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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>> TAYYABA IFTIKHAR: Hope everyone can hear me. Hello everyone. Good morning and welcome to the session Digital Dilemma AI Ethical Foresight Versus Regulatory Roulette. My name is Tayyaba Iftikhar, digital policy and governance specialist, and this is a conversation that I've been looking forward for many weeks.
Today is the final day of IGF 2025 and it's fitting that we're closing with one of the most important global governance challenges, how to regulate artifical intelligence in a way that is both ethical and enabling. Is that even possible?
As awareness of AI's power has risen, dominant response has been to turn to AI ethics. Ethics, simply put, is a set of moral principles. We've seen governments, companies, and institutions role out principles that guide framework meant to guide responsible AI development.
Here is the problem, when ethics treated surface level add‑on, often lacks teeth to create real accountability or change and that is where regulations grounded in ethical foresight being essential. We'll be unpacking challenge today through insights from multiple regions and perspectives joined in person by three incredible speaks.
AI governance consultant Global South, Alexandra Krastins Lopes, and integrity tech ethics and additional democracy consultant joining us in a short while. Vibrant workshop colleagues, Muhammad Umair Ali and Harisa Shahid.
Online moderators, over to you to introduce yourself and online speakers.
>> MOHAMED ADED ALI: Hello. Adjust just my text. Welcome to our session. I'm Muhammad Umair Ali, serving you as the co‑host and online moderator for this very session. Briefly about my introduction. Graduate researcher in the field of AI and public policy. I'm also the cofounder and coordinator for the Youth IGF Pakistan. And by my side is Harisa Shahid. Turn on your camera.
>> HARISA SHAHID: Hello. Pakistan organizing for the Youth IGF along with information security response Pakistan this year. Also a fellow. Thank you.
>> MOHAMED ADED ALI: Joined by speakers from the United Kingdom and Canada, senior technology policy advisor for the Office of Privacy, commissioner in Canada and Mr. Lawrence in the United Kingdom chief of have staff and institute of AI and law. Welcome aboard everyone. Over to you.
>> TAYYABA IFTIKHAR. Am I audible? Thank you so much for letting me know. I'm going to repeat myself. We'll begin with a round of questions for each five speakers, one each five minutes per speaker. Towards the end, we will be taking pictures. Don't run off. Start with many of the AI frameworks we see today cite ethics as a very important aspect. When you look at it closely, ethics often feels like add‑on rather than a foundational principle.
From your perspective, is that enough, and more importantly, what does it look like to truly embed ethic foresight into government structures to shape the direction of AI development from the very start?
>> ALEXANDRA KRASTINS LOPES: Great. Thanks. Honour to contribute to this important discussion. And while I have probably funded insight organizations called laboratory public policy, and served few years in the data protection, resilient data protection authority, today I speak from the private sector perspective.
I represent Brazil law firm, provide legal counsel on data protection, AI, cybersecurity, and devising multi‑national companies including big tech, law matters, government affairs.
When we talk about embedding AI governance to not talking about simply including list of ethical principles, regulation, or policy document, talking about interactive ongoing process, one is operational not theoretical.
Ethical foresight means anticipating risk before harm occurs. Requires mechanisms to ask right questions before AI systems deploy. Are systems fair? Are they explainable? Reinforce historical discrimination? Are they safe across different contexts?
That foresight must be built into organization governance structures including AI ethics committee, committees impact assessments, internal accountability protocols that operate across entire system.
AI systems also requires clarity about roles and responsibilities within organizations. Therefore, ethical foresight is not just job of the legal or compliance team. There is engagement from the product's designer, scientists, business leaders, and most importantly, designers need level commitment.
At the same time, foresight must be context aware. Many global frameworks are still shaped primarily by north country perspectives with assumptions about assumption, economic and regulatory capacity, and also tolerance that did not necessarily reflect their realities of the global majority. So regulatory debate should be connected to so much context.
Brazil, for example, historical inequalities, specialism challenges for entrepreneurship alignment to the institutional power. Embedding ethical foresight governance requires abstract principles by setting minimum requirements rather than imposing one‑size‑fits‑all model.
