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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>> ANNOUNCER: Please welcome to the stage the moderator Mr. Jonathan Charles, communications expert, former BBC Senior News Editor and Head of Communications for European Bank of Reconstruction and Development.
>> MODERATOR: Good morning, ladies and gentlemen. Thank you for getting out of bed so early for this. Distinguished Delegates, esteemed colleagues and guests joining us in Lillestrøm, and, of course, online around the world, welcome to the High Level Leader Track session of the 20th annual Internet Governance Forum. I'm Jonathan Charles. As the announcement said I advise Presidents, Governments and multi‑national companies on strategic communications. I'm a former Executive Committee member of the European Bank for Reconstruction and Development. It's my honour to moderate today's vital conversation on AI and the future of work.
We gather, of course, at a moment of rapid and relentless transformation. Artificial Intelligence, robotics, machine vision technologies have long past the point where they are confined to the lab or the works of science fiction.
They are in warehouses, factories, offices, hospitals, classrooms, reshaping industries, redefining job roles and raising urgent questions about inclusion, security, equity, and human dignity in the world of work.
This session will explore what this future means not in the abstract, but in the real world context where policies are made, businesses adapt and people's lives are affected. We will hear from political leaders, the companies driving the technology, policymakers and creative thinkers about how societies can harness AI to empower and not replace workers, and how we can design transitions that are fair, inclusive, and forward looking.
Over the next 90 minutes we will discuss strategies for preparing today's workforce for tomorrow's economy. Policies that will safeguard innovation, and the global collaboration that will be essential to shaping a shared digital future. If we are in doubt about the urgency of this issue, then consider these real life stories.
I'm told that in some companies, and this is hard to believe, but Gen Z'ers fake looking busy so worried are they that their lower level jobs will be replaced.
One investment bank CEO says he is worried about how the younger staff will progress if they can't build expertise and judgment when AI is taking over all or part of the roles. He worries about the talent of the future. We will be hearing from our impressive panel later on, but to open our session, I'm honored to first invite a national leader from our host country, please join me in welcoming Tomas Norvoll, State Secretary at Norway's Trade, Industry and Fishery Ministry for his opening remarks. Tomas.
(Applause).
>> TOMAS NORVOLL: Thank you and good morning, everyone. I'm glad to be here at Lillestrøm with you for the IGF Conference. This is certainly the place to be this week. There are so many interesting, important and necessary discussions taking place here, but I think few of them have so many consequences as our topic today, AI and the Future of Work.
I will start by disagreeing with the premise somewhat. AI is not, it's just as much at work today as it is about the future, because AI is already here. It is deeply embedded in tools we use every day.
Here in Norway we have companies using AI to accelerate the green transition. They are optimizing wind and hydropower, predicting energy demand and administrating smarter, more sustainable shipping.
And when I meet with businesses and workers, my impression is that most think that AI is not a threat, but a wave of opportunity. At the same time, it is important to see AI as more than just another tool. It is a platform for transformation, one that will impact virtually every sector of our economy and every part of our society.
And like all major technological shifts, like electricity, like the Internet, like the mobile phone, it brings opportunities, but also disruption.
This is why we recently decided to invest a billion kroner to establish six national research centers on Artificial Intelligence.
The centers will conduct research on how AI affects society. They will study the development of new technology, and they will make suggestions for how we can strengthen innovation and value creation both in business and in the public sector.
One can easily imagine that as long as there has been work at all, there has been a debate about the future of work. And my guess is there has always been optimists and always been those who fear for their jobs and their way of life. When the Samarians invented the wheel, surely there was someone who worried it could have negative consequences for those who were used to carrying things on their back.
The professor at LSE points out that there are at any given point in time several things happening at once. Some jobs are replaced. Some jobs will change. And as always with new technology, new kinds of jobs are created.
The point is, I guess, it is that change is rarely easy. That is why we have high expectation for our new research centers because there are serious questions to ponder when we talk about AI and work.
Questions about jobs, about ethics, about competitiveness, and security, and not least about inclusion. Those who know how to work with AI will be in high demand, and those without access to tools or training risk being left behind.
We need to make sure that we don't widen the digital divides, and that workers are empowered, not marginalized. If we make the right decisions now and remember to always put people in the centre of AI policy, we can set the course for the future of work that is both safer, greener and more productive. The biggest risk is not acting in time.
I look forward to the upcoming presentations and to the panel discussions where I hope that we can really look into both opportunities and the challenges that lie ahead. Thank you for the attention so far. Thank you all.
(Applause).
>> MODERATOR: Thank you very much indeed, Tomas. Let's go to the next set of opening remarks. I welcome the UN Under Secretary‑General for Economic and Social Affairs, Mr. Li Junhua.
(Applause).
>> LI JUNHUA: Good morning. Good to see you again in this Plenary Hall. Before our distinguished panel started sharing their thoughts, perhaps I could just share a few words from the UN perspectives.
We are at a critical juncture. Artificial Intelligence is no longer on the horizon. It is here, actively reshaping our economy, our future, our societies.
This transformation is evident in our daily work from the data we analyze to the countries we serve. AI is changing how Government operates and delivers the public service while raising new competences of capacity, ethics and equity, especially for the Developing Countries.
This revolution extends beyond job displacement. It's fundamentally alters how value is created, who benefits, and who risks being left behind. AI is entering every sector one from automation including hedge, education, logistics, law and finance, profounding tasks that require judgment, coordination, even creativity.
The potential is immense. So are the risks. AI can help us to address urgent skill shortages, make the work safer, smarter, more productive and unlock innovation in every corner of the world. However, the risks are equally significant. Widespread job displacement, absolute skills and widening inequalities between workers, companies and nations. That is why we must act collectively. Technology itself does not determine our future, but our policies and choices do that. We need to build inclusive ecosystem from education and training to the infrastructure and governance. We must ensure that the fair labor transition and modernize our social protection systems.
The core principle must be that AI serves the people, not the other way around. To achieve this we must international vest in digital literacy especially for women, youth and workers in the informal economy while promoting transparency, accountability and fairness in the workplace.
International cooperation is also very much essential because as no country navigate AI transformation alone. AI must be the tool to bridge the divide rather than deepen the divide.
This is not just a technological revolution. It is a social and political revolution demanding collective leadership. So let us use this discussion to share, reflect and build a common grounds in dignity, equity and sustainability.
Looking forward to hear your inputs which will contribute to the Norway IGF message to this year's WSIS+20 review which will be adopted by General Assembly later this year. Thank you so much.
(Applause).
>> MODERATOR: Under Secretary‑General Li Junhua, thank you very much indeed. Let's move to the people who are shaping this technology now, who are bringing AI technology to us. We have the first of our expert speakers, first of all, Sandro Gianella head of Europe Policy and Partnerships at OpenAI.
>> SANDRO GIANELLA: Good morning, everyone. Thank you so much for the opportunity to speak and share a few words before we have a discussion on the panel today. To share our thoughts about AI and how we see this impacting our jobs and as previous speaker said not just about the future, but how it's doing that today. It's especially meaningful to gather in Oslo, a city that embodies thoughtful governance, deep respect for social trust and rich tradition of balancing innovation and inclusion.
