlights the Prime Minister’s “Mani Vision”, a human‑centric framework for ethical, accountable, and inclusive AI governance, and stresses that future AI will rely on small, context‑specific language models rather than massive monolithic ones.
EVIDENCE
She notes, “Our Honorable PM yesterday outlined Mani Vision, a human-centric framework for ethical, accountable and inclusive AI governance” [23] and adds, “It will be in small language models, context-specific, sectoral, and decentralized” [31].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The Mani Vision framework and the shift toward small, context-specific language models are explicitly mentioned in [S2] and reinforced by calls for niche models in [S28].
MAJOR DISCUSSION POINT
Human‑centric “Mani Vision” and sector‑specific small models (Shubhavi S. Radha Chauhan)
AGREED WITH
Subramanian Ramadorai
Argument 2
Customized competency frameworks and personalized learning pathways (Shubhavi S. Radha Chauhan)
EXPLANATION
She describes the development of sector‑specific competency frameworks and personalized learning pathways for public officials, built on holistic policy frameworks that identify competency gaps and tailor learning.
EVIDENCE
She explains, “Capacity building must therefore focus on enabling our officials to deconstruct complexities, impose appropriate guardrails on data and its use…” [33-34] and adds that the Commission has “established operational guidelines, especially those for identifying competency gaps, leading to personalized learning pathways for each one of our learners” [35].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Sector-specific competency frameworks and personalized learning pathways are outlined in [S2] and further detailed in [S16].
MAJOR DISCUSSION POINT
Customized competency frameworks and personalized learning pathways (Shubhavi S. Radha Chauhan)
AGREED WITH
Anil Shivastava, Robin Scott, Speaker 1, Subramanian Ramadorai
G
Guilherme Albusco Almeida
3 arguments121 words per minute613 words302 seconds
Argument 1
South‑South cooperation on civil‑service AI training; four‑tiered capacity‑building profiles (Guilherme Albusco Almeida)
EXPLANATION
Guilherme outlines Brazil’s civil‑service AI training programme, which uses four distinct capacity‑building profiles (senior leaders, IT managers, data curators, general civil servants) and stresses collaboration with India as a South‑South partnership.
EVIDENCE
He states, “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…” [161-166] and notes the partnership with India and similar organisations in Brazil [155-158].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
South-South partnership models for AI capacity building are discussed in [S30], and Guilherme’s Brazil-India collaboration is referenced in [S2].
MAJOR DISCUSSION POINT
South‑South cooperation on civil‑service AI training; four‑tiered capacity‑building profiles (Guilherme Albusco Almeida)
AGREED WITH
Subramanian Ramadorai
Argument 2
Brazil‑India collaboration on R&D, capacity building, and ethical assessment frameworks; South‑South knowledge sharing (Guilherme Albusco Almeida)
EXPLANATION
He emphasizes the complementary strengths of Brazil and India in AI R&D, capacity building, and ethical assessment, proposing joint efforts and leveraging South‑South networks such as Apolitical to scale knowledge.
EVIDENCE
He mentions, “We should consider R&D… there are strong room for cooperation and collaboration” [151-154] and adds, “We have developed a framework for ethical assessment of AI implementation” [161-163] while highlighting partnerships with Apolitical for global knowledge sharing [165].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Joint R&D and ethical assessment initiatives between Brazil and India are highlighted in [S30] and [S2].
MAJOR DISCUSSION POINT
Brazil‑India collaboration on R&D, capacity building, and ethical assessment frameworks; South‑South knowledge sharing (Guilherme Albusco Almeida)
AGREED WITH
Subramanian Ramadorai
Argument 3
Use of AI for climate monitoring, deforestation detection, and reforestation planning (Guilherme Albusco Almeida)
EXPLANATION
Guilherme describes Brazil’s Rural Environmental Registry that uses AI to map private‑land forests, detect illegal logging, and support reforestation, illustrating AI’s role in environmental stewardship.
EVIDENCE
He explains, “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” [209-212].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The environmental impact of AI and its application to climate monitoring are examined in [S36] and [S38], with sustainability considerations noted in [S37].
MAJOR DISCUSSION POINT
Use of AI for climate monitoring, deforestation detection, and reforestation planning (Guilherme Albusco Almeida)
AGREED WITH
Robin Scott, Anil Shivastava
R
Robin Scott
4 arguments150 words per minute452 words180 seconds
Argument 1
Widespread lack of understanding of ethical frameworks among implementers (Robin Scott)
EXPLANATION
Robin reports that a global survey shows only 26 % of AI implementers understand their own government’s ethical frameworks, leaving the majority to operate without clear guidance, which raises risk.
EVIDENCE
She cites, “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” [182-188].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Surveys revealing limited awareness of ethical frameworks and the need for clearer guidance are discussed in [S33] and [S32].
MAJOR DISCUSSION POINT
Widespread lack of understanding of ethical frameworks among implementers (Robin Scott)
AGREED WITH
Dr. Washima, Dr. Jitendra Singh
DISAGREED WITH
Dr. Washima
Argument 2
Survey‑based gaps (ethical awareness, pilot evaluation) and high optimism among public servants (Robin Scott)
EXPLANATION
Robin presents data from an 8,000‑person survey indicating low awareness of ethical frameworks and weak evaluation plans for AI pilots, yet over 90 % of public servants remain optimistic about AI’s potential.
EVIDENCE
She notes, “According to our data, this is an 8,000-person global survey… only 26 % understand ethical frameworks, 75 % freestyling… 72 % say they have a pilot, but only 45 % have a plan to evaluate performance… well over 90 % of public servants are very optimistic” [182-194].
