The following are the outputs of the captioning taken during an IGF intervention. Although it is largely accurate, in some cases it may be incomplete or inaccurate due to inaudible passages or transcription errors. It is posted as an aid, but should not be treated as an authoritative record.
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>> ABHISHEK AGARWAL: Good afternoon, Excellencies, distinguished speakers, colleagues, and friends.
A very warm welcome to all of you joining us today both in person here in Oslo and virtually for this session Catalyzing AI impact: The role of international cooperation. This is like the session is like the AI Impact Summit that India will be hosting next year. And the Impact Summit will be held on 19th and 20th of February next year.
The Summit aims to forge connective pathways towards inclusive development related to AI grounded in the overarching team as recently articulated by our Prime Minister, people, planet, and progress. The summit that we are working on will focus on all these three themes, impact on people, impact on planet, and impact on economic growth and progress.
We are grateful to the intergovernance forum and the government of Norway for making this session possible and for the commitment to open and inclusive dialogue on the governance of emerging technologies.
Allow me to briefly introduce our speakers. We'll have a session moderated by my colleague and friend from France, Henri Verdier. We'll have Her Excellency Cina Lawson, Minister for Digital Economy and Transformation from Togo. Mr. Tomas Lamanauska from ITU will be joining virtually. Mr. Amandeep Singh Gill, the UN [?] and the Secretary-General from the United Nations. Then we’ll have Yoshi [?] special policy advisor to the Ministry of Information and Communications from government of Japan. He’s been a firm supporter of [?] also. Then we'll have Dr. Mariagrazia Squicciarini from the Social and Human Sciences and then from the social sector of UNESCO. UNESCO has been a key partner with us in our journey. And then Audrey Plonk, Deputy Director OECD will be joining virtually. Welcome Audrey. Again, key stakeholder and a partner for the GPAI forum. Then we have Ms. Andrea Jacobs, AI focal point from Antigua who is joining virtually. And our colleague from India, Sharad Sharma, founder of ISPIRIT joining virtually.
Now it's my pleasure to hand over to France's ambassador who not only agreed to moderate today's session, but has also helped in occur rating it and shaping the very conception of this session.
With that, I'm pleased to hand over to Ambassador Verdier to start the forum.
>> HENRI VERDIER: Thank you. That's a very difficult task I accept because I suppose as you can see we have a bright young set of speakers and minds. Most of them are friends and I have the difficult task to be sure that all the nine speakers would speak and speak briefly and we with answers to a lot of important questions.
And to the second point, we will during one and half an hour speak about a very important topic. I want to [?] because you will do but in one sentence, innovation is not always progress. And progress is not always for everyone.
And the question is, with impressive AI, how can we be sure it will benefit to everyone, including the emerging economies and the [?] but the vast majority of humankind.
So that's the question today. As Abhishek said, we are meeting here between two important summit of head of states, the Paris AI Action Summit which was organized last February, and AI Impact Summit that will be organized next February.
I just want to say that there are very important UN tracks regarding AI governance and ethics of AI and it was important.
But it is in between those tracks to have some meetings of head of states and to see that each of them can put one important aspect of this broad question.
So for example, the first one was dedicated to [?] risk, and that was right. In Paris we did speak a bit more about innovation, governance, and environmental impacts. I feel that in the lead we'll be more [?] development and inclusion of benefit for everyone. And great story and all the rest of the year we are working within the different UN policies.
So we'll start and we'll start so we'll try to address three questions in 90 minutes.
First to speak about AI divide from let's a [?] perspective. Then what can the multi-stakeholder cooperation give to us.
And then can we define together actually pathway for inclusive AI ecosystem.
And I start with the most difficult part of the debate, I will ask to each speaker, if possible, in two minutes to tell us from your position, your region, your responsibilities, what is the most pressing structural or technological barrier that hinders equitable AI adoption and why does it matter for equitable AI system?
If you agree, your ministry, excellency, I give you the floor.
>> CINA LAWSON: Good afternoon, everyone. I think it's a very important question, because from our perspective when we think of AI, we view it as a tool. And so we safely think three things are going to hinder AI development in Togo or in Africa, all the Global South. Which from our position will be the lack of infrastructure. So that's number one.
The second is that we need to better train our people. So I would say skills.
And the third one is dataset, the lack of the availability of these dataset.
In terms of infrastructure, we think there is almost -- we're still struggling with connectivity. With reliable electricity. As you know, we won't have access to GPUs or data centers, so we -- when we think about how to better include the global south in these conversations, we need to think about how to fund this infrastructure. Which types of business models do we need to support in order for these infrastructures to, you know, to fill these gaps. That's number one.
Number two is that when you say that AI is important, it has to be -- we need to think of it as a human-centric tool. And so every time from, you know, African perspective when you think about artificial intelligence, we think that it needs to be used to solve our problems.
So defining problem definition, you know, requires skills. Right now on the African Continent we're facing a major challenge, which is that we have less and less kids that choose to study math and science, you know. And with that in mind, when we talk about skills, we know that we need to address the education challenge, which is a huge one.
And then the third thing I say is, is datasets. For example, during the pandemic when Togo used artificial intelligence, we used satellite imagery, so that doesn't require to us have a lot of data within the country. And we also used mobile Telco's metadata.
Bun thing that needs to be said is if digital transformation is a challenge, it also means that a lot of our countries don't have the data that they would need on top of which we would apply algorithms.
So building these datasets which are hundreds or tens of projects that we need to develop is also something we need to look into in order to be relevant.
And why is it important to be relevant is that AI is a great tool, that's number one. Number two is that if we are not part of the conversation, we won't exist in the future.
One fear that we have is that imagine the world 20 years from now and if AI represents the totality of knowledge, if you are not part of this knowledge, people -- someone coming from I don't know which planet 20 years from now, looking at the data on the platform, if you don't exist on this platform, it will mean that we don't exist at all.
So it's extremely relevant that we be part of this, because it's going to define whether we get to even exist or not.
>> HENRI VERDIER: Thank you, minister.
Abhishek.
>> ABHISHEK AGARWAL: Yeah, the experience for any AI application or infrastructure are infrastructure compute mainly and talent, skills, and datasets.
And when we were designing our AI strategy, we realized that on skills we were putting up the ladder because we are known as the tech capital of the world, our engineers are part of almost every major initiative and digital transformation. Within India we have [?]. So on talent skills we are pretty okay. But when it came to availability of computing infrastructure and datasets, we had a lot of work do.