Norway's values reflect the AI future that we also want, one rooted in equity, openness and collective progress. The IGF also is one of the really truly global spaces where technologists, policymakers, civil society, activists come together not just to talk about technology, but to really shape how it should serve people. It's very aligned also with the mission of OpenAI which is to ensure that AGI benefits everyone.
We believe in the transformative potential of AI. It's a general purpose technology that not unlike the steam engine or electricity can enable and empower people and businesses while accelerating human progress. It goes without saying, so allow me a second to touch on it, that all of the work and what we will talk about starts with strong commitment to safety. Our team at OpenAI has been working on industry leading work starting with a preparedness framework which guides how we anticipate and moderate risks. We were the first to develop system carts which offer transparency into how models behave and where limitations lie.
AI has potential to improve education, increase collective capabilities and help us live longer and healthier lives, but unlike previous technologies, this one is unfolding much, much faster.
But it's shape is not predetermined. That's where we as policymakers, as technologists and stakeholders come in to help shape the future into one where everyone can benefit.
As said, today AI is already contributing to economic growth. Forecasts differ between 0.2 and 2 percentage points of GDP per year today. But beneath the macro figures we already see the transformative potential of AI in some of society's most important sectors today. In pharma we have a collaboration with Moderna and Sanofi in Europe where our technology is helping accelerate team development. In scientific research our models are being used by leading European laboratories at university.
In education we are happy to work with the Estonian Government who are thinking through how to bring AI to schools and students in a responsible way. And as for climate and the environment, we have worked with Amazon GPT where tools are helping university's Computer Science Department to generate conservation and health insights to help preserve the rain forest.
But, and I think this is especially meaningful for me and us at OpenAI, you don't need to be a leading pharma company or business school to access and benefit from these tools today. These tools who used to be only accessible as previous speakers said to R and D labs are being used by small businesses, by startups, by individuals, by NGO's across the world.
Entrepreneurs can use AI to analyze markets, generate product ideas, brainstorm, build prototypes and all without needing this full stack team to just get started behind them. One practical example of our effort to really improve access to the technology is an integration with our friends from Whatsapp, a platform that's already embedded in the daily life across many people in the globe. This is part of our effort to make sure that even in places where there isn't high speed Internet or where there isn't an access to advanced hardware, people find an easy way to interact with these tools and get the most of them. With such potential and opportunities in sight, we want to work with policymakers to ensure that AI benefits are shared responsibly and equitably across society. The AI area is an unmissable opportunity to drive growth and I think successful nations will turn these resources into competitive advantages.
In this AI age or the age of intelligence as our CEO Sam Altman likes to say, the resources are compute, data, energy and talent. For the discussion today we will have a focus on talent which I think is right and calls for an important discussion.
Even with the best hardware and data, the AI leadership ultimately depends on people, researchers, engineers and all of us and on informed users to future proof their workforce. And I know we will touch more on it on the panel. I wanted to offer ideas or things that we see Governments and societies do that we think are worth exploring. The first is an obvious one, broad and equitable access, no one left behind. We need to make sure that there isn't a widening gap of people who have access or don't have access to technology.
So from primary school on wards, I think we are inspired by the focus and effort that the Estonian Government is putting on it but we are seeing loads of Government across the world making sure that citizens and people have access to this tech. Governments must significantly expand investment in STEM education and specialized AI scholarships on the research side, equally crucial is large scale workforce reskilling through apprenticeship, vocational program, reenabling current workers to adapt skill for AI‑driven and evolving roles. But simpler than all of that, there is a lot of content and ways to learn about technology that's already out there whether you are using the tools themselves to learn about the tools or you look at something that we launched to play our part called the OpenAI Academy. It's part of our commitment to invest in people, not just in technology. It equips policy makers and future practitioners with the knowledge to understand, govern and apply AI responsibly, turning transparency into shared capacity and expanding AI fluency beyond a few global capital. We offered this platform at the beginning of the year and have trained 1.4 million people and we are looking forward for your feedback and ideas.
As previous speaker said I think history shows us as technology shift, so will the way that we work. It's always been true and it will continue to be true. Take radiology. AI tools now help detect cancer a lot earlier, but we don't need fewer radiologists, we need tools to help them see more patients and see them faster.
And we need tools that reduce wasting lists and get people into treatment faster expanding output. So today AI is primarily a productivity enhancer and a tool that we as humans can leverage. It offers task level automation, not job level automation.
Our models help clinicians reduce time spent on paperwork which allows people to spend more time on care. They are enabling doctors to spend less time on routines, time consuming tasks and spend more time interacting with patients. AI is also providing tools to scale the impact of workers in countries like India or Kenya. One example we like is a company called multi‑modal, digital green where they are delivering multi‑modal, multi‑ lingual and tailored chat bots for farmers to interact to get live information. The interesting thing is that if you think about these agricultural extension service, by delivering these through low latency and through our tools they have reduced the prices by 100X. So we have moved from $35 per farmer to 0.3% per farmer to get the same information.
Technological shifts will result in the revolution of existing roles or creations of new roles entirely. If we try to explain to our grandparents or our great grandparents what our jobs are like today, I think they would have struggled to try to understand what we do, and what we define as work and jobs. Our work has changed and evolved, much due to new technologies creating new jobs and changing the nature for work. AI is the latest stage in that constant process of evolution and change, and that is why the future proof of skills, literacy and education I explained earlier are so vital.
To conclude, AI's impact as we have heard is not just about growth. It's about the kind of growth that we choose to pursue as a global community. And it's how we manage it's transformative impact on society. We can choose to enable a more productive, a more inclusive and a more innovative future, but we must, of course, get the balance right on safety, on access, and on innovation.
And I think most importantly, which is why it's so good to have these debates at a forum like the IGF, we must work together. There is no single actor, no single company, no single Government that can do this alone. So with that, I would like to thank you for your attention, and I look forward to the discussion later on.
>> MODERATOR: Thank you very much, fascinating examples of what AI can achieve and I'm sure we will hear more examples now from our next speaker. I would like invite Chris Yiu to come up Director of Public Policy for Northern Europe for Meta. Chris.
>> CHRIS YIU: Thank you. Good morning, everyone. Real pleasure to be here with you today to talk about such as important topic around AI, the technology, and where it's going. We have heard some really inspiring examples already this morning and also a good outline of the topics we want to cover. What I thought I would do is try to ground the conversation a little bit in a few things.
First, just to speak a bit about the terms and what we mean when we an artificial general intelligence, for example, and talk about practical terms what this technology can do, and then really focus on Meta's commitment to open source, making sure that the AI technologies we are building are as available and accessible as possible to people all around the world.
Now, at Meta, we know that people use our technologies to connect with the things that matter the most to them, friends, family pursue their interests, find new experiences. Meta has been a pioneer in AI for more than a decade. It's the technology historically we have used to help people find relevant content on our platforms. It's also the technology we use to find and deal with harmful content on platforms which is important to us.