MAJOR DISCUSSION POINT
Survey‑based gaps (ethical awareness, pilot evaluation) and high optimism among public servants (Robin Scott)
Argument 3
Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott)
EXPLANATION
Robin mentions that a dedicated course on AI and climate, developed with the Stanford Doerr School of Sustainability, has been created to educate public servants on the intersection of AI and environmental sustainability.
EVIDENCE
She says, “We have developed a course on AI and climate and understanding the links with the Stanford Doerr School of Sustainability” [201-203].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The push for ‘green AI’ and climate-focused AI education aligns with findings in [S36] and [S38].
MAJOR DISCUSSION POINT
Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott)
AGREED WITH
Guilherme Albusco Almeida, Anil Shivastava
DISAGREED WITH
Anil Shivastava
Argument 4
Global survey highlighting readiness gaps and the need for common evaluation standards (Robin Scott)
EXPLANATION
Robin reiterates findings from the global survey that reveal gaps in ethical framework comprehension and pilot evaluation, arguing that standardized evaluation metrics are essential for responsible AI rollout.
EVIDENCE
She references the same survey data, emphasizing that only 26 % understand ethical frameworks and that many pilots lack evaluation plans, underscoring the need for common standards [182-190].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Calls for standardized ethical evaluation metrics are echoed in [S33] and the regulatory gaps noted in [S32].
MAJOR DISCUSSION POINT
Global survey highlighting readiness gaps and the need for common evaluation standards (Robin Scott)
D
Dr. Jitendra Singh
3 arguments144 words per minute2236 words927 seconds
Argument 1
Integrity and human‑in‑the‑loop as non‑negotiable (Dr. Jitendra Singh)
EXPLANATION
Dr. Singh stresses that AI systems must operate with integrity and always keep a human in the decision‑making loop; this is presented as a non‑negotiable principle for trustworthy AI governance.
EVIDENCE
He declares, “Artificial intelligence can substitute everything on this planet but it cannot substitute integrity… the basic mantra is to learn to be a good learner and human-in-the-loop is essential” [324-327].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The non-negotiable nature of integrity and human oversight is reinforced by trust and accountability themes in [S23] and [S24].
MAJOR DISCUSSION POINT
Integrity and human‑in‑the‑loop as non‑negotiable (Dr. Jitendra Singh)
AGREED WITH
Dr. Washima, Robin Scott
Argument 2
Hybrid models that combine AI tools with human judgment; AI as an augmenting, not substituting, technology (Dr. Jitendra Singh)
EXPLANATION
He describes AI as an augmenting technology that should work alongside human expertise, forming hybrid models where human judgment guides AI outputs, thereby preserving integrity and accountability.
EVIDENCE
He states, “AI is a powerful tool… we must learn to be a good learner… hybrid model… AI as augmenting, not substituting” [323-327].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Hybrid human-AI models are advocated in responsible AI governance discussions in [S24].
MAJOR DISCUSSION POINT
Hybrid models that combine AI tools with human judgment; AI as an augmenting, not substituting, technology (Dr. Jitendra Singh)
Argument 3
AI as a catalyst for citizen‑centred, accountable governance while preserving human values (Dr. Jitendra Singh)
EXPLANATION
Dr. Singh portrays AI as a catalyst that can enable citizen‑centred, accountable governance, provided that human values, integrity, and ethical oversight remain central to its deployment.
EVIDENCE
He remarks, “AI is a catalyst for citizen-centred, accountable governance while preserving human values” and elaborates on the need for integrity, accountability, and human oversight throughout his address [291-298] and [300-307].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI’s role in inclusive, citizen-focused governance is highlighted in the AI Impact Summit report [S25] and its transformative potential in [S27].
MAJOR DISCUSSION POINT
AI as a catalyst for citizen‑centred, accountable governance while preserving human values (Dr. Jitendra Singh)
AGREED WITH
Dr. Washima, Subramanian Ramadorai, Speaker 1
A
Anil Shivastava
3 arguments145 words per minute671 words275 seconds
Argument 1
Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava)
EXPLANATION
Anil explains that existing IT systems are siloed and built for past technologies, requiring re‑engineering of data, processes, multilingual capabilities, and security to enable effective AI integration.
EVIDENCE
He notes, “Existing IT systems are very centric… they have silos of data… AI needs contextual data… we need to re-engineer… also need to ensure multilingual support… and address data-sovereignty and security vectors” [126-138].
MAJOR DISCUSSION POINT
Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava)
AGREED WITH
Shubhavi S. Radha Chauhan, Robin Scott, Speaker 1, Subramanian Ramadorai
DISAGREED WITH
Subramanian Ramadorai
Argument 2
Legacy IT systems are siloed; AI requires re‑engineering of data, processes, and security controls (Anil Shivastava)
EXPLANATION
He reiterates that legacy systems contain siloed data and business logic, which must be restructured to provide the contextual, secure data streams AI models need.
EVIDENCE
He describes, “The existing IT systems are very centric… they have silos of data, silos of business logic, whereas AI needs contextual data… we also need to re-look at exposure and security vectors” [126-138].
MAJOR DISCUSSION POINT
Legacy IT systems are siloed; AI requires re‑engineering of data, processes, and security controls (Anil Shivastava)
Argument 3
Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava)
EXPLANATION
Anil highlights Google’s pledge to make all its data centres carbon neutral by 2030 and expresses willingness to partner with the Indian government to set similar sustainability targets.
EVIDENCE
He says, “Google, first of all, has committed that by 2030, all our data centers will be carbon neutral… we want to partner with the government of India to ensure that all the data centres we are building in the country have targets to ensure carbon neutrality” [215-218].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Sustainability goals for AI infrastructure, including carbon-neutral data centres, are discussed in [S36] and [S37].