So India AI mission focuses on GPU. We don't have as much as the U.S. has, but we need to start training models and build models and build health care applications and other sectors. That's one initiative that we have taken to address the gap in computing for secure.
The other is about datasets. How did we ensure datasets both the public and private sectors across domains and sectors are made available. For that, we build an AI for [?] for all stakeholders to contribute to datasets that are AI ready, that are shareable through APIs which can be used by developers and by entrepreneurs to build applications.
When we look at the adoption of AI globally, we do believe that these bottlenecks are there across, in fact, most of the AI today is controlled by a few companies and a few countries are focused the impact summit we'll be hosting next year will be how to democratize AI [?] and how do we ensure that the benefits of AI are used for solving problems in health care, agriculture, and solving problems in science and math education, how do we address a lack of teachers who are there. How do we make education available in mother tongue becomes a very, very important component.
But we're working with [?] which is a natural language processing through voice. So voice is our focus area. When we're able to offer service throughs a voice command in the mother tongue, then we'll able tomorrow power people out of the ecosystem. When that happens, it has a lot of utility and benefits.
I would say that global consensus on focusing on democratizing AI and making the Global South part of the conversations, ensuring that the compute datasets are available, algorithms shared, applications are shared will go a long way in ensuring that the whole world becomes a key stakeholder in AI conversations and not just in [?] AI users of [?] for a few companies.
>> HENRI VERDIER: Thank you very much.
Before giving you the floor, we know that Tomas has to leave early because he has other engagement. So maybe I will give the floor to Amandeep and then to Tomas. So Amandeep, if you can also tell us, why does this topic matter and what can the [?] system provide solutions?
So you have four minutes or five.
>> AMANDEEP SINGH GILL: Thank you. And thank you to you and to Abhishek for getting us together.
I think there's strong momentum coming out of the Paris AI Action Summit going into the summit we hosted by India, the folks on AI action, AI impact is an important turn in the conversation.
I agree with you that of course there are more inclusive processes and they have their role, I'll come back to that in a bit.
But engaging leaders on a regular basis is important. Leaders everywhere are talking about AI, they're acting on the AI-related challenges, and it's good to get them together in this summit format.
Now the agenda which Abhishek has described is very much welcome. I think on top of the existing digital divide we have a looming AI divide. All of Africa, less than a thousand GPUs, less than 1% of the dataset to capacity. Most of the datasets, language datasets are in six or seven languages. The culture context is also very specific, [?] and Western Europe.
And we've already seen many parts of the world where there are efforts, for example in Japan, and Gulf, to find more contextually relevant datasets, to find more use cases that are appropriate for that context.
And Cina spoke about those use cases. I think we have to have this global dynamic and a local dynamic without which we cannot really recognise the opportunity and advance progress on these Sustainable Development Goals.
Just a moment to reflect on how this connects with the ongoing work at the UN. Of course you'll hear from the ITU and the UNESCO on the longstanding work on the AI issues, the AI for Good summit and the AI framework.
But we took a decisive turn last year when the global digital compact was adopted. It's the reflection of the high-level Advisory Board and [?] here was a distinguished member, landed in those negotiations and led to key decisions.
One was setting up an independent scientific panel. We need those regular scientific assessments as fast-moving technology is going to impact on various sectors, employment, for example. The environment that was just mentioned. So we need regular assessments based on a global perspective. Not the perspective of a region or a few companies, but a global scientific perspective.
Alongside that, we need a regular global dialogue on AI governance within the United Nations. So the summits are there, they are important moments for leaders to engage, but on a sustained basis, on an inclusive basis we need that dialogue so we can learn from each other.
The experience of the EU with the AI act, what's working, what's not working, China's experience with GenAI, other approaches need to see what works, what doesn't work.
And also ground all this effort in our shared norms, international law, international humanized treaties, the SDGs, and other commitments on environment, on gender, and so on.
So that dialogue is crucial. And then we need to work on AI capacity building. I mentioned the AI divide. The GDC asks for a report on the consumptions of AI divide. And that work has been done and this will be presented, the report will be presented in September.
It will allow governments and other actors, philanthropies, private sector, to consider compute, data, the shareable open use cases and how to invest in those so that the effort, for example, launched in Paris, [?] or the efforts recently embarked on by G7 countries, they can be put into a globally, cohesive, impactful framework.
Finally, there's works on standards. I'm sure Tomas will go into that. We should have regular engagement, a clearinghouse kind of engagement on standards. We build up those standards into a more prominent, more impactful set of soft regulations.
So the AI safety is there, started [?] taking form in different ways. Now being rebranded. I'm sure there's aspect on children's safety which is being thought about. So how do we build standards in various areas and how do we come together for the industrial benefit and for the tech community to build this technology in a trusted way.
So I'm sorry I have to leave, but I leave you with these thoughts. And we are looking forward to the February AI Summit and we will support the summit of Nazareth, the co-host going forward the just as we did [?].
>> HENRI VERDIER: Thank you, Amandeep. I'm going to -- are you [?].
>> TOMAS LAMANAUSKAS: Thank you very much, Henri, I just unmuted myself. Great to join from Geneva. Cannot be in Norway because our council is ongoing. So our annual council. But really great to see you there. And good-bye, Amandeep, I think.
>> HENRI VERDIER: Amandeep did leave without his phone, so the --
>> TOMAS LAMANAUSKAS: Okay.
>> HENRI VERDIER: We are listening to you, again, these are two questions important of equitable AI and what can we do with the ITU did organize for a long time the AI effort initiative and you have quite a experience on this.
>> TOMAS LAMANAUSKAS: Thank you very much. Indeed, it's a pleasure to be joining this panel this time virtually especially as we have a great presence in collaboration with you for the AI Action Summit in France.
And indeed where we together launched a coalition for sustainable AI. As we mentioned the sustainability being key part of that conversation in Paris.
And the need now working forward to the AI Impact Summit in India next February. And again we also, you know, we're coming there not for the first time, you know, just last year we had a spot of our -- on the sidelines of our world organization assembly, we had related but also independent two important events that would impact India as well as first AI standards Summit. And I think Amandeep mentioned how important is this collaboration there.
So indeed it's great to build a network together with, you know, with you and make sure that this dialogue continues to be inclusive.
So now back to this specific question here about the gaps. And indeed, I think the three gaps already quite a few people mentioned, infrastructure, you know. I would add finance, you know, because to kind of help, you know, to have infrastructure there we need the finance at the end of the day.
And I think here indeed we have huge gaps not only in basic connectivity, but also in the kind of data infrastructure, when we talk about data centers, whole Africa has 1.8% data centers at the same time having 17% of the global population. So disparities are pretty big.