All of you know that the recent advances in AI have captured the public's imagination. We have seen the potential for huge advances in people's ability to be productive, to be creative, and also I think to drive important progress including medical and scientific research, which is optimistic about when it comes to contributions that relate to all of us and the world ahead. We have heard that AI has potential to be a leveling technology. Certainly one thing we see is for small businesses using our platforms and our AI tools help the small businesses and individual entrepreneurs to compete with larger businesses and bring their products to market in ways that weren't possible previously. And I think we will see more empowerment of small businesses, entrepreneurs and individuals from this technology as things move forward.
But I think just to ground us all, one of the first questions that people often have about AI is what exactly are we talking about? So here is how I like to think about it. When we talk about Artificial Intelligence, we are thinking about systems and technologies that are able to do what traditionally were the preserve of human beings. So in our world, this would be things like image classification or speech recognition where we have had a lot of recent advances.
And we then have GenerativeAI technologies, so these are systems which learn statistical representations of patterns and structures and data, and then can use these to generate new content, to have a conversation, and so on, so forth.
And then looking ahead, a lot of the debates and I think relevant to this session is the question of artificial general intelligence where we are talking about systems that are able to perform feats of cognition, reasoning, planning, perception, which really are taking us to human capabilities and beyond. And I think as we look forward, that is where a lot of the important conversations with policymakers need to be located.
Now, when it comes to Meta's contribution, our flagship GenerativeAI technologies are released as a family of foundation models we call Llama. Meta has a rich and long history of contributions to the open source community, and I know that open source and open standards and so on are something which has been an important topic of discussion in the IGF community and elsewhere over many, many years. And our Llama models continue the tradition of openness. These models are what we call open weight models. This means any developer can download and deploy models for themselves in their own projects with full customization and control of the systems they build. And I will say more about why open source is so important for this conversation in a moment.
Just, and I won't go through the detail up here, you can look it up after the session. We have a range of models available in this family, and the point is to make sure there are different technologies available for people in communities wanting to use it for different purposes. We have small models which are optimized to run on devices, so that if you have only access to low capability hardware or don't even have an Internet connection, you still have the ability to benefit from this technology. We have models which are able to reason over images as well as text and we have more advanced models which provide state of the art reasoning capabilities, but still designed to run efficiently and quickly.
And these models just to give you a sense of the widespread use have been downloaded more than a billion times. There are people all around the world in the open source community building and refining with these technologies.
Okay. So just to help us with the conversation about the future of work, some of the things which these open source models can help anybody to do with the hardware that they have access to, and I won't touch everything on here, but to pick a few examples, language translation using this technology is incredibly powerful in terms of bringing the world together and breaking down barriers.
And this really is an area where the ability to do this quickly and efficiently is tremendously powerful.
You see the development now of assistants and agents that can help people manage schedules, tasks, reminders, help people to be more productive in whatever it is that they are choosing to pursue.
You will be familiar with large advances in coding and software development that these generative models can reason over very large code bases. They can find and spot patterns, nuances and interrelationships that I'll lewd human developers.
Developers are able to do more than they could on their own. And I think in the sphere of education and learning, which I think we will touch on in the panel as well, for me, tremendous potential here to offer students opportunities for far more tailored educational content and supports, personalized assessments and really just break the tradeoff we have had in the past between trying to give everybody an education, and helping to ensure that what everybody has access to is personalized to them and their particular situation and needs.
This technology helps us along that journey and to break some of those constraints. And just to talk a little bit more about open source and why this matters so much to us at Meta, and I our CEO raved about this a year ago and talked in depth about our commitment to think way of doing AI development and there are three legs to this. We think open source is good for the software developer building technology and trying to innovate. It's good for us, but most importantly we think it is good ultimately for the world.
So in terms of the developer community, these open models, the ability to download and then fine tune and distill the models for your own purposes we think is tremendously powerful because it gives real control over making sure the model is customized to fit your particular needs wherever you are in the world, whatever sort of organisation you are, whatever scale you are at we think it's important that you have that ability to innovate on your own terms.
And also in some circumstances for people who have particular requirements around how the data is used and processed. So if you run the llama models on your infrastructure and the prompts you put and the outputs that come back out can remain entirely within your own purview.
This is good because it helps us as we see models to stay at the forefront of innovation, but most importantly this is good for the world. So we really believe that if we go down this open source route, we can do a few things. One, we can make sure that the widest possible number of people in communities around the world access to this technology. Number two, it helps to ensure that this powerful technology is not solely sitting in the hands of a few large corporations, but rather is something which is belonging to the community.
And we think that by doing this the pace of AI adoption can proceed more evenly and more safely than it would otherwise.
So I will wrap up there. There is a code here you can use to find more information on the models and experiment with them if you want to do that, but for now we have an important conversation to get to. So thank you very much for your attention and I look forward to the debates.
(Applause).
>> MODERATOR: Chris, thank you very much indeed. I enjoyed learning about the llama. So thank you. If you stay up here and take your place on the end here, and then I will introduce and call up the other members of our distinguished panel this morning. First, let me welcome Nthati Moorosi, Minister of Communications and science from Lesotho. Good morning.
(Applause).
And next, Tomas Norvoll who we have met this morning, State Secretary from the Norwegian Government. And we have also met Sandro Gianella if I could ask you to come up and take your seat from OpenAI.
And I'm delighted to welcome this morning the actor, producer and founder of HITRECORD, Joseph Gordon‑Levitt.
And we move onto Jennifer Bacchus, acting head of Bureau for the Bureau of Cyberspace and Digital Policy at the U.S. State Department.
Next, it's Ishita Barua, the author, chief health AI officer and Ph.D. AI in Medicine.
And finally to join our panel Juha Heikkila, advisor on AI at DG‑Connect at the European Commission.
So, without further ado, let's move onto our panel discussion here. We have about an hour or so to discuss some of these pretty difficult and challenging issues, but ones that offer great hope for the future of our economy. So let's start and think about AI obviously in the way it's transforming how we work, live, and interact right now, and I would like to ask all of you from each your of your perspectives what you think are the most powerful shifts you are seeing not just in the jobs but across society where the biggest new opportunities, the biggest risk. It's a lot to answer. I would ask you to keep your answers fairly brief because we have a lot to get through over the next few minutes, and Nthati Moorosi, perhaps I could ask you to respond to that.
>> NTHATI MOOROSI: Thank you, program Director, the moderator, and thank you for affording me this opportunity to talk a bit about what we are doing in Lesotho.
Artificial Intelligence as everybody has said this morning is a disruptive technology, but with a lot of good. It is transforming society, reshaping our public services are delivered.
In Lesotho we are experiencing the positives of AI. Although our digital development remains low compared to our peers in the region, we have made significant strides in certain areas. And I just want to talk about some of those.
In healthcare AI is helping us tackle high tuberculosis rates, particularly in the rural highlands. Since 2022 Partners in Health, which is a local NGO, and our ministry, they are using an AI technology named Q, which is also using another one called qXR. Both are AI powered tools They analyze chest X‑rays and detect signs of TB.
By flagging potential cases early, this tool ensures timely treatment, and in areas where radiologists are scarce, especially in rural areas, reaching even the most rural and remote communities. We also have some positives noted under agriculture where AI is driving improvements in food security. A locally developed application called Lava empowers farmers, particularly small holder farmers to upload crop photos and ask questions in their local language in Lesotho.