MAJOR DISCUSSION POINT
Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava)
AGREED WITH
Robin Scott, Guilherme Albusco Almeida
DISAGREED WITH
Robin Scott
S
Subramanian Ramadorai
3 arguments140 words per minute1223 words520 seconds
Argument 1
Blueprint for a Digital Capacity Building Alliance and global funding model (Subramanian Ramadorai)
EXPLANATION
Subramanian calls for operationalising the proposed alliance, referencing a blueprint for digital capacity‑building labs that outlines shared work for AI development and funding across nations.
EVIDENCE
He says, “Let us take this convention forward to see how the proposed alliance can be operationalized… the Summit Master launched a blueprint for digital capacity building and labs that sets out the share of fair work for developing AI” [104-105].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The concept of a global digital capacity-building alliance aligns with South-South partnership frameworks in [S30] and the inclusive AI agenda of the 2026 summit in [S25].
MAJOR DISCUSSION POINT
Blueprint for a Digital Capacity Building Alliance and global funding model (Subramanian Ramadorai)
AGREED WITH
Shubhavi S. Radha Chauhan, Anil Shivastava, Robin Scott, Speaker 1
Argument 2
Emphasis on edge AI and small, domain‑specific language models for rural and local contexts (Subramanian Ramadorai)
EXPLANATION
He points out that the next billion AI users will interact with tiny embedded AI on devices, and that India’s rural opportunity lies in small, domain‑specific language models that can run on edge hardware.
EVIDENCE
He notes, “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… India’s rural opportunity lies in small language models that are absolutely domain specific and can run on edge devices” [96-98].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Calls for small, domain-specific models for edge deployment are made in [S28] and reinforced by the focus on small models in [S2].
MAJOR DISCUSSION POINT
Emphasis on edge AI and small, domain‑specific language models for rural and local contexts (Subramanian Ramadorai)
AGREED WITH
Shubhavi S. Radha Chauhan
DISAGREED WITH
Anil Shivastava
Argument 3
India’s “third way” partnership model positioning itself between US‑led and China‑led AI trajectories (Subramanian Ramadorai)
EXPLANATION
He frames India’s AI strategy as a “third way”, offering a partnership‑based approach that is distinct from the market‑driven US model and the state‑led Chinese model.
EVIDENCE
He states, “Globally, AI is framed as a binary race… However, it might lend India offers a third way, in partnership, of course” [74-76].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The ‘third way’ partnership approach is reflected in the Global South collaboration narrative of [S30] and the inclusive AI development goals of [S25].
MAJOR DISCUSSION POINT
India’s “third way” partnership model positioning itself between US‑led and China‑led AI trajectories (Subramanian Ramadorai)
AGREED WITH
Guilherme Albusco Almeida
S
Speaker 1
2 arguments114 words per minute284 words149 seconds
Argument 1
Launch of the Digital Capacity Building Alliance as a public‑good platform (Speaker 1)
EXPLANATION
Speaker 1 announces the unveiling of a Digital Capacity Building Alliance that integrates global AI principles, digital public‑good standards, and a mission‑cum‑worthy model, positioning it as a public‑good resource for capacity building.
EVIDENCE
He declares, “Today, the Capacity Building Commission unveiled a proposal to forge Digital Capacity Building Allowance… a unique model for demand, design, delivery, and continued evolution… a global public good for inclusive, ethical capacity building” [263-270].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The public-good capacity-building platform mirrors alliance concepts described in [S30] and the AI summit’s emphasis on shared resources in [S25].
MAJOR DISCUSSION POINT
Launch of the Digital Capacity Building Alliance as a public‑good platform (Speaker 1)
Argument 2
AI‑enabled governments with personalized decision support, moving from reactive to adaptive capacity models (Speaker 1)
EXPLANATION
Speaker 1 describes AI‑enabled governments that provide personalized learning paths and smart decision support, shifting public service delivery from reactive systems to adaptive capacity models.
EVIDENCE
He says, “AI-enabled governments, personalized learning paths, smart decision support, from reactive systems to adaptive capacity model” [258-262].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Personalized learning pathways and adaptive decision support are discussed in [S28] and [S16].
MAJOR DISCUSSION POINT
AI‑enabled governments with personalized decision support, moving from reactive to adaptive capacity models (Speaker 1)
M
Moderator
1 argument96 words per minute632 words393 seconds
Argument 1
Moderator’s framing of questions that link technical risks to capacity‑building needs (Moderator)
EXPLANATION
The moderator asks about technical and operational risks of layering AI onto legacy infrastructure and how initiatives can align infrastructure modernization with workforce capability development.
EVIDENCE
He asks, “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?” [110-112].
MAJOR DISCUSSION POINT
Moderator’s framing of questions that link technical risks to capacity‑building needs (Moderator)
S
Speaker 3
1 argument77 words per minute9 words6 seconds
Argument 1
Speaker 3’s prompt for audience interaction to surface additional concerns (Speaker 3)
EXPLANATION
Speaker 3 invites the audience to ask another question, encouraging further engagement and surfacing of concerns.
EVIDENCE
He says, “one more question here last question please thank you” [245].
MAJOR DISCUSSION POINT
Speaker 3’s prompt for audience interaction to surface additional concerns (Speaker 3)
A
Audience
1 argument144 words per minute364 words151 seconds
Argument 1
Call for a generic, hyper‑localizable international AI impact assessment framework (Audience)
EXPLANATION
An audience member proposes developing a collaborative, generic AI impact assessment tool that can be hyper‑localized to different national contexts.