Skills were mentioned and datasets were mentioned. I'd like to add capabilities and innovation. If you look at the [?] for example, a rough measure how we look at innovation, you see the two countries join together really dominate that area, you know. And they're not leaving -- not leaving a lot of percentages.
So how do we generate that innovativeness in our innovation coming from other areas? And that means how we generate those companies that could also do that.
Then trust, you know. The trust gap. Because around 60% of the people around the world, you know, have issues with the I trust. So that's not necessarily unique to the, let's say, development versus the countries [?] but that is around the world.
The other thing from our perspective that's important is the policy gap and policy barrier. A lot of those things they need solid policies. I think to create the policies, we need policy makers to understand whether they're regulating or governing.
So I think this is very interrelated topic and of course this is a correlation without having infrastructure and skills in the country and having policies there as well.
So our -- our service of the countries have demonstrated that actually there's a big policy gap, still around 55% of the countries say they don't have a policy, they don't have the right policies or strategies in place. 85% of the countries don't have regulation environments, so it's more detailed. And I think without that, it's difficult to address other barriers there. So I think that's why it's most important.
What I find really intriguing, I would call optimism divide. That's conversely related to everything I said now. If you look at the recent studies, actually the people in Europe and other developed countries are very skeptical about AI. They've been more fearful. They will say AI will come and take our jobs. There are 75% fearful that AI will take their jobs.
When you look in the Global South it's opposite. 70% of the people say it might help us. It might help develop our economies.
And then two-thirds of the people actually look forward to the applications in health and agriculture and other areas. I think that's very interesting.
So that means for me if we are managing to bridge other gaps, infrastructure, skills, innovation, we actually have a ready-made population and town pools and ready made consumer areas, if the world is well that they're ready to take up with AI and really using the data in their lives and allow to us drive economic and social development there.
Now what we're doing from the ITU side and broader UN said and I think are complementing what Amandeep was saying and areas there. Now is a crucial moment, those of you who follow and others of us who follow the implementation of global digitization impact and the panel on AI and global AI governance dialogue, I know that conversations continuing in New York on this, but of course we're not starting from a blank sheet of paper. UN and ITU has done quite a bit already before to help create that AI governance fabric, if you will.
As it was mentioned, we have AI for Good global summit running since 2017 already that brings all this together. Last year we had the first year governance day. We brought around 70 countries to exchange views.
And in a couple of weeks, the 11th of July, we're looking next AI for Good global summit with the second governance day in July. We're expecting significantly more policymakers than last year, including a few heads of state there as well.
So the platform, there is a pattern to build on. We're very happy that in the resolution discussions the AI for Good global summit is recognized as at least a potential venue hopefully for the first global dialogue on AI governance that was coming out of the Global Digital Compact.
The other piece so to bring everyone on the standards. To spread innovation standards a key tool to spread innovation in an interoperable, affordable way.
We're working, we have our own suite of standards, more than 400 of them. But at the same time working with partners within what is called world standards cooperation, key partners there, international standardization organization, ISO, where we bring the standards community on AI together. Again last year as mentioned already, we had the first AI standards summit in India, looking forward in the summer to our second. And then during the AI for Good also to bring all the relevant organizations together to progress the joint work on AI standards. So they're relevant, interoperable and benefit everyone there.
Skills, this is a broad range of things. We will introduce an AI skills coalition. Our most recent flagship initiative with 50 partners joining us where we aim bind of this year to get 10,000 people trained in the AI skills in different -- in different subsets of courses. But we have understanding parts of initiatives for people around the world, AI factory, start-ups, participate in phishing compositions, to AI mission learning challenges to engineers around the world and we have a lot of interest from developing countries in that. And these initiatives will show us that there's a really strong -- there's really strong, you know, talent pools around the world, they just need to be tapped.
And of course, and then just the last maybe initiative of all these flagships I wanted to mention is digital [?] initiative is launched in the Brazil 2020 where we tried to bridge [?] 1.6 trillion but of course with that the infrastructure. And of course in just or the week -- actually just a week we'll have financing for development conference in Serbia, Spain, where we also go for UN financing for development for conference we're going with that flagship initiative and looking how to also host the [?] infrastructure.
Inclusive, I think looking back, what is also key is inclusivity around the world. I mentioned that in our AI for Good last year we had around 70 policymakers. What some of them said it was the first time when they were in the AI governance discussion. And I think that is very important. Because I think it's important that those discussions don't just, you know, involve the usual suspects. The countries that already have the capabilities and capacity of that really involve everyone from the get-go. Great to see AI impact -- action impact, you know, like four month come to different parts of the world.
We have like a very strong participation in developing countries in Geneva. Last year we have, as I mentioned, AI Impact Summit in India. We have also in Africa and Capetown. So we're trying to bridge that inclusivity gap and make sure it reaches everyone in terms of skill and also important policy instruction that are important.
I'll stop there and back over you to. Thank you very much.
>> HENRI VERDIER: Thank you very much. And thank you for making time within a big, huge agenda.
So now I will come back to my initial schedule, but we are changing slightly.
I will try to mix the two questions, Oshie Son and others. What is the main barrier against the equitable table of AI and what can we do in the framework? I can see the consensus with the three gaps, but I feel that we're not going far enough.
I was thinking listening to all of you, certainly we have examples of great technologies that were not used for the best. Television could have been a brand tool for education and it didn't become a resource -- resource for education.
Genetically modified could have been a solution for education in topical eras and didn't.
So we know from history sometimes there are brilliant innovation that don't turn enough into progresses. So collectively we have to go further and tradition of Japanese very interesting.
>> OSHIE SON: Thank you very much, Henri, and thank you very much for the invitation. I try to be brief, but let me talk about the Japan's situation where I talk about the international efforts.
And the -- if you look at Japan, we have the very unique challenges of the rapidly aging society and also even the decreasing population.
So we need, really need to make the full use of technology such as AI in our society to keep the energy and the liveliness of the society and community.
So from this perspective, the trust of the people in technology is very, very important element. And the -- also the skills and the literacy also very important element in order to make people use the technology without concern and in a very efficient way.
Of course, we have a lot of problems elevated by the colleague from [?] and also I envy when you talk about the skills, okay, for India. We have a lot of problems in competing resources and also the dataset and also the skills and literacy of the people.
But as I said in the beginning, most urgent problem for Japan is the how to make use of the -- this technology to benefit the society and the literacy and skill of people and also the trust of the society and the technology. It's very, very important.