The AI analyzes the images, identifies issues such as tomato blight and provide tailored solutions that help farmers protect crops and boost their yields.
However, the developers face challenges of monetizing the app and accessing accurate weather data which are critical for maximizing this impact.
The Ministry of Agriculture Culture in collaboration with ITU and FAO, they are developing AI powered chat bot. This innovative tool delivers real time advice to agriculture extension workers offering guidance on crucial issues like pest control, ultimately improving the ability to support farmers across the country.
Similarly, we are developing a public service chat bot to assist citizens. This is now the E‑government services delivery. It assists citizens with practical queries such as applying for birth certificates, registering deaths and streamlining access to services and boosting efficiency worldwide. I just want to talk a bit about some of the challenges we are experiencing. The digital divide.
For us it's real. It means many rural farmers and patients still lack Internet access, and this leaves them excluded from these innovations. Privacy concerns are another critical issue requiring robust safeguards to protect sensitive data whether it's patients' records or farmers' information. Lastly, the change in jobs landscape driven by AI demands programmes to ensure our programmes remains competitive is part of the challenges we see. So I would like to just conclude and say that AI is making Lesotho services faster, smarter, and more inclusive from cleaning to farmers by bridging access gaps, safeguarding privacy, we can enhance full potential of AI while managing its risks.
>> MODERATOR: Thank you very much indeed. Let's look at it from a content creator point of view, Joseph Gordon‑Levitt.
>> JOSEPH GORDON-LEVITT: Thanks for having me. Well, I will talk about, you ask what are some of the great things happening. Let's talk about something that's super impressive in my world. You have maybe seen some of the new generative video products that can just make a video seemingly out of nothing, and they are incredibly impressive, and from a creative standpoint, I think there is something deeply inspiring about the idea that without a huge budget, without the resources that a traditional Hollywood production would require, you can make something that looks at this point close to as good as anything and in the coming years it will be I think indistinguishable from large budget content creation productions.
And putting that in the hands of anybody, whether it's a kid growing up in a suburb of LA like I was, or anybody else around the world, that's, again, a really deeply inspiring prospect to put these kinds of creative tools in the hands of so many people.
Now, to the risk, and the potential downside I see of products like this, the first thing you have to talk about is, well, how does a product like this really work? Did a company create a tool that can just out of nowhere make an amazing looking video? And the answer is no. It didn't do that.
What they did was they made a tool that is fed videos that were made by millions of people, millions and billions of videos made by people, and algorithmically crunches the data that maybe up the videos and then can output pattern‑following videos.
But it all comes from videos that people made. The tech product would not be able to make anything at all if it weren't for all of the videos that people made that were ingested into this model.
So where did those videos come from? Well, they came from people. Were those people asked permission in no. The companies that are producing these tools don't ask permission and in fact they don't even at this point disclose what data they have used to train their models. Were the people paid for these incredibly valuable products that are now generating enormous economic value off the backs of the creations of all of the people whose videos were taken? No. No one is paid.
And so right now there are a number of lawsuits of various content creators that are suing these companies and in my country those lawsuits have yet to be decided. We will see what happens.
There was a report that was put out by the copyright office in my country that says that in the opinion of the copyright office it's probably illegal most of the use cases of this training data being used without consent and compensation. The very next day after that report was put out, the head of the copyright office was fired.
The executive administration that fired her would not give a reason why she was fired, but, again, it was the next day after this report was put out. And I want to zoom out for a bit and talk about how this same principle applies to our entire future of work since we are here talking about the future of work. This is not just about the creation of videos. It's true that I have made my living throughout my life making film and TV and certainly my fellow entertainment industry workers are concerned about this.
But this same thing is going to happen and is already happening and will continue to happen at a greater scale throughout our economy. It's not just videos that are being stolen and used to train these valuable tools. This same thing will happen whether you are working in content creation or you are working in education, whether you are in Academia, you work in marketing, you work in logistics, you work as an engineer or architect, anybody that is delivering their work digitally is, I think, threatened by this.
And if we go by the basic principle that big tech companies are allowed to take people's data without permission and without compensation and use them to make money, what kind of economy are we headed for? What economic incentive do people have to be creative, to do great things, to work hard? I really think that if we want to have an economy in the future where people are incentivized to compete, to strive, to be excellent, we need to incentivize that hard work by compensating people when they create something of value.
And I will leave it there for now.
>> MODERATOR: Thank you very much. Some fundamental issues raised there, and that actually, so that's a challenge for Governments really, balancing out the opportunities and those sort of issues.
>> TOMAS NORVOLL: Yes, it is definitely. And coming from the Ministry of Trade and industry, I should be most into how this can reshape the industry. I would like to say that I believe that AI is a huge possibility for all sorts of Government also to uphold the welfare state, and thereby upholding the democracy, because if you look into how at least this part of the world is developing, we see we are lacking people because we are getting older and older, one year every year.
And so and we are using too much resources, and we cannot just put money into any kind of problem that will occur in the public sector, so we have to find the more efficient way to work, especially in healthcare and education.
The problem is that first of all, that is maybe the sectors where you will find most conservatism because you have strong professions that might have some kind of issues taking new tools into their work, but it's also the sectors where you will meet real risks concerning privacy and real risks of discrimination. So we have to kind of find this balance to make sure that we are not afraid of using new tools to work more efficient, but also that we protect our people, that we protect our kids and that we protect the rights that people have.
I'm very sure that we address these challenges best with global cooperation. I don't think that every single nation can make up some kind of framework that will protect people from any kind of risk. We have to find international regulations. We have to invest in our people, making them resilient to the threats that AI can represent, and if we don't manage to do that, we will come into a situation where what can be a very, very important tool that can do a lot of good for mankind will be something that people are skeptical about, and will be scared to take in use.
>> MODERATOR: Thank you very much indeed. We will have to look from Washington. Jennifer Bacchus, thank you for joining us, U.S. State Department.
>> JENNIFER BACCHUS: First and foremost I want to thank the Kingdom of Norway for hosting IGF. It's a real pleasure to be here. I think the enthusiasm for Norway hosting is evident by the number of people who traveled out here for this event. So thanks first and foremost to the Government because we know it's a really big lift to put on one of these conferences.
But to the topic of AI, I think the U.S. view of AI as really an incredibly revolutionary technology that has applications and impacts in economic innovation, job creation, national security, healthcare, freedom the expression and beyond is well known. As policymakers, one of our biggest concerns relates to efforts to restrict AI's development which from our point of view could mean paralyzing one of the most promising technologies that we have seen in generations, promises that we heard from my colleague from Lesotho. And we want to embark on the AI revolution before us with a spirit of openness and collaboration.