Tools can be adapted to specific condition such as voluntary code of conduct, soft law mechanisms, AI ethics board, and flexible risk‑based approaches such as, additionally, national policies may have different strategic goals, technology development, maintaining geopolitical literacy, protecting ethical.
Have some countries, for example, tend to emphasis ethical values prioritize advancement social risk, national regulatory fragmentation, and normative conflict, safeguards promotion of technological progress, investment and global competitiveness.
Scenario proposal I bring for reflection to using, need to establish global AI governance platforms capable of harmonized minimum principles, safety ethics, and accountability while respecting local specificities tools, voluntary codes of practice, which allow business to anticipate and mitigate risk without restricting innovation.
Additionally, there should be parameters for cross‑regulatory corporation for reinforcement in accountability. This jurisdictional fragmentation makes enforcement difficult especially with platforms that operate globally. Accountability is local. Advising companies I've seen that they were willing to act responsibly and ethically, international cooperation certainty are essential for that to happen.
Thank you.
>> TAYYABA IFTIKHAR: Thank you so much. As mentioned, ethical foresight is not just job of legal team multistakeholder process. Now we'll turn to online speaker. Moritz, if you're there, you've been keeping very close view on how AI regulatory framework is evolving, where they're falling short. From your perspective, key loopholes, blind spots in current AI regulation, and what would that take in terms of practical terms to close these gaps and build a governance model that builds distrust and resilience? Over to you.
>> MORITZ Von KNEBEL: Thank you. Thank you for having me. Asked this question, what are the regulatory gaps that we see. I think that assumption already is a bit flawed and mistaken because that would assume that around these gaps, we have well‑thought‑out systems, processing, and frameworks that I don't think we have.
So I will employ a metaphor used by a professor of mine. Said he does not have knowledge gaps because would be just too large, but he has knowledge islands and those are surrounded by a lot of ocean that we don't know about. And then those islands well‑connected enough, then you can travel back and forth, still kind of works, more gaps than there is actual substance.
So with that caveat, look at where those gaps are clearest or where the ocean is deepest, so to speak. I think, on the domestic level, I would identify two big items. One is lack of technical expertise. Regulators often look at the deep technical understanding, needed to effectively oversee those rapidly evolving AI systems.
Especially true in the countries that have historically not have the kind of capacity and resources to build up that infrastructure and institution. Creates reliance on the industry for setting standards for self‑reporting for self‑assessing the safety of their model. That makes it very difficult to craft meaningful technical standards on the political level in these very deep‑sea areas.
Another one is that we often see reactive frameworks. So current approaches largely respond to known harms and try to track when a harm occurs, but they do little in terms of anticipating emerging risks.
If you think that is where a huge amount of risk in the future is going to come from, frameworks need to be adaptive to that. And pace of AI development which proceeds at breakneck speed consistently outstrips pace at which regulatory systems can adapt, which is a huge challenge.
This is national level, one item feeds into rather problems, jurisdictional conflicts, races to the bottom, and then that turns into sometimes unjustified sometimes justified fears of other regulation. Different national approaches, but also international approaches like one that EU creates a plot complexity for regulation.
China focuses algorithm risk base. That creates regulatory patchwork. Difficult to navigate. Creates room for regulatory arbitrage and so similar to how you would move your company to a country that has very low tax rates, you might do the same when it comes to regulation. Create incentives for countries to water down regulation. Amplified, we do not know enough, a lot of terms that are used in concepts like risk, systemic risk, insufficient, defined no consensus what that means.
Maybe gloomy note, a way to close these gaps, or rather, to build bridges between those islands, that we already have the UAI and some of the frameworks exist around the globe. Rather than having static rules, we have framework that can evolve with technology and rather quickly. So that could mean that you have principles‑based regulation and these technical implementation standards can be updated through streamlined processing in secondary regulation.
You could also have regulatory sandboxes where you try out new approaches and see what works. Have quick feedback loops, which maybe governments aren't historically good at, but definitely getting better at as we speak.