That is why we enacted AI law at the end of the last month which people call not AI regulation law, but AI promotion law.
The law is trying to push the AI usage in the society for it by generating and growing the people's trust and also the literacy and the skills. So education is very, very important for us.
That require the government very radical transformation with the old system, not only in education, but also the -- the labour's risk or maybe understanding of the people on technology.
So a lot of things have to be done before the government. And also I don't believe when we want to make use of the AI technology in the society, we have to use the technologies from across the borders. I don't believe, you know, all requirement, all demands of Japanese people for AI can be fulfilled by the domestic technologies and domestic businesses.
So that is why we need very much coherent and interoperable governance frameworks across the regions and across the countries, across the jurisdictions so that we can make use of the AI models and the systems without concern when they come from abroad.
That is why we are promoting the initiative called the Hiroshima Process which encourage the companies to take up measures and share the information, relevant information with public very openly.
And so by doing so, we believe we can foster the trust among people on this very path of technology of AI and the people can make use of the technology without concern.
So that -- that is the -- our approach and these are our challenges. And in order to do that we have to work not only with the governments from around the world, but also with stakeholders with businesses, Civil Society, and academia, all kind of communities all together to achieve a type of core governance which will bring very safe, secure, and trustworthy AI ecosystem across the world.
So that is what we are doing now and I hope I will share the same understanding with all colleagues here.
Thank you very much.
>> HENRI VERDIER: Thank you, Oshie.
I'm going to Mariagrazia. Before the meeting you told me that we need a technical strategy for inclusion. So maybe -- because there is -- this is too [?]. So you [?].
>> MARIAGRAZIA SQUICCIARINI: Seems like my microphone -- now it's going on. Thanks a lot for the question. I had to take note because it got more and more complex by the time we're talking about and I would like to avoid being repetitive.
It's true, perhaps you said it before, like a country's problem needs to be analysed well to find solution. UNESCO has 194 Member States, so our territory's the world.
And without the sectors, what to we do in different sectors, we cover any sector from culture to education to any other sector in our activity. So the question of the key barriers becomes one, in my mind, of systematizing the problem. That is the computability, the endowment of the infrastructure, it's not only the physical infrastructure, but also the human capital, developing skills.
Let me add a point there. In order to work, live, thrive in what we can now call the AI era, of course and we heard we need to trade also, Tomas mentioned that, more people in S.T.E.M., for instance, people that really deal with AI, build AI. But we need 10 to endow population with social and emotional skills. And this goes to the technical issue we were mentioning. That deploying AI in an environment from public institutions to companies into nonnegligible changes.
So there are a number of components that go into that. It's not let's say one component, perhaps the solution is in the mix. And why this relates also to the governance, because you need to have -- in order to have these assets around the table that allow you to leverage your opportunities that AI may offer, you really need to have the institutions.
You need to have legislation, all of you were mentioning legislation, for instance, for initiatives that have been passed in your countries in order to address the AI transformation. And we also need to learn from each other.
So that's exactly what UNESCO has been doing through what we call the Readiness Assessment Methodology. It's an analysis and now we're working with India to finalize theirs. Something that gives you a picture of the countries. It's not a ranking.
Nobody has it right or wrong, there are good practices, and I emphasize good because the best is not there yet. Nobody has the solution to the problem.
But there are good practices from everywhere in the world that understands the group does show, again I don't really like this name, but that's the way in which typically it's referred to, because there are different components and different aspects that need to be taken into account. And everybody can contribute to that.
And perhaps the narrative has been going in a direction which is somewhat [?]. We typically talk about inequalities in AI in developed versus developing world. Let's remember and this something that's very much on the table in the current discussion in the context of the G20, of the redeem countries and inequalities, and you underline one important, the generational one.
It's not the same thing to deal with AI when you have a generation this an average age of the population that is relatively low where it is relatively easy to endow the population with certain type of skills because their closer to education than when you have a population that's getting older.
There are a number of things on the table, and perhaps based on understanding, this is what was referred to when we were talking before, that is that there's another one including basically benefits will be included.
Actually what we know about AI is if we have biased data, if we don't have infrastructure there, governance mechanism, for instance a number of languages are not included so certain communities don't have their societal habits, contributions reflected in that, ultimately the AI itself is performing worse.
So it's not able to address when you go in what it is called in the jargon, in the testing, it performs worse. It will actually generate systems that are not as performing or as fit for purpose as they should. Including bringing more actors around the table, as you mentioned for instance, the multi-stakeholder having better data, more representative data. Including women for instance in the AI transformation.
Ultimately inclusive AI is very good businesses, because it's more accessible and brings better benefits.
Another component that we were mentioning is also about the companies. And this refers again to inclusiveness from a different perspective. Now we are talking about [?] in the game and who would like to enter the game, so to speak.
So if we think about what is the constituency nowadays in AI, we see a number of very big corporations that typically are from a certain number of countries.
Well, there are a number of start-ups that are aiming to scale-up that are not really finding it easy to do so. But why should be in our interest to let them to do that, because there is plenty of evidence that radical innovation, breakthrough innovations tend to come from young, small entities that is plenty of research about that.
And so the issue is whether we only care about the AI for today, or we do care also about the AI for tomorrow. Because unless we let these companies bloom, the likelihood that the payoffs from AI will be there also tomorrow, new types of AI are less likely.
And these all, nevertheless, have to happen within some guardrails like the ones foreseen in the ethics of AI from UNESCO.
I will close it there because we have seen again and again in history, what's feasible doesn't necessarily means being society desirable.
So perhaps we have to have a conversation about what we do not want AI do and let the rest bloom to address the many challenges that society is facing these days.
>> HENRI VERDIER: Thank you very much.
I'm going to our online friends, maybe I will start with Andrea. The OCD is another important body and you have an initiative including the G [?] our favourite project from France, because I didn't negotiate it with Japan seven years ago.
So there's things that we are in the good direction to be sure that we do include in this conversation, the developing countries and the needs of the developing countries.
>> AUDREY PLONK: Thank you, everybody for being here and part of the global conversation on AI, which is no longer a hosted entity of the OECD, we were proud to have announced last year in India at the summit of GPAI. We hope that the GPAI will be interesting to a large set of companies that are at a level of development in AI that we can come to the table and work on a set of topics, many of which have been discussed here today.
I think in terms of the question around where we see divide, you know, I will try not to be redundant of others have said, but there's the capacity divides in terms of the ability for countries to participate in certain activities. And I think that's where Tomas mentioned policy divide. And we do see a lot of effort from the UN system and UNESCO to try to accelerate governments' efforts to develop policies and strategies to put AI central to government policy. But we see there's still a lot of work to do there.