EVIDENCE
The participant says, “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” [246].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The need for adaptable AI impact assessment tools is highlighted in the regulatory discussion of [S32] and the ethical foresight challenges in [S33].
MAJOR DISCUSSION POINT
Call for a generic, hyper‑localizable international AI impact assessment framework (Audience)
Agreements
Agreement Points
Need for trustworthy ethical frameworks and integrity in AI governance
Speakers: Dr. Washima, Robin Scott, Dr. Jitendra Singh
Trust‑based collaborative ethical frameworks (Dr. Washima) Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Integrity and human‑in‑the‑loop as non‑negotiable (Dr. Jitendra Singh)
All three speakers stress that AI systems must be anchored in trustworthy, collaborative ethical frameworks and that integrity with a human-in-the-loop is non-negotiable for trustworthy AI deployment. Dr. Washima calls for trust-based collaborative frameworks [10]; Robin points out that only 26 % of implementers understand their government’s ethical frameworks, leaving most to “freestyle” [182-188]; Dr. Singh emphasizes integrity and the necessity of keeping a human in the decision-making loop [324-327].
POLICY CONTEXT (KNOWLEDGE BASE)
This aligns with calls for transparency and explainability as ethical imperatives highlighted at the IGF high-level session on AI ethics [S55] and reflects the broader consensus that AI must be governed with integrity, as emphasized in discussions on enhancing rather than replacing humanity [S71].
AI as a transformative catalyst for inclusive, citizen‑centred development
Speakers: Dr. Washima, Dr. Jitendra Singh, Subramanian Ramadorai, Speaker 1
AI as a transformative tool for improving quality of life, public services, and inclusive growth (Dr. Washima) AI as a catalyst for citizen‑centred, accountable governance while preserving human values (Dr. Jitendra Singh) AI for economic development, social good, safe and trusted AI, and human capital (Subramanian Ramadorai) AI‑enabled governments, personalized learning paths, smart decision support, from reactive systems to adaptive capacity model (Speaker 1)
The speakers converge on the view that AI should be leveraged as a societal lever rather than a mere technology. Dr. Washima likens AI to a “great leveler” that can improve quality of life [4][66-68]; Dr. Singh describes AI as a catalyst for citizen-centred, accountable governance while preserving human values [291-298]; Subramanian notes the summit theme of AI for economic development and social good [11]; Speaker 1 outlines AI-enabled governments delivering personalized decision support and shifting from reactive to adaptive capacity models [258-262].
POLICY CONTEXT (KNOWLEDGE BASE)
The view mirrors the optimism expressed at the AI Impact Summit 2026 that AI can be a catalyst for inclusive development in the Global South [S78] and the emphasis on citizen-centred public-service transformation noted in Rwanda’s digital inclusion strategy [S67].
Preference for small, sector‑specific or edge AI models over monolithic systems
Speakers: Shubhavi S. Radha Chauhan, Subramanian Ramadorai
Human‑centric “Mani Vision” and sector‑specific small models (Shubhavi S. Radha Chauhan) Emphasis on edge AI and small, domain‑specific language models for rural and local contexts (Subramanian Ramadorai)
Both speakers argue that the future of AI lies in lightweight, context-specific models rather than massive monolithic ones. Shubhavi states that AI will move to “small language models, context-specific, sectoral, and decentralized” [31]; Subramanian highlights the opportunity of “tiny embedded AI” on phones, tractors, classrooms and domain-specific models for rural users [96-98].
Capacity building through customized competency frameworks and personalized learning pathways
Speakers: Shubhavi S. Radha Chauhan, Anil Shivastava, Robin Scott, Speaker 1, Subramanian Ramadorai
Customized competency frameworks and personalized learning pathways (Shubhavi S. Radha Chauhan) Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava) Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott) AI‑enabled governments, personalized learning paths, smart decision support, from reactive systems to adaptive capacity model (Speaker 1) Blueprint for a Digital Capacity Building Alliance and global funding model (Subramanian Ramadorai)
A shared emphasis emerges on building human capacity with tailored frameworks and learning routes. Shubhavi describes sector-specific competency frameworks and personalized pathways for officials [33-35]; Anil stresses re-engineering legacy systems, multilingual support and data-sovereignty as prerequisites for effective AI uptake [126-138]; Robin notes the creation of an AI-and-climate training course as part of broader capacity-building efforts [201-203]; Speaker 1 highlights personalized learning paths as a core feature of AI-enabled governments [258-262]; Subramanian references a blueprint for a digital capacity-building alliance that will scale such pathways [104-105].
POLICY CONTEXT (KNOWLEDGE BASE)
Capacity building is framed as an engine of innovation in the ‘AI for Viksit Bharat 2047’ roadmap, which advocates personalized learning pathways and continuous feedback loops [S51]; similar recommendations appear in the AI Policy Research Roadmap that stresses raising awareness and competency across public-sector actors [S66].
South‑South collaboration between Brazil and India on AI R&D, capacity building and ethical frameworks
Speakers: Guilherme Albusco Almeida, Subramanian Ramadorai
South‑South cooperation on civil‑service AI training; four‑tiered capacity‑building profiles (Guilherme Albusco Almeida) Brazil‑India collaboration on R&D, capacity building, and ethical assessment frameworks; South‑South knowledge sharing (Guilherme Albusco Almeida) India’s “third way” partnership model positioning itself between US‑led and China‑led AI trajectories (Subramanian Ramadorai)
Both speakers advocate for a collaborative South-South approach. Guilherme outlines Brazil’s four-tiered civil-service AI training model and calls for deeper Brazil-India R&D and ethical-assessment cooperation, noting partnerships with Apolitical [151-158][165]; Subramanian frames India’s “third way” partnership as a collaborative alternative to the US-China binary, positioning India as a partner for other nations [74-76].