To truly harness the benefits that AI has to offer, we need to regulatory regimes around the world that foster the creation of AI technology rather than strangle it. In terms of risk, the United States is troubled by reports that some foreign Governments including here in Europe are using policies that could tighten the screws on U.S. tech companies with international footprints and we will not accept that, and we think it's a terrible mistake. We need to focus on opportunities to unleash our most brilliant innovation and use AI to improve the wellbeing of our nations and their people. Excessive regulation on the AI sector could kill a transformative industry before it can really take root. And we need to make every effort to encourage a pro innovation, pro-growth, deregulatory AI policies. Another major concerns of the United States is that some authoritarian regimes have stolen and used AI to strengthen military intelligence and surveillance capabilities, capture foreign data, create propaganda to undermine other nations' national security and violate human rights.
The United States will block such efforts, and we of safeguard technologies from theft and misuse, work with allies and partners to strengthen and extend these protections and close pathways to adversaries attaining AI capabilities that will threaten all of our people.
I would be remiss if I didn't just note to all of our international colleagues and friends that partnering with such regimes never pays off in the long term despite incentives that they may offer in the short term. So the United States is committed to making sure that RAI is the gold standard and that we are the partner of choice for the world. Thank you.
>> MODERATOR: Thank you very much indeed. Let's move to the health sector. Ishita Barua, how do you see the balance of risks and opportunities?
>> ISHITA BARUA: Thank you for having me. As someone working at the intersection of medicine and AI, I see this technology entering healthcare at a very opportune time. We often talk about how AI is disruptive, but in healthcare when it is applied thoughtfully AI isn't disruption, it's restoration. And because for decades healthcare systems across the world have been quietly accumulating what I define as care debt or care deficit. This is a growing gap between the care that people actually need and the care our systems can realistically provide due to rising patient volumes, more complex conditions, and a workforce that simply hasn't scaled to meet demands. And it's not that healthcare professionals don't care. They care deeply, but they are exhausted from caring too many for too many and with too few resources. For years patients have been remarkably patient. They have tolerated queues, waiting lists, rushed appointments and lack of follow‑up, not because they didn't notice, but because they understood that the system was completely overwhelmed and under strengthened. For now we have tools that can help patients and physicians and healthcare professionals and repay the care debt. AI scribes are freeing doctors from the burden of documentation. AI supported diagnostics are catching disease earlier consider. Language models are helping patients understand their care in more compassionate and clear ways.
But the real frontier, I think, the one I find most hopeful is where AI is not just optimizing healthcare, but also transforming it. We need to improve both the care delivery, but also medical discovery.
Take alpha Fold, which has mapped the structure of over 200 million proteins, the building blocks of life. Accelerating our understanding of biology and drug discovery in ways we couldn't imagine a decade ago. So everything from developing the future cancer vaccines, plastic degrading enzymes, so on, so forth, or robotic surgery where AI systems are utilizing imitation learning, which means robots watching videos and performing simple procedures with the skill level of human surgeons. This is research led by Johns Hopkins University offering possibility to meet the global demand for surgeons that are hard to train. And perhaps most astonishing brain computer interface in combination with AI. With the help of these devices people with paralysis can remain the ability to move, speak and even write through direct decoding of brain activity.
So there are a lot of opportunities here, and I think that the biggest change can be to move from a reactive healthcare system to a proactive one, and from managing illness to anticipating and preventing it from treating symptoms to understanding biology at its deepest level. But we have to be intentional. We have to mitigate risks and we are very accustomed to that in healthcare. If these tools are only deployed in healthy hospitals and wealthy places with a lot of resources trained on narrow imbalanced data sets, designed without equity in mind, we risk hard coding existing inequalities into the future of care.
The opportunity here isn't about speed or scale. It's about equity, and about giving more people access to the kind of care they always deserved, that is timely, proactive and highly personally.
>> MODERATOR: Thank you very much. I think that will be the last mention of equity on this panel and the importance of that. Let's turn to one of the areas where obviously there is a fair amount of discussion going on about regulation and how this should be dealt with, Juha Heikkila, I could ask you to speak, you are an advisor to the European Commission which is paying great interest in these issues.
>> JUHA HEIKKILA: Thanks very much.
First of all, the European Commission thinks actually that AI as a technology is a technology or set of technologies which has great potential, and it can bring us many opportunities and many potential positive effects as has been mentioned by previous speakers.
That's why we have very strong and increasing support in the European Union for innovation in this area. We think that we need trust. Trust is for take up and for benefits of AI to materialize. That's why we have innovation and risk‑based innovation which only intervenes where necessary. That's why we think it's supportive.
The labor markets and the impact on work, some of the questions are still quite similar than they were nine, ten years ago before we knew about GenerativeAI. The jury is out. We don't know what the net effect will be on jobs. We cannot put numbers on it. Studies are quite different in terms of quantification of the impact.
But, of course, what we do know is that it's mainly the routine tasks that are at risk, and in many ways this line may be moving up because GenerativeAI has proved to be very powerful. So those who are affected, they may be more numerous now than they were before.
And in that regard those who benefit also from this may be a slightly decreasing set of people. However, I think it's important to bear in mind that jobs will also be created. The job creation is often distributed in its nature whereas job losses may be more concentrated and more visible as a result.
And if something can't be automated, if a job can be automated it doesn't necessarily have to be, and many jobs do not lend themselves well for that, particularly if we talk about robotics. I want to specifically include robotics here because AI is not just on the Internet as I heard stated yesterday. It's also embedded in robots and autonomous vehicles, et cetera. In those cases, of course, we are talking about a different aspect, and robots are not yet dexterous as humans are in ways to carry out jobs that are important which seem benign for us, folding garments, waiting tables, doing haircuts, stuff like that. So there are many, many very sort of complicated questions related to this.
I would like to, however, highlight one aspect which I think is quite important and interesting and may not always be presented in these discussions which is the question of deskilling. I'm old enough to remember the time before navigators, and I sort of have noticed that the current generation, I don't know where we are with the alphabet, is it Z or are we in AA, so they don't necessarily know how to read maps.
So there is this overall risk, of course, the more reality on AI and automation, we kind of become heavily dependent on it. And we may not necessarily have then the required skills when we need them if that service is not available. So from time to time, we should maybe use those skills as well and keep that memory alive, if you like, which enables us to carry out tasks which, of course, we most of the time are happy to let AI do for us, simply because it's much more convenient, faster and also more efficient.
So this is something that I think is worth Director some attention to because it's after all an important aspect if we don't find home anymore that becomes a problem, of course. So I will stop there. Thank you.
>> MODERATOR: Thank you very much indeed. Let me move onto the next question now, question 2. So what guiding principles should shape national and global policies to ensure that AI supports decent work and fair transitions rather than deepening existing inequalities something that, Joseph Gordon‑Levitt touched upon, the fairness of the transition. Let's hear from you, Jennifer Bacchus.
>> JENNIFER BACCHUS: Thanks. I think we can all recognize and we can all say we have clearly a changing technological environment, and we need to adapt to this new reality without destroying our way of life. I think this is something we can all agree on, and we need to not disinherit workers.
We seek in the most basic terms to secure our economy, restore our middle class and uphold America as the planet's best home for innovators. As Vice President Vance the United States will maintain a pro worker growth for AI so it can be a tool for automation in the United States. AI will facilitate and make people more productive. I think this is something we can all agree on. It's also not going to replace human beings. We refuse to view AI as a purely disruptive technology that will inevitably automate away our labor force and we are hearing the ways that can help us and not just harm us.