For example, we maintain a database, the largest database of AI policies around the world and we cover over 72 jurisdictions, but there's a lot of room for improvement and growth, but also learning from each other. And so not just collecting the information and data from countries about their efforts, but also finding ways to access, share that data that helps build capacity in other countries.
So I think on the policy and institutional capacity of countries and government to participate in the global dialogue, there's a lot of room for us to work collectively to bring others along. And GPAI is a place where we are fully committed to doing that.
I want to also say about the infrastructure piece, because many people have mentioned it and it's exceedingly important not just for AI development and deployment, but also for general digital transformation. And we see that there's of course a lot of opportunity there. And I just want to mention one project because it's new and not yet totally public.
A new methodology we're developing to measure compute availability in different countries. We're talking about that in the GPAI context for those of you who are at that table, you know. But I think it will be really important that we put good empirical evidence behind some of the discussions that we're having at the political and policy level so that we can actually, you know, eventually move the needle on where things like investment is going and where business opportunities are moving.
And so I want to also echo the reality of financial divides in terms of investment and AI and the ability of other colleagues who said for small and medium enterprises which are of course the lifeblood of the economy, of the global economy to engage in the AI world.
And then I think in terms of the skills and education divide, I think these are different things and we need to be -- we need to think more granularly about what we're trying to do with skills and with education.
Everything from early education in S.T.E.M. all the way through upskilling and training of workers and aging populations.
And I think targeted -- what we're seeing is targeted media literacy programs, targeted efforts to meet different populations within a country and across countries where they are is extremely important, not again just for their ability to adapt to AI coming into their lives, but also to generally adapt to digital transformation.
And I think the more global cooperation and sharing of experiences that we can have in that regard, the better the outcomes will be in the long term.
I completely agree we need to be thinking longer term, not just today and tomorrow, but where's our population, where's our society going to be in the next ten to 20 to 30 years and using this technology.
With that, I think, you know, I would say that finally we see in terms of culture and language, which many people mentioned, one important effort that we have at the OECD is our AI observatory. You're probably all very familiar with it. And one of the big efforts there in order to help contribute to a more multilingual, multicultural environment is we're trying to make as much of that data available in multilingual -- multilingually as possible.
And so for example if you go to the live data coverage on the observatory and you look at the media coverage of AI, you can see and read about what's happening in AI and many, many, many different languages.
The same is true for the incident monitor where we've been building a methodology for classifying problems that happen in the ecosystem relating to AI systems. You can look in native language across different countries around the world.
So I think the more that we can cooperate both on the data side and on the policy side, the better picture that we're going to have of what's working and what's not working. And then finally I think the lastly and I'll close with this in the interest of time, that the game changer in AI, particularly in the developing world, is doing to be adoption and diffusion across different aspects of industries and society.
And I think -- and that's the case really for all countries. And everybody even big countries are grappling and challenged how do we use this technology.
So that's a shared experience that everyone is going through. How do we make ourselves more competitive, more productive by using these technologies. And I think that's a big opportunity around the various international tables, multilateral tables to really work together to get the best possible outcomes for our population.
Thank you very much.
>> HENRI VERDIER: Thank you very much.
So now we are going to Antigua, Barbuda, and to ask Andrea Jacobs what's your view regarding this question.
>> ANDREA JACOBS: Thank you. So that's a very, very good question, and you know, I've heard a lot of unpacking from different regions. And [?] certainly sets with Africa on what was said.
So the Caribbean and more broadly among small island developing states, the most pressing structural barrier to equitable AI adoption is the lack of robust digital infrastructure and institutional readiness.
And this -- this sentiment, dare I say, is echoed across the Global South. And this includes unreliable connectivity, particularly in rural areas and island areas.
Then we have weak data ecosystems which limit our ability to develop context-relevant AI. And then we would have limited regulatory and technical capacity to ensure safe, ethical, and inclusive AI use.
On the technological side, there's a major imbalance. We are overwhelmingly consumers of AI technologies that are developed elsewhere. And oftentimes our realities languages priorities in mind, most of these companies don't bear this in mind.
And as you know, the people or the companies rather who make the AI products, they might not think about people in the Global South or even Black and Brown people, dare I say, and that's where the biases come in.
So the tools that we adopt are not built for us, and that poses a real, real risk.
And then the question is, why would this matter, right?
Why does this matter for the Global South? Well, if these disparities continue to go unaddressed, global AI will continue to serve the few rather than the many. Reinforcing existing imbalances, embedding biases and excluding millions from the shaping of the future of technology.
And this is why in Barbuda we talk about having a seat at the table every time in these AI meetings. Because the world needs to know that we are in an era where we are being left behind. The private companies are making these products. We're not getting our voices heard enough. We don't even have rules and regulations. We don't have good governance structures. We don't understand the ethics of AI. How it's going to impact people in the Global South. And more importantly, Black and Brown people like myself and the situation is very, very real.
And then we're moving into the context of AGI, which is the next level of AI. And we're not even -- we haven't even mastered AI as yet and we're moving forward towards general AI.
So we need to be a part of the conversation, not just as recipients, but as equal partners in co-creating values, rules, and technologies that will define our shared digital future.
And then lastly, for us in the Caribbean, and somewhat in the Global South, because I talk a lot -- I talk a lot to my partners in the Global South and we have this view. We need local infrastructure, talent development, we need culturally relevant innovation ecosystems, and we need stronger participation for countries in the Global South.
As long as we remain primarily consumers of the AI products made elsewhere, without a seat at the design and decision-making table, we risk adopting tools that entrench inequality instead of empowering transformation.
Thank you.
>> HENRI VERDIER: Thank you very much.
And now I'm going to Sharad. I don't see you so far. Same question about this AI divide and how can cooperation help to fix it.
>> SHARAD SHARMA: Right. So let's look at digital divide first. You know, digital divide in some countries has been coming down quicker and there's an example of that.
And there are many lessons to learn from that. At the same time, we must realize that the AI divide is a very big problem, you know, because we know that the first version of AI that we have is actually social media. Social media is entirely AI driven, right?
And that is how the social media platforms ensure that we spend, you know, increasing time on their platforms, you know, year after year.
Now, so the question of course, is how have we done in dealing with these [?] effects of AI diffusion in the world of social media?
I would say we have done very poorly. What is the test?
The test is do these new systems change the balance of power between the citizen and the state in the favour of the state?
Do these systems change the balance of the power between the consumer and the provider in the favour of the provider?