POLICY CONTEXT (KNOWLEDGE BASE)
South-South cooperation is highlighted as a priority in the AI Impact Summit 2026, calling for open, non-discriminatory norms and joint research initiatives among Global South countries [S63], providing a policy backdrop for bilateral Brazil-India collaboration.
Integration of environmental sustainability into AI initiatives
Speakers: Robin Scott, Guilherme Albusco Almeida, Anil Shivastava
Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott) Use of AI for climate monitoring, deforestation detection, and reforestation planning (Guilherme Albusco Almeida) Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava)
All three speakers link AI work to climate and sustainability goals. Robin reports a dedicated AI-and-climate course developed with the Stanford Doerr School of Sustainability [201-203]; Guilherme describes Brazil’s AI-driven Rural Environmental Registry that monitors forests and supports reforestation [209-212]; Anil highlights Google’s pledge to make all data centres carbon-neutral by 2030 and its willingness to partner with India on sustainable infrastructure [215-218].
POLICY CONTEXT (KNOWLEDGE BASE)
Multiple policy statements link AI to climate action, including the IGF networking session on AI and Environment that notes AI’s role in sustainable energy systems [S54], UNESCO’s call for AI to support climate goals [S60], and Germany’s AI Flagship Projects for the Environment that fund climate-focused AI solutions [S57]; together they underscore the need to embed sustainability in AI programmes.
Similar Viewpoints
All three highlight that technical and operational challenges of layering AI onto legacy systems must be addressed through targeted capacity‑building, governance reforms and structured alliances. The moderator explicitly asks about technical risks and capacity‑building alignment [110-112]; Anil stresses re‑engineering legacy IT, multilingual support and security as capacity‑building imperatives [126-138]; Subramanian presents a blueprint for a digital capacity‑building alliance that would tackle such risks [104-105].
Speakers: Moderator, Anil Shivastava, Subramanian Ramadorai
Moderator’s framing of questions that link technical risks to capacity‑building needs (Moderator) Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava) Blueprint for a Digital Capacity Building Alliance and global funding model (Subramanian Ramadorai)
Both call for systematic evaluation mechanisms for AI pilots. Robin points out that many pilots lack evaluation plans and stresses the need for common standards [188-190]; Subramanian’s alliance blueprint includes provisions for evaluation frameworks to ensure responsible AI rollout [104-105].
Speakers: Robin Scott, Subramanian Ramadorai
Global survey highlighting readiness gaps and the need for common evaluation standards (Robin Scott) Blueprint for a Digital Capacity Building Alliance and global funding model (Subramanian Ramadorai)
Unexpected Consensus
Call for a generic, hyper‑localizable international AI impact assessment framework
Speakers: Audience, Dr. Washima, Robin Scott, Shubhavi S. Radha Chauhan
Call for a generic, hyper‑localizable international AI impact assessment framework (Audience) Trust‑based collaborative ethical frameworks (Dr. Washima) Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Customized competency frameworks and personalized learning pathways (Shubhavi S. Radha Chauhan)
An audience member’s suggestion to create a generic, hyper‑localizable AI impact assessment tool mirrors the ethical‑framework focus of Dr. Washima, the survey‑driven gaps highlighted by Robin, and Shubhavi’s push for customized competency frameworks, showing an unexpected convergence between a non‑speaker input and multiple speakers’ positions.
POLICY CONTEXT (KNOWLEDGE BASE)
The need for a clear, implementable assessment tool echoes critiques of the Global Digital Compact for lacking concrete mechanisms [S70] and the broader call for evidence-based approaches to bridge policy-practice gaps in digital cooperation [S69].
Alignment of AI development with climate responsibility
Speakers: Robin Scott, Guilherme Albusco Almeida, Anil Shivastava
Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott) Use of AI for climate monitoring, deforestation detection, and reforestation planning (Guilherme Albusco Almeida) Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava)
Although each speaker approaches climate from a different angle—education (Robin), operational AI for forest monitoring (Guilherme), and sustainable data‑centre infrastructure (Anil)—they all converge on the principle that AI initiatives must be environmentally responsible, an alignment that was not explicitly pre‑planned.
POLICY CONTEXT (KNOWLEDGE BASE)
UNESCO’s renewed appeal for AI to align with climate responsibility [S60] and Bouverot’s remarks on ensuring AI progress matches environmental protection goals [S58] provide authoritative framing for this alignment.
Overall Assessment

The discussion shows strong convergence on several fronts: the necessity of trustworthy ethical frameworks and human‑in‑the‑loop integrity; AI as a catalyst for inclusive, citizen‑centred development; a shift toward small, edge‑oriented models; extensive capacity‑building through customized competency frameworks and personalized learning; South‑South partnership models, especially Brazil‑India cooperation; and embedding climate‑sustainability into AI programmes.

High consensus – most speakers echo each other’s core positions, indicating a solid shared foundation that can facilitate coordinated policy actions, joint programmes and the launch of the Digital Capacity Building Alliance.

Differences
Different Viewpoints
Gap between the aspiration for trust‑based collaborative ethical frameworks and the current low awareness of existing ethical frameworks among implementers
Speakers: Robin Scott, Dr. Washima
Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Trust‑based collaborative ethical frameworks (Dr. Washima)
Robin reports that only 26 % of AI implementers understand their own government’s ethical frameworks, indicating a large implementation gap [182-188]. Dr. Washima, however, calls for the creation of trust-based collaborative ethical frameworks to guide AI deployment, implying that such frameworks are not yet established or widely understood [10]. This reflects a disagreement between the current state of awareness and the envisioned governance model.