Need capacity‑building, expertise lacking in government and elsewhere. Independent technical advisory groups could be useful that include perspectives of different people, and that also means that we need inclusive and novel approaches to engage stakeholders. We need dialogue and diplomatic efforts, so I said that some terms not sufficiently defined without a shared language, the landscape will remain fragmented. Incentives to cut corners will remain. So we see some work on this with international reports coming out and international dialogues, safety for instance, but much more needed to establish on census on the key questions because only then can we start to think about regulatory framework.
And one last thing, because I do work on AI, I have to flag this. Might not be ways to leverage AI for these processing. Little work gone into it and much more needed. There are many more gaps and many more traditions we could talk about leave it happen. And happy to receive questions any or all things in the A.I.
>> TAYYABA IFTIKHAR: You mentioned shared language. Can you elaborate more on that, Moritz, on that because it sounded really interesting. Spans fundamental. What is the risk. AI system luckily OCD. Provides definitions most people are happy with.
When it comes to give you concrete example, systemic risks in the European Union under the AI Act. This will influence a lot on how government models are government and deploy and developed future AI since that is the case matters what people think of our systemic risks.
It's not a field that has centuries of researchers for decades. Understand things under system risk as others do. Unless you have consensus on this, very difficult. That is on the fine grain regulation and specific legislative framework.
High‑level conversation about what are either most important risks and try to create consensus on this. Again, different cultures, different countries, see AI in a very different way. If you consider that, that makes it difficult to cooperate and collaborate internationally. So to establish a shared language around what does AI risk mean, and specifically focused on risk here, same goes for benefits, what benefits we care most about that will be needed.
That again also touches on the technical expertise a lot of this requires, technology knowledge you need to know what accountability is and what is necessary robustness is of AI model, so that further complicates things.
>> TAYYABA IFTIKHAR: Thank you so much. The enlightening main key takeaway, I could see different countries see AI different way. I think we really need to explore that further. I'm going to go to you now. Given how borderless technology is, there is a real challenge around jurisdiction and enforcement and I know Moritz touched upon the way platforms operate globally, but the laws don't.
What opportunities to see cross‑border regulatory corporation and how can regulate corporation help tackle jurisdictional conflicts and enforcement barriers especially for digital platforms may be lightly regulated in one country, but highly impactful globally. Over to you.
>> VANCE LOCKTON: Sure. Thank you. Very interesting question. We get into this idea of regulatory cooperation because flagging not only understandings of official intelligence different across countries. Artifical intelligence such a difference. What the regulatory frameworks actually exist and what can be applied that once we're into the realm of enforcement, certainly there is some countries that have attempted to do, make sure shared enforcement efforts. I don't think those are necessarily where we need to focus our effort. Necessarily going to be the most effective way to address some of these issues.
I think what really needs to be happening, talking about regulatory enforcement rather than shared enforcement actions, really has to be how can regulators have more influence over design and development and deployment decisions that are being made when these systems are being created or adopted in the first place.
Something that a lot of organizations are starting to try to wrap their heads around. I look at documents like the OECD, has a framework for anticipatory governance, anticipatory governance of emerging technologies I don't have any particular connection to.
OPC, my organization, doesn't have particular endorses this document, kind of creates this useful framework for me of the elements that they set out in this framework, what this regulatory governance needs to look like. Saying needs establish guiding value, extra strategic intelligence, bringing stakeholder engagement, regulation, international cooperation. We don't want to walk through framework.
Useful pieces come out of that, because from a regulatory perspective challenge, we don't get to set the environment in which we work. Generally speaking, regulators are not going to be the ones who are drafting the laws that they're overseeing. We may be able to fineprint into their drafting but, by and large, we're going to be handed a piece of legislation over which we have to have oversight.
So there are elements even within that, even within that, there are elements of discretion as far what kind of resource can be applied for, what strategies can be applied to particular problems. Often, a lot of statutes, there will be considerations with respect to appropriateness or reasonableness.