The answer to that is yes.
And therefore, ironically, we are in a session of Internet Governance. We have to go back and look at this and say why has our efforts of Internet Governance 2.0 failed?
This situation is not getting better, it's getting worse. So if we have to make progress with AI, we have to first acknowledge that the last ten, 15 years have failed. And not perpetuate the things that we have been doing, you know, which have led to this failure.
What are those things? There are three that I like to point out based on the experience of India stack that was mentioned earlier on. First is traditional regulation has to be replaced by technology regulation.
Our Prime Minister talked about it at the AI summit in his brief speech there. This is absolutely essential. The old form of regulation can begin by the producers of digital services or AI services, they do it five years ago, ten years ago, 15 years ago and they'll be able to do it as we move forward.
So we have to bring in a new regulatory paradigm. And that's techno legal. There's a lot of learnings about that in India.
The second is we have to change the nature of innovation. Innovation has to become an innovation that's built on public goods and private innovation. Because if you don't have public goods and the innovation is entirely in the realm of private sector, then as can Andrea pointed out, the outcomes are going to be terrible.
We will all be consumers and not producers. India will have super teachers, super doctors, we'll have better medical devices, even our students will learn better. But the people who will provide the AI models to make it happen will not be from India. And the value capture of all this will not be in India.
So this is a very serious problem that we are looking at. Therefore, we have to look at the innovation architecture itself.
And the third item is still there, but one of the big takeaways from the UN AI advisory body is that we have to create a new type of an infrastructure. A public infrastructure for dataset shift that is controlled and yet unlocks hidden data from companies and countries in a manner that they can control.
And in -- in the UN report that's recommendation Number 6, that's absolutely essential.
India is in a very advanced form of building that out, and again it was mentioned at the Paris AI summit by a Prime Minister, we call it DRDA because it's data requirement and data [?] more of the same is a recipe of disaster. We must acknowledge as a group of people that we have to make a new beginning.
If we don't make a new beginning, just keep doing what we've been doing for the last ten, 15 years, we will not get good outcomes, good rules and then we will just be a talking shop and we'll collect again five, ten years from now and how little has changed from where we are today.
So let's please make a fresh start. The India AI Impact Summit will attempt to bring these ideas to the table and we're hoping that as your participate in that in February, you get infected by the spirit of making a fresh beginning and taking these new ideas into the AI [?]
Thank you so much.
>> HENRI VERDIER: Thank you, Sharad. Now I reschedule referring are we're at the end of this roundtable. We'll focus to one question. I would ask this question to six speakers, because you will conclude, and the question is quite simple.
Can you share with us your suggestions for [?] concrete ideas to build really inclusive AI ecosystem?
But I have to mention that when we started one hour ago, I did ask to every speaker to speak in two minutes. The only one that did respect the rules was Minister Lawson.
And I beg you to stay in two minutes because we'd love to extend a bit for the room, if possible.
So question, concretely, actionable IDs, what can we do to progress in the field of inclusivity. Minister Lawson.
>> CINA LAWSON: Thank you very much. The first comment I make is AI has to work for us. It means that we have to make sure that it is designs to solve our problems. And in Togo we use AI for beneficiaries of financial aid programs. The second instance when we use AI it was to design better network.
We were deploying fibre networks and we use AI to really build the I.T. [?] in a way that a network would be efficient.
So I'm saying that because when we think of AI as a tool and we say, okay, it has to work for us, it also implies few other things. And one issue we faced when we were doing that was the availability of local data.
So there's a bit of work that needs to be done and to build this data and the dataset.
I really appreciated the comment on public infrastructure for datasets that was made earlier. I think it's extremely relevant for the Global South.
The second comment I'll make is that today most of AI and AI platforms are designed for -- in a language that is not our language. I mean, the majority of what people call the Global South speak different languages. And so we need to make sure that the new platforms and new systems that are designed are designed in local language.
Because by designing them in local language, we can have better participation and also relevant datasets. If you build something that seems a bit foreign, it's extremely difficult.
But one comment that was made has also do with culture, to make sure that the dataset represented our culture. And so I'm saying that because if in the future AI platform will represent reality or will represent the totality of knowledge, we have to make sure that our cultures are also represented in these platforms.
And I think that the summit in India and India is well known to have such a diverse, you know, culture within the 1.2 billion, you know, population. So I think that India can really drive -- be a huge driver to making sure that, you know, there's a diversity in culture.
The third thing I would say is that one thing that's extremely important for us in Togo is to make sure that we're part of the solution.
So enough, and I think you've heard it everywhere, that the Global South does not want to be just consumer. So what it means is that we need more alliances or programs to fund research. Research on the continent, researchers, you know, joint programs of research. I know that we had conversations and many countries had conversations with India and other places to send researchers, perform research and so on.
Research programs are going to be extremely important in this new world, and also shared infrastructure. Because we did mention that we lack GPUs and other things and that we didn't have enough -- enough data centers. So it means that we need to build new programs, new models where we share infrastructure.
And I think that we need to -- to build business case and new business models that take that reality into account. And again, I'm looking to India saying that these type of outcomes need to be discussed during the summit. Which kind of models that we need to build so that we can make sure that the Global South is part of this new world.
The last comment I'll make and it's an important one, has to do with training. How do we design the new training programs, because we do realize that we have a training issue, we have a skills issue. But -- but this talent training, we need to have conversations about effective talent training. And I think that there's not a lot of investment being made at the global level with regard to training talent.
And without us needing to send talent abroad to be trained, how do we build models and programs within the continent and within, you know, the Global South so that we improve talent training is also going to be extremely relevant.
And I think that in all these -- when we talk about all these issues, you know, India is a pioneering in some of these issues and the conversations need to happen during the next summit.
So the keyword here is participation, training, and research and local languages. These are all words that, you know, are very important.
>> HENRI VERDIER: Thank you very much. For the next speakers, one ID, one way to implement it. Oshie.
>> OSHIE SON: If we want to materialize some AI application, AI services, based on the concrete demand and the concrete [?] of other people, maybe we need to work in multi-stakeholder way and we need to work together to understand each other and create the AI services which responds to the concrete demands from each of our users.
And the global partnership on AI [?] would be one of the forums to realize multi-stakeholder approach. And also in the AI summit will be also another opportunity.
We are also running the Hiroshima process group where many developing countries are joining and also we work together with AI companies and the businesses and also international [?] such as OECD or UNESCO to understand and create the new values through AI services.
So we have -- we must have many opportunities to realize and materialize the [?] approach into the underground services or underground AI application.