We believe and we will fight for policies that ensure that AI is going to boost worker productivity, whether in the healthcare sector, in the agricultural sector, et cetera, that it's going to improve job quality and working conditions and unlock cutting edge economic potential. We expect that American workers will reap the rewards with higher wages, better benefits and safer more prosperous communities. AI is creating new roles like AI trainers, data analysts and human machine teaming managers. GenerativeAI can level the playing field for access to jobs, making it easier to build the technology and skills that have historically excluded otherwise very qualified workers.
We also see potential for AI to help with hiring. If designed transparently, AI systems can provide a record of how employment decisions are made and can help us ensure fairness is embedded in the process. As AI creates new jobs and industries, our Governments, businesses and labor organisations have an obligation to work together to empower workers all over the world.
To that end, for all major AI policy decisions coming from the federal Government, the Trump administration will guarantee American workers a seat at the table. President Trump will always centre American workers in our AI policy and we want to work with all of you to emulate this internationally. Thank you.
>> MODERATOR: Thank you very much. Joseph Gordon‑Levitt, you touched on fairness in your previous answer. How do you see it in this case?
>> JOSEPH GORDON-LEVITT: Thank you. Your question is what can we do? I think there is a basic principle we ought to adhere to and this is a perfect place for us to be talking about it. That basic principle that your digital self in the context of this panel, your digital work belongs to you. A human being that produces some data, whether that's data is their work, is their ideas, is their connections, is something they wrote down, is some digital deliverable from their job, any of that data, the human being should have some economic stake in that data. It shouldn't be allowed for a tech company to take that data and not compensate or not get consent from that human.
I'm not saying that the tech companies shouldn't be able to make money. They should be able to make money. I very much admire the work that Meta or OpenAI are doing and the tools being provided. But it's pretty clear that these companies are generating huge, huge economic value. And so it doesn't make sense to me why all of that economic value should go to the tech companies and none should go, zero percent should go to the human beings whose data are being taken without consent or compensation.
I think if you set up a system whereby people can be compensated for their creativity, for their work, for their data, now you establish a vibrant and vital market, and this is what we want for our economy. This is what we historically know works well for economies. We are sitting here in a western Democratic capitalist country, and I believe in that, but if we want that to continue to thrive, then we have to set up a way to compensate workers for good work that they do.
If you ask some of the leaders in Silicon Valley where we are headed, they talk about something called universal basic income because people won't be able to make money anymore because AI will be providing all of the economic value. The sleight of hand that's going on in that statement though is the idea that the AI is generating all of this economic value when in fact there is no economic value without all of the human contributions that were Hoovered up into these machine learning models. And so I think if we really want to have a pro worker stance, I admire the United States' advocacy to make workers central for our policy moving forward, if we want to really do that though, then we've got to set up a way to compensate people for the value that they are creating. I don't think that has to strangle the innovation. I think that that is the innovation that we should strive for, and that we can meet that challenge with pride and positivity, hey, let's build something that really is good for everybody.
>> MODERATOR: Thank you very much indeed. That was fairly clear. A good time to turn to OpenAI,.
>> SANDRO GIANELLA: What does it mean when we think about the way we as humans and workers are using the tools and how we think about the future of work and what it means to work, and what economic value we are creating, what the bright balance is between the economic value the tools are creating, how we will use them, I think there is a lot of joint learning we are still doing and that is happening right now.
I think there are three things that to me are important to add to the discussion. One, and I think the Minister touched on it well is making sure that there is access to the tools because one of the things that the IGF community has been good about and has been fighting the good fight for is to make sure we have equitable access and that we are not adding to a digital divide that we know we are all concerned about and we want to make sure we mitigate. One of the things we did more as a test but it turned out to be successful, is what are the different ways for people that may not be comfortable using a phone or computer to access this technology. I touched on one in my speech earlier, but another one we did was we set up a land line to be able to call into and access this technology, called 1‑800 ChatGPT. A lot of people thought it was a joke when we launched it, but it speaks to something that's important which is lower the barriers to access to this technology as much as we can. The second one when I think about the future of work. The combination of work and learning is very much intertwined. For as long as humanity has existed we have learned new skills and we have applied those skills that to things we found meaningful as humans, that help our communities, that provide economic value, and I think one of the things that excites me about the way that this technology is being used is that it can be used to learn itself. We know from the way that people are using these technologies that they are actually finding great ways to learn new skills, to learn about the world, to learn about our communities and to learn new skill sets.
So I think that's one where I hope we can be creative in working with Governments and others to rolling out ways to make sure people have access, and they then can use them to learn and to reskill.
And I think the last point I have made is as I think was mentioned in different parts of this panel, there are, this is a general purpose technology. This is posing important optimistic sometimes difficult questions about the right balance that we are striking, about how different communities, different industries are grappling with the changes that are coming. I think the Minister touched on it well in his speech, and I think that shows that the how of this technology being implemented, how are, whether they are industries, whether they are specific communities we are working with, the shape and the way in which we allow this technology to be used, the principles that we rely on and that is important to us obviously there is a difference in using these tools from healthcare to the creative sectors and I think what we are seeing is that all of these communities are grappling with these questions.
We hope we can do our part by being part of these discussions, by showing up, by being here and doing that in as transparent a way as we can.
>> MODERATOR: From the Norwegian Government, Tomas Norvoll.
>> TOMAS NORVOLL: Just two points, first of all, it is extremely important that we make the tools accessible. I mean, some of the AI tools, they can play a very Democratic role because it will give virtually everybody access to all kinds of information. If you look ten years ago, twenty years back, there could be a gap between those who had access to information, who had long education and those who didn't.
That also means we are using the right tools. People without extraordinary skills can do extraordinary things if you have the right tool and that opens some kind of Democratic area that is important. But we have to make sure that we do this in the responsible way. We have to make sure that the systems reflect our values, that they protect our rights, and that they promote dignity in work.
For example, for me it would be great to have an AI system that could in a way monitor my health, making sure that I make the right decisions on how to take care of my health.
But under no circumstances would I like the insurance company to get the same data. That would be just catastrophic in my example. And we also have to find systems to make sure that my data, either if I create something or it is just kind of data about me, they are mine.
I have, we have to find a system where that can be some kind of ownership, making sure that nobody can just steal it and use it as their own as a way to make profit out of it.
And I think that is one of the big things we have to find Resolution to. As I said earlier, the only way to do that is to do it internationally. I think the EU is doing a great job in trying to find a framework through the AI Act to see how can we make sure that we put people first when they are discussing AI, but we still have a very, very long way to go before we have a kind of optimal system into this.
>> MODERATOR: Tomas Norvoll, I'm very glad I wasn't wearing an AI health monitor as I had my breakfast this morning. Education systems are under pressure to evolve alongside the change in technology. How can AI expand access to quality education? What does quality education even look like in a change the labor landscape.
>> NTHATI MOOROSI: Thank you very much once again. AI is coming at the time when Lesotho we are just dealing with our education trying to find ways of improving the education system.