POLICY CONTEXT (KNOWLEDGE BASE)
The AI Policy Research Roadmap identifies a persistent awareness gap among practitioners [S66], while the Open Forum on Digital Cooperation highlighted implementation gaps between policy intent and on-the-ground understanding [S69].
Resource allocation for climate‑focused AI initiatives
Speakers: Anil Shivastava, Robin Scott
Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava) Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott)
Anil highlights a concrete corporate commitment and a partnership model to achieve carbon-neutral data centres by 2030, suggesting that sufficient resources are being mobilised [215-218]. Robin mentions a newly developed AI-climate course but adds that it “has too much money”, indicating concerns about funding adequacy for such initiatives [201-203]. The two positions differ on whether the necessary financial resources are already in place or remain a constraint.
POLICY CONTEXT (KNOWLEDGE BASE)
Funding mechanisms such as Germany’s AI Flagship for climate and the ‘Make Your AI Greener’ workshop stress dedicated resources for climate-oriented AI projects [S57][S56], and Bouverot’s closing remarks call for financing that matches environmental ambitions [S58].
Approach to enabling AI in public services – extensive re‑engineering of legacy systems versus deployment of lightweight edge models
Speakers: Anil Shivastava, Subramanian Ramadorai
Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava) Emphasis on edge AI and small, domain‑specific language models for rural and local contexts (Subramanian Ramadorai)
Anil argues that existing IT systems are siloed and must be re-engineered, with attention to multilingual data and security, before AI can be effectively integrated [126-138]. Subramanian stresses that the next billion AI users will interact with tiny embedded AI on edge devices and that small, domain-specific models are the primary opportunity for rural India, without explicitly calling for large-scale re-engineering [96-98]. The disagreement lies in the depth of systemic change required to enable AI.
Unexpected Differences
Optimism about AI’s transformative potential versus caution about its inability to replace human integrity
Speakers: Robin Scott, Dr. Jitendra Singh
Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Integrity and human‑in‑the‑loop as non‑negotiable (Dr. Jitendra Singh)
Robin expresses strong optimism, noting that over 90 % of public servants are very optimistic about AI’s role despite current gaps [190-194]. Dr. Singh, while supportive, warns that AI cannot substitute integrity and must always retain a human-in-the-loop, suggesting a more cautious stance on AI autonomy [324-327]. The contrast between high optimism and a firm warning about non-negotiable human oversight was not anticipated given the overall collaborative tone of the session.
POLICY CONTEXT (KNOWLEDGE BASE)
Debates on enhancing rather than replacing humanity capture this tension, with experts arguing AI should augment human values and not supplant ethical judgment [S71].
Different perceptions of funding adequacy for climate‑focused AI initiatives
Speakers: Anil Shivastava, Robin Scott
Google’s commitment to carbon‑neutral data centres by 2030 and partnership with India for sustainable infrastructure (Anil Shivastava) Development of an AI‑and‑climate course and promotion of “green AI” principles (Robin Scott)
Anil presents a concrete corporate pledge and partnership indicating sufficient funding for sustainable AI infrastructure [215-218]. Robin, however, remarks that the AI-climate course “has too much money”, implying financial constraints or insufficient budgeting for such programs [201-203]. The divergence in perceived funding sufficiency was unexpected given the shared emphasis on sustainability.
Overall Assessment

The discussion showed broad consensus on the importance of capacity building, ethical governance, and South‑South collaboration for AI in the public sector. Disagreements were mainly technical and implementation‑focused, such as the current awareness of ethical frameworks, the depth of system re‑engineering required, and the allocation of resources for climate‑related AI initiatives. These divergences reflect differing institutional perspectives (government vs. private sector vs. academia) rather than fundamental ideological conflict.

Moderate – while all participants share the same overarching goals (ethical, inclusive, and sustainable AI deployment), they differ on how to achieve them. The disagreements are likely to shape policy priorities, with potential implications for the speed of implementation, the design of capacity‑building programs, and the financing of green AI projects.

Partial Agreements
All speakers concur that capacity building is essential for responsible AI deployment and that tailored learning pathways, competency frameworks, and collaborative platforms are needed. They differ on the specific mechanisms (e.g., sector‑specific small models vs. re‑engineering legacy systems vs. South‑South training structures), but share the overarching goal of strengthening public‑sector AI capabilities [10][33-34][126-138][155-166][182-194][263-270].
Speakers: Dr. Washima, Shubhavi S. Radha Chauhan, Anil Shivastava, Guilherme Albusco Almeida, Robin Scott, Subramanian Ramadorai, Speaker 1
Trust‑based collaborative ethical frameworks (Dr. Washima) Customized competency frameworks and personalized learning pathways (Shubhavi S. Radha Chauhan) Need to re‑engineer legacy processes, ensure multilingual support, and address data‑sovereignty (Anil Shivastava) South‑South cooperation on civil‑service AI training; four‑tiered capacity‑building profiles (Guilherme Albusco Almeida) Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Emphasis on edge AI and small, domain‑specific language models for rural and local contexts (Subramanian Ramadorai) Launch of the Digital Capacity Building Alliance as a public‑good platform (Speaker 1)
All three stress that AI systems must operate under strong ethical oversight and human involvement. Dr. Singh explicitly states that AI cannot replace integrity and must keep a human in the loop [324-327]; Robin highlights the current deficiency in ethical‑framework awareness [182-188]; Dr. Washima calls for trust‑based collaborative frameworks to ensure safety and fairness [10]. They agree on the necessity of ethical governance, differing only in the description of the current gap versus the desired structure.