Thank you very much.
>> HENRI VERDIER: Thank you. Mariagrazia.
>> MARIAGRAZIA SQUICCIARINI: So actually I think we should move -- we seem to agree on the what, we should move to the who and the how. Because if you really want impact, you need to know who's around the table and how we do things.
The other thing is to move from fixing the problems ex-post to have been ethical by design. Ethical means that abides by human rights, human dignity and fundamental freedoms. Because everything becomes much easier then.
And then also the other thing that I think is important in order to move towards impact is to move beyond bias data type of approach whereby we think if we fix the data in [?] the rest will come with it.
There are a number of inequalities, there might be a number of challenges that emerge by the time we deploy the AI systems in the real world. So moving from having a suitable design, good implementation, but checking after as we do with any other product, I think is fundamental to make sure that AI responds to what are societal needs.
I'm trying to be very disciplined here.
>> HENRI VERDIER: And you are. Thank you very much.
I'm going online now, I'm coming back to Paris, Audrey. Your main ID.
>> AUDREY PLONK: I think the main thing I would offer at this point is to join us at the global partnership in AI to advance on some of these topics.
And with that I'll probably save you a lot of time to get through the other speakers. But there's a lot of really stunning work happening, it's founded on the OEC-AI principles familiar to everyone, and that community is driving forward on topics like deploying AI in agriculture, working on AI in transport systems. And so I invite you all to come work with us.
Thank you.
>> HENRI VERDIER: Thank you very much. And we're coming back to Caribbean region, Andrea.
>> ANDREA JACOBS: Okay, so I'm going to choose my top two even though I have maybe five.
So until we progress to become producers of the AI products, we remain first and foremost consumers. So we need to understand that.
And as consumers, we have a vested interest in how these technologies are built, governed, and applied.
We need to understand that first of all, we're consumers at the moment. We will progress to be producers, but until then, we remain consumers.
And that is why the Global South must use our collective strength, we must use our collective voices to ensure that we advocate for inclusive, transparent and the accountable AI governance frameworks.
Then the second thing is we need to start to develop and I investigate in local data ecosystems.
Data rights, all that sort of stuff, we need to ensure that our people have the knowledge and the skills to retool and to up-skill. Those are my top two and I'll pass it on to Sharad for brevity.
>> HENRI VERDIER: Thank you very much.
Sharad.
>> SHARAD SHARMA: You know, I mentioned some points last time, but I'll share another learning that we've had. But to place it in context, to me, India will do more than 60% of the world's digital transactions.
These are not just commerce transactions, these are direct benefit transfer transactions which the poor people in India rely on to get their benefits from the government.
And those benefits come from our taxpayers. This also includes the tax paying transactions. And more than 50% of the world's tax paying transactions by volume happen in India.
And so therefore, all this has happened since 2012. You know why? Because many of reasons, techno legal, BPI, stuff like that. But in addition to that, as Andrea noted, we were relentless in this. Some of you have seen the slides. And by being relentless focused on that for the past 30 years, it kept us focused, determined to be able to solve this problem that we're talking about.
Now, when it comes to AI, we are gravitating to picking on younger girls as our focus area. Because young girls, while the AI may lift them and make them better students, you know, but it has also the potential to have an enormously destructive effect on their lives.
They may reduce cultural norms. They may get distracted by pornography, gambling, there are a number of concerns that arise when it comes to child safety. And child safety is important. I would say child safety is super important.
And it is also important from this sovereignty perspective. Is each country perpetuating the culture to these young children that are going to be, you know, living digitally and using AI systems.
So that is our focus. And I would suggest that this ought to be a global focus, not just an India focus, not just a Global South focus, it ought to be a global focus.
And you see now around this, we measure ourselves and say are we make progress in protecting our children while we empower them with AI.
I think the we will have more flexibility in deciding what works, what doesn't work. Because that will be the (video froze) let's try something else to make progress over the next ten, 15 years.
So this would be my submission to all of you.
>> HENRI VERDIER: Thank you, sir.
So folks, because you did save time, I can ask the same question to Abhishek, then we take a few questions. So if you are new in the IGF system, I tell you, if you want to ask a question, you go in line after the first speaker and then Abhishek, you will conclude.
So your two points regarding concrete outcome.
>> ABHISHEK AGARWAL: What we need to do, I would say if I had to list what we need to do, in India our focus is to build in [?] enabled services so we use the technology of AI and GenAI tomorrow power those who are not part of the digital ecosystem.
As a community, as a group of nations working together, what we need to do is that can we -- can we create a framework in which we enable access to compute, to datasets, and algorithms to larger countries in the Global South. And how to do it, if we can build repositories of AI solutions, like we came up with the global DPA repository. They can be shared across nations is he summit that we hosted. We created a repository that can be shared with different countries and adopt and deployed.
If you have [?] or farmers, they will have use cases across geographies, across countries. Even though one country is developed it, it can be deployed elsewhere. A repository of AI-based applications will be one of my wishes that we -- that we should work together. And similarly, another thing that's required, like we all talk about datasets. And when we talk about datasets, privatization and [?] becomes equally important.
Can we develop tools which can be shared across countries?
Can we kind of fast forward the development of data [?] platform enabling data sharing within various stakeholders not only within our own countries, but globally.
If we're able to build that framework, Sharad mentioned about the framework that we have, that can have an application for global data sharing proposals and that will really, really fast forward building the AI applications and models.
So I would conclude by saying that these are my wish lists within India about services, and as a global community, building repository of AI applications and tools for enabling AI sharing and building applications.
>> HENRI VERDIER: So I'm supposed to be the moderator, so I don't contribute. Maybe my two cents, I just mention that the very utmost important of research and common knowledge. We need to have common knowledge for humankind and we need to [?] research too.
So please, we have three questions from I'm correct.
>> Hello. My name's [?] I'm president of the Slovakia I'm vice-chair at committee and business at OECD and also MAC 2024.
My question is exactly to you, Mr. Henri Verdier, it's pity that you're not speaker today. So I don't know if you -- if you heard that idea from Joseph Gordon Leavitt who shared today about several companies earn money on our data. And they should give back this money or this benefit would help to us as a citizen or maybe also to [?]
My question is, do you -- in principal [?] I don't know how to do it because it could change completely the economy or the system. So my question is do you have this idea, do you have how do it in the world, this model.
>> HENRI VERDIER: Quite a question. I'm not supposed to be a speaker. They did take some revenue and they did weak on a bit of ecosystem of media. If we did ask to -- if we had asked those companies to pay us, it would have been, I don't know, two or three years, that's a lot to the benefits they do and next [?] generate. It might be useful and I mentioned the content, it can't be a global solution to finance the global development of humankind. But that's an interesting point.