Lesotho's education system faces tremendous challenges. We still have students who walk many, many kilometers to get to a school. When they get to a school, it's one teacher to a minimum of about 60 students in one class, and some classes have two classes in one room. So AI is, I see it as a tool that is going to change our education system considerably.
We have challenges from basic education to tertiary education, but I want to confine my responses to the challenges and opportunities in the basic education system. Challenges include, as I said, overcrowded classrooms with one teacher to for over 60 students in some cases. We also have a very specific case of vulnerable groups such as head boys leaving the high lands who most of the time they miss school to attend to livestock. These conditions hurt their education. To many young people each year some even drop out.
AI offers exciting opportunities to change this. It enables the creation of personalized learning experiences for every student whether they are in a busy city school or a remote high land village. A learner in the city and a head boy in the rural areas can receive lessons tailored to their specific pace and learning style, and language preference, such as Lesotho or Phuthi or Xhosa which are the minority languages in the country.
AI applications can provide mathematic lessons that adapt to each student specific needs. Many head boys struggle with English fluency, yet most subjects are taught in English language.
This approach not only supports overworked teachers, but also helps under resourced students making education more accessible to everyone. However, we must ensure that AI solutions align to our culture. If we use English only, tools built on foreign data, they don't work for our rural head boys or Lesotho speakers, and they leave them behind.
That's why our AI policy emphasize building a human‑centred AI ecosystem. To sum up, AI can expand access to education in Lesotho by personalizing learning and reaching remote areas, but only if it is culturally relevant. By supporting teachers, AI can improve quality of our education. Thank you.
>> MODERATOR: Thank you very much indeed. Let's turn to the European Commission, Juha Heikkila.
>> JUHA HEIKKILA: Thank you. So indeed as the Minister said, AI can actually improve access to education and it can allow sort of the building of tailor made courses, tailor made study programmes and in that sense it can be a great asset. However, in that sense, of course, I think it's preferable to see AI in a support role rather than taking over, but it can be a significant contributor to access to training and education.
More generally, of course, people should be ready to work with AI, and some kind of AI literacy will have to be a part of the education. This is already because there will be increased coworking with AI whether it's stand alone or physically embedded in robots or other kinds of autonomous systems. And it is important for the workforce also to be able to have the opportunity to upskill and reskill.
This is also why we in the European Union, we have just recently launched what we call the AI content Action Plan in which we focus on skills as one of the five pillars promoting AI literacy is crucial there, and we also want to capitalize on the network of what we call digital innovation hubs which we have built over the years which are basically hubs which provide services to help companies and the ecosystems in regions to do the digital transition and have the necessary wherewithal so that they can actually take part in the digital transition and benefit from it.
So we have focused on that quite strongly now in our most recent policy statements and we will be building on measures on that basis. Thank you.
>> MODERATOR: Thank you very much. Chris Yiu, you touched a little bit on this in your presentation earlier, the opportunities that exist for AI in the education area.
>> CHRIS YIU: Thank you. So I think this question of the AI opportunity in education is significant and I think the Ministers and others have touched on some of the potential ways it can benefit people. The way that I like to think about it is it's both for educators, and for learners. So for the educators, having access to tools and technologies help them do their job better and more effectively and more productively is tremendously important. There are a wide range of challenges around the world that people face in schools and other educational environments. There are many things that AI can do. There are many things that AI can't yet do and where human connection and the human touch is important, and so if you can use the technology to lift some of the burden for educators to take away some of the administration, to handle some of the work they spend when they are not face‑to‑face with students, that is tremendously important in many, many contexts.
And for the learners themselves, to be in an environment where for the first time now you have the opportunity, perhaps, not to be in a one‑size‑fits‑all learning environment, but to have access to additional tools and support that speaks to you, your interests, your passions, your needs, that, again, which is something which historically has been the preserve of a few and now ought to be available to a far wider range of students and learners around the world in different settings. So it should be a great and I think will be a great leveling technology.
And we see tremendous examples of how AI models and others being used around the world for this. And particularly to the Minister's point about a language and culture, one of the things which is dear to our hearts around our open source approach here is we see people in different settings taking the models that we produce and invest in but then fine tuning those to reflect local language, culture, dialects, all of which is important to the opportunities that we serve. So I think in all of this it's important that we lean in on the opportunity in education. We have to equip young people both to make the best of these tools and also to be fluent in them when they go out into the wider world. Thank you.
>> MODERATOR: Thank you very much indeed.
>> ISHITA BARUA: In a world where AI can generate content faster than we are able to consume and read it, the true strength of education stimulus is not how seamlessly we are able to adopt new tools, but in how deeply it values domain expertise, cultivates human judgment and actively resists deskilling and cognitive outsourcing.
We don't need systems that simply automate every task, we need systems that sharpen our ability to think independently, reason critically and build deep understanding. How are we incentivizing that? How are we incentivizing healthcare professionals to cultivate their skills and domain expertise. If you can simply ask ChatGPT or any other language model to do the task for you.
And also what really worries me is that we are seeing a quiet shift. More and more people read summaries instead of full texts. They write by prompting a language model with a few key words and receive a polished paragraph in return. Where is learning in that? It may feel productive but it's changing something fundamental about how we learn, and for me, for instance, writing isn't just a way to express thought. I write to think. I don't truly understand something until I have worked through it on page. Failed and revised it and clarified it.
So the French philosopher Rene Descartes famously, said I think we need a revision of that. My take on that is, I write, therefore I think, and, therefore, I am.
(Applause).
I think that quality education in this new labor landscape means creating learning environments where people learn to use AI. Yes, that is important. But also when to question it, override it and think beyond it. And it's about forming thinkers, not just front engineers.
>> MODERATOR: That goes back to the question, thank very much, at the beginning where I raised where Chief Executives are worried about how junior executives will learn how to make decisions that will allow them to become senior in their careers.
We have eight minutes left. That tells me out the use of AI that we have a minute for each of you. I would suggest that to make this a choir fire round let's sum up from each of you how you see everyone working together to try to get this landscape right, and any final reflections that you have on how we ensure that the benefits are shared across sectors, and not just concentrated in tech companies or tech hubs.
So a minute each, Ishita Barua, you get the privilege of going first.
>> ISHITA BARUA: There is a dimension we haven't bone about and that is the dimension of gender there are two Nordic studies that women are adopting tools like ChatGPT more slowly than men but because of lack of competence but due to differences in digital confidence and how technology is introduced in their work environment. Women in high income countries are three times more exposed to automation risk because they are overrepresented in roles that are highly susceptible to AI driven train, administrative support, healthcare, education. And if we don't address this explicitly AI risks becoming a new layer of structural inequality, reinforcing old patterns are the guise of innovation.
And that's why inclusive growth must also mean gender responsive AI strategies in workforce development, access to tools and in who gets to shape the systems we are actually building.
>> MODERATOR: Well done, you got it within a minute. Thank you very much. Sandro Gianella, you have heard a lot here.