Speakers: Dr. Jitendra Singh, Robin Scott, Dr. Washima
Integrity and human‑in‑the‑loop as non‑negotiable (Dr. Jitendra Singh) Widespread lack of understanding of ethical frameworks among implementers (Robin Scott) Trust‑based collaborative ethical frameworks (Dr. Washima)
Both advocate for a collaborative, partnership‑based approach that avoids the binary US/China AI race. Guilherme emphasizes Brazil‑India cooperation and South‑South knowledge sharing [155-166]; Subramanian describes India’s third‑way model as a partnership alternative to the two dominant models [74-76]. They share the goal of multilateral cooperation, differing only in the framing of the partnership.
Speakers: Guilherme Albusco Almeida, Subramanian Ramadorai
South‑South cooperation on civil‑service AI training; four‑tiered capacity‑building profiles (Guilherme Albusco Almeida) India’s “third way” partnership model positioning itself between US‑led and China‑led AI trajectories (Subramanian Ramadorai)
Takeaways
Key takeaways
Ethical, human‑centric AI governance is essential; trust‑based collaborative frameworks and a “Mani Vision” were emphasized. Capacity building for public‑sector AI must use customized competency frameworks, personalized learning pathways, and continuous feedback loops. Legacy IT systems are siloed; successful AI integration requires re‑engineering data, processes, security, and multilingual support, with a focus on edge AI and small, sector‑specific language models. International South‑South cooperation (e.g., India‑Brazil) is seen as a viable “third way” to shape global AI norms, share R&D, and co‑develop training programmes. Environmental sustainability must accompany AI deployment; green AI principles, carbon‑neutral data centres, and AI for climate monitoring were highlighted. AI is positioned as a catalyst for socio‑economic development and improved public service delivery, but human‑in‑the‑loop integrity remains non‑negotiable.
Resolutions and action items
Launch of the Digital Capacity Building Alliance (public‑good platform) and its accompanying Blueprint for a Digital Capacity Building Allowance. Commitment by Google to achieve carbon‑neutral data centres by 2030 and to partner with the Indian government on sustainable AI infrastructure. Agreement to develop sector‑specific, small language models that can run on edge devices for rural and local contexts. Plan to embed AI within workforce transformation frameworks and to contribute to shaping global responsible‑AI norms. Proposal to create a generic, hyper‑localizable international AI impact assessment framework/tool (raised by audience). Continuation of large‑scale AI training for public servants (e.g., 1 million target through Apolitical partnership, 400 000 already trained).
Unresolved issues
Concrete operational details for the Digital Capacity Building Alliance and its funding mechanisms remain undefined. Specific technical‑operational steps to align legacy infrastructure modernization with workforce capability development were not fully addressed. Standardized processes for evaluating AI pilots and measuring outcomes are still lacking. A universally accepted international AI procurement and ethical‑framework guideline has not been established. Detailed actions for ensuring climate‑responsible AI beyond high‑level commitments were not specified. Audience concerns about the timeline for achieving AI‑driven governance goals (e.g., 2047 vs. 2026) were not resolved.
Suggested compromises
Adoption of hybrid models that combine AI tools with human judgment, ensuring integrity while leveraging technology. Preference for small, domain‑specific AI models over massive monolithic models to balance capability, resource use, and sustainability. India’s “third way” partnership model positioned as a middle path between US market‑led AI development and China’s state‑led techno‑nationalism.
Thought Provoking Comments
Technology is a great leveler, and AI is the next big thing after electricity. We must carve out trust‑based collaborative ethical frameworks so that the fast‑paced AI‑DPD age delivers safer public services.
Sets the philosophical foundation of the whole summit, framing AI not just as a technology but as a societal equalizer that requires trust and ethics.
Established the central theme of trust and ethics, prompting subsequent speakers to address governance, capacity building, and the need for ethical frameworks throughout the discussion.
Speaker: Dr. Washima
The future of AI will not be in massive monolithic models. It will be in small language models, context‑specific, sectoral, and decentralized.
Introduces a paradigm shift from large, generic AI models to localized, domain‑specific models, highlighting scalability and relevance for diverse Indian contexts.
Steered the conversation toward edge AI and multilingual capabilities, leading Anil Shivastava to discuss re‑engineering legacy systems for multilingual AI and Guilherme Almeida to emphasize Brazil‑India collaboration on small, sector‑specific models.
Speaker: Shubhavi S. Radha Chauhan
The most important question for this summit is not how far we can scale AI but how we can recognize it as a movement that elevates humanity. India can offer a ‘third way’—a partnership model between the US‑led market race and China’s techno‑nationalism.
Broadens the debate from technical scaling to geopolitical positioning and ethical purpose, positioning India as a potential bridge in global AI governance.
Reframed the dialogue from pure technology to strategic policy, influencing later remarks about India’s 5.8 million IT professionals, the need for inclusive capacity building, and Robin Scott’s focus on global norms.
Speaker: Subramanian Ramadorai
AI is not a layer you can just put on existing systems. Existing IT systems have data and business‑logic silos; to harness AI we must re‑engineer those systems, ensure multilingual data, and address security and data‑sovereignty vectors.
Provides a concrete technical critique of naïve AI integration, highlighting practical challenges that many policymakers overlook.
Prompted deeper discussion on the necessity of redesigning legacy infrastructure, reinforced Shubhavi’s point on sector‑specific models, and set the stage for Robin’s data on governance gaps.