Critical governments, for the challenge you set out, idea of international impacts of AI systems where, frankly, as a western nation, we aren't necessarily going to be able to have that direct visibility, direct insight into the impacts of that system on global majority. So we aren't necessarily going to have that full visibility into what safeguards need to be pushing for appropriate purposes or what reasonableness actually means in the context of these AI systems when we aren't seeing what the true impact of these systems are.
So having those kind of dialogues amongst regulators, to share that cultural knowledge is going to be a critical piece of this going forward.
Just the sheer regulatory cooperation of understanding regulators, who has what capacities in AI. As Moritz flags, for a lot of regulators, there isn't necessarily going to be that technical expertise. Quite understandable. Newer data protection authorities or some of the less resourced of the authorities, you might have a dozen staff for the entire regulatory agency, that's not the dozen staff on AI. That's a dozen staff covering privacy or data protection as a whole. Obvious isn't only a piece of AI regulation. Just kind of the piece most familiar to it. That's why I'm kind of focused on it.
Might have dozen staff. Canada has but 200 staff. We have a dedicated tech lab designed to be able to kind of get into these systems, take them apart and really understand what's happening under the hood, a lot of these AI systems.
Look at something like the United Kingdom Information Commissioner Office has well over a thousand staff. So over a thousand staff and a lot of programs set up for ways that you kind of have more innovative engagement with regulators around these like regulatory sandbox, understanding amongst regulator who has capacity within AI is going to be critical piece.
I think having that shared understanding of who can do what, what the true risk and benefits are going to be, is such a critical piece because one of the biggest challenges for me that I'm kind of seeing from regulatory perspective is, again, western regulatory perspective, I'll say that there is this narrative that coming out that AI is such a sine qua non, essential piece, future economic prosperity of a nation or even future security of a nation, that there's this idea that any regulation that creates restrictions on development of AI is a threat as opposed to the opportunity, or opposed to this necessary thing to get to, responsible and responsible innovation of being able to have that real understanding of what the potential risks are, what potential harms are, and realistically, what benefits we're trying to achieve. Not simply just, again, making stock prices for handful of companies go up or making overall GDPR of a country raise.
>> TAYYABA IFTIKHAR: So sorry. 30 seconds left.
>> VANCE LOCKTON: No problem. Again, we have need to have that ability to counter that narrative and within countries or regulators getting better at having that cooperation amongst various sectors. So we are working towards having better cooperation internationally and finding soft mechanisms, finding ways to have influence over design and development.
Again, it's a work in progress, but my overall message is going to be we just need to reframe regulatory cooperation away from enforcement cooperation and to finding opportunities to influence that design and development. I'll stop there.
>> TAYYABA IFTIKHAR: Thank you so much. Thank so much for joining us. I love to talk to you about power and participation shifting the lens to inclusion, which is a very important part of artifical intelligence.
So we see that AI governance conversations are often dominated by handful of powerful perspectives. In your view, whose values are shaping the way AI is being regulated now and what would it take to insure that voices that are marginalized or under‑represented if communities are not just included, but also influence the decision‑making.
Thank you. I would just like to start with what I view as the ideal on AI governance. I think previously speaking, have kind of highlighted major challenge in that lack of shared language idea that AI like all together knows no jurisdictional borders. It's global.
What I think ideal would be is some form of international law around AI governance. And through that process, perhaps run through the UN. Ability to get more inclusive process that includes language, the ideals, ethical systems of various countries. I think that is the direction we need to be going.
I think experience from kind of over the last year with social media and governance and that difficulty with different countries, some instance is not having laws, regulations, policies in place.
Others doing that. There's a lack of proper oversight. I think it's an opportunity to now, therefore, international law to be drafted and as it stands right now, outside of what I think is the utopian, great thing to have around AI governance.
I think two challenges of inclusion. Right now, one is that in the Global South, particularly in Africa, there's policy absence. Many African countries, African countries, AI not a consideration. That is not because it's just something that is not viewed important. Conflict with bread and butter. Most of these countries are more concerned or more focused those type of things. Because of that, there is an exclusion in those discussions because that is just a process that hasn't taken place in those countries.