>> SANDRO GIANELLA: I will give it a shot. I think the two things I would add is curiosity and agency. If we think about learning and the future of work, I think making sure our institutions, our tools, our technology is built for people to feel the agency that they have and shape the environment they live in and remain curious. I would like to pick up the point that Ishita Barua made around are we sure we can learn with these 2508 tools? I think it's an important question that we think about. We have an entire team of education practitioners that are working through what are the way in which learners, students and teachers have found ways to tailor the tools so they don't jump into the answer every. So they push back on thinking and reflect critically about how we are thinking about a subject and I hope, and that's my plea, is that we find ways to use knowledges not to narrow the scope of the things we think about and we know, but that we broaden the scope, and we allow these tools to help us to think more critically about our own biases, our own reflections and I think there is a way to do that.
>> MODERATOR: Thank you very much. Very interesting there was a survey out recently that showed since 2010 our ability to learn has started dropping off quite substantially and we all know what started in 2010. Let's move on to you Juha Heikkila.
>> JUHA HEIKKILA: So training is important as was mentioned and highlighted. So we do need to be prepared in order for us to reap the benefits, and the panel made it clear, we need to be ready, prepared and that is key. I think that is also important to sort of channel funding and research towards public objectives, health in particular has been mentioned many times here. Immensely important, obviously benefits society at large and individuals, of course, in many ways but other public services as well.
And, therefore we are very closely monitoring this in the European Commission to see how these things develop, how things pan out and what will be the impact on the workforce and the workplace in general. I think what is encouraging here is that there is increasing attention to this. So a panel like today's is not an exception. We see this at different events, so I think that there is this common awareness that this is an important aspect we need to focus on.
>> MODERATOR: Thank you very much, your final reflection on where we stand.
>> TOMAS NORVOLL: Well, first of all, I think it is important that we dare to use these new tools. It is also important that we make sure that everybody has access whether you are like me, live above the Arctic circle or if you live in an metropolitan city in Europe or the United States, you have to have access so it's not just the elite that have access to the new tools that are emerging.
From a governmental side, it is extremely important that we have a framework, that we have rules, regulations that put people first into the discussion. And finally, I think it is important that we arrange more IGFs and other arenas so that we have a place to discuss how we are going to cope with the new challenges that are ahead of us.
>> MODERATOR: Thank you very much indeed. Jennifer.
>> JENNIFER BACCHUS: So in my position where I have been for three years, I have traveled a lot around the world. I have talked to lots of people, and the number one request I have gotten up until now has always been about digital and cyber workforce development. It is at the centre of what everyone wants, and we are seeing an evolution where we are talking about AI workforce development, and just like workforce development where the United States led the way, this administration is focused on making sure that our workforce will be prepared for this new economy, that we can demonstrate how you do it, how you think about these things in a deliberate way so that in fact we can have workers that can use this technology, that can be the human in the loop, that can question things, not just accept the answers, but look at it. I think these points are incredibly important, that these are enabling technologies, not meant to replace humans, but meant to help us be more productive, just like calculators were a tool that I have to tell you my children are still learning to do Math. They don't like it. They want to do Math on the calculator, but just like kids are learning how to do Math, kids are still going to learn how to reason, how to write, how to do these basic things, so how do you then say you know these basic skills and now you will use AI to enhance that.
So I have to say first of all, I am optimistic that we are going to be able to figure out a way to do this, that we do have people around the world looking to promote policies and academies where you can do the AI education. But I think just to conclude, what we have seen is too often regulations are really being designed to try to control AI rather than to unleash it. That ultimately what we need to do is we need to look at AI as a tool of prosperity, and we need to not clip the wings of the new companies. We need to embolden our innovators so that we can have all of the positive benefits we talked about and ultimately consumers and workers alike will be able to benefit.
So all of our efforts should be aimed at innovation that will deliver real world benefits. Thanks.
>> NTHATI MOOROSI: I think the biggest words for me in closing is inclusivity is collaboration. AI economic driven growth requires all to act, Governments, international bodies and other stakeholders to ensure equitable benefits across all regions and sectors.
Governments have to build AI enablers, prioritize governance and ethical policies. For example, a whole of society model have to be engaged. Academia, civil society, industry, to create sustainable AI ecosystems that foster transparency, inclusivity, adaptable to local context like agriculture and small businesses. International partners in the same vein need to support capacity building efforts that are sensitive to local contexts including AI tools, local language models, and global support is needed for technical training that can equip young people with skills necessary for high quality AI jobs rather than entry level positions thereby promoting economic equity.
And Private Sector in the same way should collaborate with Governments and create ethical AI solutions that respect human rights and preserve cultural heritage. Thank you.
>> MODERATOR: Thank you very much indeed. Chris Yiu.
>> CHRIS YIU: A couple of things to conclude here, number one, I think we all know in the end technological progress is the road to innovation, it's the route to prosperity and a safer and more secure world. The AI technology we are talking about at the moment is very much in its infancy and so innovation is important. We should pay attention to the questions around rules and regulation, but we mustn't get too far ahead to a place where our ability to unlock benefits is overly constrained. I think Governments around the world are talking about that a lot now, and we think it's a very important thing for people to stay focused on.
The second is just to say, I think sometimes this can be an abstract conversation about AI, and I just want to bring us back to the human side of this. I have a pair of AI glasses with me. These can translate people speaking in other languages so that I can understand them, they can describe things for people who are blind or visually impaired.
This is a tremendous humanizing technology, and that's one of the reasons why innovation is so important.
>> MODERATOR: Thank you very much, Chris, very useful for Americans trying to understand British people, I'm sure. Last but not least, Joseph Gordon‑Levitt.
>> JOSEPH GORDON-LEVITT: Thank you. I want to pick up on something Chris, my fellow panelist from Meta said about this technology not only being good for the companies but wanting it to be good for the world. With respect, Meta cannot prioritize what's good for the world. It's not built to do that. It's a to for‑profit company and it has to prioritize value for shareholders. I ran a startup, obviously much smaller than Meta but I know what it's like to have investors and shareholders and to move numbers.
The way the technology will work is in partnership with innovative and proactive companies like Meta or OpenAI working together with policymakers who do set up rules. This is a false dichotomy this contrast to say that innovation is the opposite of rules. That if we don't have any rules, then the competitive market dynamic will force these companies to build stuff that is bad for the world, that harms the world, that they can't do it themselves. The Private Sector can't do it themselves. That's why I take a lot of heart in being here with so many people doing great work in the public sector because we need a partnership. We need a partnership between the Private Sector and the public sector. We need to have great companies building great things and we need to have rules of the game that can help that benefit everybody.
That's what we need.
(Applause).
>> MODERATOR: Thank you, thank you very much indeed, Joseph Gordon‑Levitt. Thank you to the panel. I'm struck by this discussion in the past hour and a half because it reminds me very much of the discussions I Chaired in the early days of the Internet Governance Forum, the first forums, 20 odd years ago where we were then discussing how to get through the challenges of the Internet in its early days. Somehow we found a way through that. I guess that gives us hope we can find a way through this as well, but many of the things that were said today remind me exactly of this the sort of arguments we were discussing then. I would like to thank our panel, as William Shakespeare might have said and certainly wrote, time's winged chariot, it got away from us. Thank you to the panel, thank you to you and the audience in Lillestrøm. Thank you to the audience online. I hope you have a good morning. Thank you.