Speaker: Anil Shivastava
Only 26 % of public‑sector AI implementers say they understand their own government’s ethical framework; 75 % are essentially freestyling. Moreover, while 72 % plan pilots, only 45 % have an evaluation plan.
Introduces hard data that quantifies the ethical and evaluative gaps in AI adoption, turning abstract concerns into measurable shortcomings.
Shifted the conversation from aspirational goals to urgent accountability, leading the moderator and other panelists to stress the need for standardized frameworks and evaluation mechanisms.
Speaker: Robin Scott
We have developed a course on AI and climate in partnership with the Stanford Doerr School of Sustainability – a concrete step to align AI‑driven public infrastructure with climate responsibility.
Links AI capacity building directly to environmental sustainability, expanding the scope of the discussion to include climate impact.
Opened a new sub‑topic on green AI, prompting Guilherme Almeida and Anil Shivastava to discuss energy‑efficient models and carbon‑neutral data centers.
Speaker: Robin Scott
Integrity cannot be substituted by AI; human‑in‑the‑loop is essential. Digital public good is simply public good delivered through digital means – the technology is a tool, not the end.
Re‑emphasizes the primacy of human values over technology, summarizing the summit’s ethical thrust and introducing the memorable M‑A‑N‑A‑A acronym for AI governance.
Culminated the discussion by reinforcing earlier ethical themes, providing a memorable framework that resonated with the audience and tied together the various strands of capacity building, governance, and sustainability.
Speaker: Dr. Jitendra Singh
Overall Assessment

The discussion was shaped by a series of pivotal remarks that moved the dialogue from high‑level optimism to concrete challenges and solutions. Dr. Washima’s opening set a trust‑centric agenda, which was sharpened by Shubhavi’s vision of decentralized, sector‑specific AI and reinforced by Subramanian’s geopolitical framing of India’s ‘third way.’ Anil’s technical critique grounded the conversation in implementation realities, while Robin’s data‑driven gaps forced participants to confront the lack of ethical awareness and evaluation. Subsequent comments on climate‑aligned AI and Dr. Singh’s insistence on human integrity provided actionable pathways and a unifying ethical narrative. Together, these comments redirected the flow from abstract enthusiasm to a focused, multi‑dimensional roadmap for responsible AI capacity building.

Follow-up Questions
What technical and operational risks arise when AI systems are layered onto legacy infrastructure, and how can initiatives like Mission Community align infrastructure modernization with workforce capability development?
Understanding integration challenges and capacity‑building alignment is essential for safe, effective AI deployment in government services.
Speaker: Subramanian Ramadorai (to Anil Shivastava)
How can Brazil and India collaborate more closely to shape the global conversation around AI trust, alignment, and governance, and which collaborative areas would have the greatest global impact as AI becomes more autonomous?
Leveraging complementary strengths of the two nations can help define international norms and accelerate responsible AI adoption.
Speaker: Subramanian Ramadorai (to Guilherme Albusco Almeida)
What are the biggest gaps in AI readiness within public institutions, and how can the global conversation be shifted toward work reinvention?
Identifying readiness gaps and promoting new work models are critical for scaling AI responsibly in the public sector.
Speaker: Subramanian Ramadorai (to Robin Scott)
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?
Addressing the environmental footprint of large‑scale AI deployments is necessary to meet sustainability goals.
Speaker: Subramanian Ramadorai (to panel)
Can we develop a generic, collaborative international AI impact framework assessment tool—building on UNESCO’s competence framework—that can be hyper‑localized to national contexts and assess capabilities across whole organizations or countries?
A unified assessment tool would help standardize AI governance, procurement, and competence evaluation worldwide.
Speaker: Audience member (Prof. Charu, Indian Institute of Public Administration)
How can governments ensure systematic evaluation of AI pilots, given the gap between pilot implementation and performance assessment identified in surveys?
Without robust evaluation, pilots risk failing to deliver intended outcomes and may introduce unchecked risks.
Speaker: Robin Scott (observed from 8,000‑person survey)
What research is needed to develop sector‑specific, small language models that can run on edge devices for rural and underserved contexts?
Tailored, low‑resource models are crucial for delivering AI benefits to the next billion users in remote areas.
Speaker: Subramanian Ramadorai (statement)
How can public servants improve their understanding of existing governmental ethical AI frameworks to reduce the 75 % ‘freestyling’ risk?
Increasing awareness of ethical guidelines is vital to mitigate misuse and build trust in AI systems.
Speaker: Robin Scott (survey data)
What security and data‑sovereignty challenges arise from integrating AI into existing government IT systems, and how should they be addressed?
AI introduces new attack vectors and data‑privacy concerns that must be mitigated for safe deployment.
Speaker: Anil Shivastava
How can AI be leveraged for environmental sustainability (green AI) and for enhancing climate‑policy decision‑making, such as forest monitoring and reforestation?
Exploring AI’s dual role in reducing its own carbon footprint and supporting climate actions can amplify its societal benefit.
Speaker: Guilherme Albusco Almeida
What mechanisms ensure that AI systems retain human‑in‑the‑loop integrity and do not compromise ethical standards?
Maintaining human oversight is essential to preserve accountability, moral judgment, and public trust.
Speaker: Dr. Jitendra Singh
How can countries develop localized ethical assessment frameworks for AI implementation that complement global standards?
Context‑specific ethical guidelines are needed to address cultural, legal, and societal nuances.
Speaker: Guilherme Albusco Almeida
Should India aim to achieve its AI‑driven governance vision by 2047, and what concrete roadmap is required to avoid procrastination?
Clarifying timelines and actionable steps is critical to meet long‑term national AI objectives.
Speaker: Audience member (unnamed, referencing doomsday clock)

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.