Please, next question for a real speaker.
>> Actually follows on from what the last question was asked.
So my name is Deanne Hewitt Mills and I run a global protection office, so we oversee data protection, sign, he are AI compliance for large multinationals. And I was actually one of the -- we're sort of UK based but we're global. I'm here in Norway launching our Nordic's branch.
I was one of the first data protection offices to attain what's called the B Corp standard. And B Corp -- well, the office is based in the UK. It's a standard where organizations have demonstrated high levels at ESG. Environmental, social governance.
And what we have to do is demonstrate that we're a business that's a force for good. You actually have to attest to what you've done to make a social impact and actually have a report that sets this out on a yearly basis, and then you get -- you're renewed every three years.
And I've done this because I really believe in using business as a force for did. I think actually it would be a great thing if many other organizations -- because I'm not a large tech business with deep pockets, but I've seen the social impact that I've been able to have. And I think, you know, other organizations could be made to do the same. I'm really pleased to see all the women on this panel, because I think if you actually invest in women and invest in women-owned businesses and then also have a structure where businesses are required to demonstrate their social impact, I think there's a lot that can be done to improve governance in this space.
So it's actually just a recommendation based on a real-life case which is the example of what I have done as a business owner.
>> HENRI VERDIER: Thank you. I'm not sure this is a question, but would someone like to answer? Yes.
>> MARIAGRAZIA SQUICCIARINI: I'd like to point to what you mentioned is distrust, which is fundamental for the business of AI and for the data. If we don't trust now with all the regulations that we have, you know, finally help -- try to protect us and say, look, you might want to take yes or no to giving this data, we will get more and more patchy datasets that in order to build AI on is going to be really challenging.
You will have to do, and I mean we know there was someone talking about before AGI. But let's talk about how to use it in a decent way for a good reason, for instance, to fix patchy data in order to represent dataset.
It all goes about in my mind also the trust that we need to have consensus, you were mentioning Henri, that is about let's leverage technology in the way we want. And again because it actually does good to technology and the businesses themselves. And that's what you were actually pointing to.
>> Thank you.
>> HENRI VERDIER: Thank you.
>> Hi, I run a foundation that unlocks the potential of neurodiverse individuals globally. We work with governments on this. And today I've heard a lot about inclusion and diversity.
Unfortunately, it's only in the context of the South or language and culture. But I think a good reminder is that humans are diverse, we have an aging population, over 10% that's going to get impacted. We have a of course gender. We have ability in terms of disabilities that are coming on, and a large population of neurodiverse individuals.
Latest data on Gen Z is 53% of Gen Z identify as being neurodiverse. These groups, if not included in the AI revolution, will have a big -- we will have a big issue of divide that goes beyond the Global South on language.
I think -- I'm not sure this a question or a comment, but how do you include them in the conversations on international cooperation, the SDG goals, impacting children. Because AI is also rewiring their brains.
We see a lot around the anxious generation and their mental health, employability.
>> HENRI VERDIER: So I don't know who wants to answer. Online, someone online? One, two, three? Someone in the room?
>> MARIAGRAZIA SQUICCIARINI: I don't want to monopolize this conversation. But it's true that at UNESCO we have a food programme about inclusiveness of people with disabilities from school to AI that I address from many points of view.
And actually going towards the starting of your question about neurodiversity, UNESCO, perhaps you don't know, but UNESCO in the UN system is [?] the new technologies, hence the work on AI and where it brought us today.
And the latest recommendation that has been worked on is about neurotechnologies and the impact they have on people, on again what society wants them to do or not do.
And the special [?] is put at the crossroad between AI and neuro tech, because that's where the biggest impact may be on societies. So there are ways of actually bringing into the conversation these different aspects and where we meet when we think inclusivity, we think 360 degrees.
>> HENRI VERDIER: Thank you.
I will let Abhishek conclude our work. But just to mention, I will quote you, that I will quote Tomas. Tomas spoke about the optimist divide. And I remember you told me once it's enough you're pretty sure that you will have some benefits from AI.
So you try to fix the problems. Et cetera. We are not sure so far that we'll benefit from AI enough. So that's maybe the difference. And that's why we need designs today we are adding this divide. Yes, we know and we respect that there are other divides. We have three minutes to let you conclude.
>> ABHISHEK AGARWAL: Thank you all for moderating to beautifully. I would think how would you manage. But you did it beautifully and got everyone to contribute. And the thoughtful contribution that came from all of you and all the panelist, different perspectives from all over.
It was very, very useful, very relevant, and you've given us a lot of inputs as we frame the themes for the AI Impact Summit.
For the last 90 minutes, we not only identified the various barriers, various obstacles, what needs to be fixed while we're moving ahead on the AI study where that limits the accessibility, but we also found opportunities, identified solutions and interventions that can help shape a future where AI will truly work for everyone.
One really important message that also came out in the discussions, especially with the reference to the friends, the Hiroshima process, the OECD, the GPAI effort, UN effort is that there's an urgent need for inclusive multilateralism, one that listens to and shapes experiences of the global majority. How to we ensure that the Global South become part of the conversations at every forum.
Whether we make GPAI for inclusive, therefore involves all the country in the process. The UNESCO's work on it, or U.N. kinds of brings together a consensus with the Global Digital Compact initiative.
We heard about addressing the gaps and access to infrastructure. How to we have grounded datasets, how do we enable cross-border cooperation and above all, how do we move from high-level commitments to real actionable pathways. That becomes very, very important.
As we mentioned right in the beginning, this event we had planned with IGF and support from [?] as a precursor to the impact summit in February of 2026, the ideas we'll share will become part of the themes that we mention as we move forward. I look forward to involving you as we develop the concept notes and themes and we curate the sessions.
This dialogue will continue through participatory and transparent process, including when we plan the session for the main summit, we were doing public consultations, online meetings, we'll have a working group that we work with the collaborative spirit, and we'll have an open call for side events. Whether they're from government, Civil Society, all important stakeholders, we'll hold side events during the summit.
We invite all of you to stay connect and engage in the summit in February. On behalf of the government of India and the IGF, I would like to thank the Governor of Norway and our moderator, Henri, each of the speakers, for joining us today and making this session so meaningful and rich in substance.
We look forward to building on this momentum and seeing most of you at the AI summit February next year. Thank you and look forward for the remaining sessions of the IGF here.
Thank you.
(Applause)