Think I would like to see more African countries, countries in the Global South, including themselves in those conversations by beginning to begin the process of drafting those policies, crafting those laws, and always say that may appear incredibly complex, but I think there is a way of looking at what other jurisdictions have done, and kind of amending those laws to reflect local situations.
I don't think it's a situation where there needs to be a reinvention of the wheel. I used to be a lawmaker and I want to say this in a polite way. There's a bit of, I don't want to say tech is not right phrase. Not something that,
>> TAYYABA IFTIKHAR: You can be candid.
>> VANCE LOCKTON: Just, seems like a very difficult topic to handle and just avoided.
Kind of encourages, not that difficult, frameworks in existence that can be amended to fit requirements in each country. So one, that exclusion. You think there is the theoretical misnomer around what is seen as democratization of AI and I think that is the wrong phrase to use. There hasn't been a democratization.
While there may have been somewhat of a democratization in terms of access, access to tools, gen AI tools, particularly chat bot and all of those, there hasn't been proper democratization.
Going to talk democratization and AI governance, we need to talk about it through the life cycle. There needs to be democratization. I wrote down there not only democratization of AI use, democratization of AI development so that in the creation of AI tools, there's already diverse voices included in those design choices. Large language models that there is someone at the table that says, you need to look at African languages, different countries.
Democratization of AI process can't be a situation where countries are merely seen as sources of income, and there is no way to kind of shape profit share. Profits need to be democratization of AI profits and democratization of AI governance itself.
Maybe this is Saba's way to kind of summarize it. Needs to be deliberate efforts by the Global South, by African countries, by other countries, to insert themselves forcefully into the discussion and that requires them beginning those processes where it hasn't begun. And indeed for there to be a deliberate inviting of those voices to say come take part in the discussions and discussion is not only at the stage where technology is deployed from through the entire life cycle.
>> TAYYABA IFTIKHAR: Very insightful. Running a bit short on time. Probably going to have to leave it towards the end.
I really like the way that you said that the inclusion of gender inclusion or diversity perspective is not very difficult, but seems very difficult to do. So in the real world, in making sure that regulations or framework, that actually include a part of that as well. Thank you so much.
Jasmine, move on to you to wrap this up. We talked a lot about the challenges, what is not working, but let's imagine what could.
If you had a plain slate to design AI regulatory framework, one that is forward‑looking, ethically‑grounded, and innovation‑friendly, I mean, huge to ask, what are the three most essential features you would include?
>> JASMINE: Good morning everyone. Jasmine, AI governance consultant at Deloitte and founder of Europe's first youth‑led, not‑for‑profit focus on responsible technology basically trying to bring young voices to responsible tech field and have them basically share ideals, fear, and ideas how to make this world a better place. Let's just say it like that. Really happy, brought up the point of international law because, yes, ideal world, we would all get along.
And ideal world, we have some kind of definition on AI governance specifically on international law, but there are two aspects that I really, really, I wouldn't say problematic, but take this utopia. Hard to achieve. I wouldn't say not a possibility to achieve it, but it's hard to achieve it.
That is the first part is definitions. We need to get to a point where everyone defines the same aspect same way. So just definition of AI systems is a huge, huge issue. We saw that with European laws already with the UAI Act.
Then the second part, which is also issue is our countries actually up holding international law already. Past years, most, a lot of countries, we see huge increase in countries not upholding international law, so the first part of the question, and push former accountability from countries.
This is one aspect.
I wanted to bring up one point because I love the fact that also Miss Saba brought up the aspect of inclusion. We need to set a base infrastructure, but we don't have infrastructure. Different countries who are lacking access to AI, we're not able to democratize the access to AI. This would also be a base for me. Let's come to the actual question.
Ideal framework. As said, in the ideal world, we wouldn't have approach that is so reactive, as Mortiz called it earlier, we would have one that is adaptive. In this case, what we have right now is risk‑based approach. So we basically look at AI systems and we categorize them in different risk or straight up just prohibit them. While I do see why we're doing that, the ideal form would actually be use case framework. So we actually look at AI systems and look at them how they're used, in what sectors they're used.
The idea behind it is that AI systems, same AI system can be used in different use case and different ways, which means can have different harms to different stakeholders. Idea here is to make sure that we can actually use these AI systems, but we make sure we really do uphold all the different scenarios that could happen, and use‑case approach would actually make this easier for us.
It would also make it easier to keep in check impact assessments that you have to do as someone actually implementing those laws.
Brings me actually to the second part, need frameworks implementable and understandable. What do I mean? At the end of the day, those regulations and laws are being implemented by the people who are developing AI systems because those are the ones who are actually building it and those are the ones who is to uphold it.
If the developers cannot implement the regulations because they simply do not understand them, we need translators, people like me or Alexandra, to go down and try to explain. I'll be a bridge between tech and law. In the ideal world, we have developers who already understand this, which would have developers who would be able to implement each aspect, each principle, in a way that is clearly not only defined, but understandable, second part.
Third part, and I know that some of you will laugh already because you have heard this so many times over the past days. We need to include all stakeholders, multistakeholder approaches. Civil society, private sector, and public sector need to come together.
Now, here's the thing where I disagree with most multistakeholder approaches. When talk a lot about including all stockholders, forget to include the youth. Responsible technology hub see not only potential of youth, see most understanding their technology better and know how to implement it better. We need to include them not to only future‑proof legislation, willing to make sure they're included by means of, okay, these are their fears, to the only ideas, but this could be solutions. And for my work, I can tell you that youth young people and young professors have a lot of ideas for solutions that we're facing. They're just not heard.
So we need to give them platforms. We need older generation leads by example, gives platform. We need young generation that refreshes discourse every time, and we need spaces that are spaces of real cocreation. So these kind of discussions that we're having right now, they are a great base, but we need spaces where we actually create where we have enough space to talk, to discuss, at the same time, to bring different disciplines and different sectors together.
So specifically, I see this work actually very well. So having space where academia, councilmembers, public sector comes, private sector coming and we need intergenerational solution for issues and intergenerational building solutions together.
With that in mind, those would be three aspects of I would say I'd ideal AI governance framework specifically.
>> TAYYABA IFTIKHAR: Right on time. Thank you so much to all of our speakers. So many valuable takeaways. Now we open it up to the floor. The mics are on either side of the room. Please introduce yourself. If you're joining virtually, feel free to post in the chat or raise your hand. Do we have any questions?
>> MOHAMED ADED ALI: We have questions. I have a question in the direct message and chat box. Questions from onsite participants before we move on to online participant?
>> TAYYABA IFTIKHAR: We're warming up here. Start with the question.
>> MOHAMED ADED ALI: Question I received might be more the answer. The question is that, just like the concept of international fragmentation, do you see that we are heading towards either AI fragmentation, consensus basic language. If that is the case, how do you suggest to move forward with it?
>> MORITZ VON KNEBEL: Yes. I do think that we do see fragmentation, but I also think that may be often gets portrayed as fragmentation along country lines or jurisdiction like EU, US, China. Often split between different actions and their interests and what they see as the governance systems. Actions have input. Fragmentation happening at multiple levels. Fragmentation goes beyond different countries.
Concerned about fragmentation. Wrong incentives to race to the bottom. Doesn't build great base for trust. And between different partners, again, different countries, but also different sectors, not‑for‑profit sector, industry, academia, government. So yes, I see this as concern.
What can be done, I think, goes back identifying areas where people already agree on, and then building up from there. Never two perfect agreements and total unison on these things. Sometimes there's more room and more overlap than people are willing to give credit for.
In the foreign policy or diplomatic domain, track 1.5, track 2 dialogues pretty successful. I think identifying these areas of consensus and, yeah, at the end of the day, it's also events and fora like IGF, people get together and, hopefully, get to, at some point, establish a shared language or at least hear what other people, sometimes people are also too ambitious here. They want everybody to speak the same language. And cultural anthropologists and other people will tell us that is not actually what we should be aiming for.
It is okay for people to speak different languages, but I think if you dial back your ambition and they know we don't have to have complete agreement, the first step is hearing how the other side sees things, then I think having more of these conferences. And the other people have said diverse representation of voices at these conferences and events can be very useful. And yeah, shining path forward, shared many languages. Iterative painful process. Not going to come overnight. It doesn't mean we shouldn't invest energy in it.
>> MOHAMED ADED ALI: Another question here. It says that, so yeah, can any of the speakers point to words, any exemplary AI policy that balances innovation and ethics? Broad‑ended question. If anyone would like to take that up.
>> TAYYABA IFTIKHAR: Anyone from onsite like to speak? I would like to take this question.
>> JASMINE: let me take this off first.
So point to any regulation out there that brings in good government and doesn't hinder innovation. Funny part, officially not a lot of governance out there yet, so officially, laws that are implemented, there's a lot of discussion out.
US working on specific governance structures within their state, and then trying to do federally as well.
We have Canada as well. We have EU. Brought up UAI Act which is also being discussed again, by the way for those that haven't kept up with news lately. So even there, we have still discussions on how to implement the specific laws and there is still a lot of room.
So for example, with the Middle East, we barely have any official AI governance there. We see a trend of discussions. We saw this at the last IGF where a lot of Middle Eastern, North African states together started having discussion. Relied more on principles rather than actual frameworks that could be implemented. Still, for whoever asked this question, there is still a lot of room to actually cocreate and to bring regulation into the market.
>> TAYYABA IFTIKHAR: Great. I believe you got a question from the chat as well. Do you want to go?
>> HARISA SHAHID: Yeah. We have another question. So there has been recent trend from tech companies, work they call innovation against development. Going forward, are we going to see similar question as we have seen in social media and access versus development regulation.
Onsite speakers have a comment online. Moritz or Vance, do you want to answer this question? Can you please repeat the question again? We didn't understand it. Connection got a bit fuzzy.
>> HARISA SHAHID: Question is, harmfully, are we going to see similar AI states we have seen in social media and business development regulations.
>> TAYYABA IFTIKHAR: What I understand, in the past, we're seeing some friction between platform regulations, platform governance as well. Are we going to be seeing similar sort of friction in AI framework, AI regulation as well as we move forward in the future? Do you think so? You don't think so? One word answer would be great as well.
>> Hear that one. I hope not. That is why we're here having this multistakeholder discussion. We can achieve some kind of consensus.
Also complementing the last question about different kinds of legislation and which one would provide safeguards and would not hinder innovation. I believe that the UK has been taking a good approach by not regulating with a specific bill of law. There is no bill of law going on right now. They are letting the sectoral authorities handle the issues.
And also, they did not define the concepts so it won't be a closed concept. So it can let the technology evolve and we can evolve concepts as well. So I hope that, I believe that principle‑based approach and not a strict regulation would be the best approach in that would prevent friction we're talking about.
>> TAYYABA IFTIKHAR: Great. Perfectly concise answer. Good thing because we are running a bit short on time. So we're going to move towards final stretch. I would like to hear one last thought from each speaker. Please restrict your answer to one sentence or two sentences max. We're going to start with you. Jasmine, start with you. Most urgent action we must take to align AI governance with ethical foresight.
>> JASMINE: To give a quick answer to the last question about the friction between tech companies and regulators, yes, we see the friction. Yes, there will be more friction. I would be surprised if we didn't have specifically democratic state have friction. We will see it and hopefully find a common ground to discuss these regulations. Critical.
What we need specifically as a society, regardless of government regulation or tech regulation, whatnot, we need to make sure we're critically assessing what we're consuming, and we need to make sure that we critically assess what we say, what we perceive, and what we create, because what we are right now is very worrisome and means of how we're using specific AI systems without questioning their outputs, where publicizing without question context are right or no. One of the most important things as citizens is to make sure we're bringing critical thinking back again.
>> TAYYABA IFTIKHAR: Would you want to go next?
>> I'm going to stick to one sentence. Gone into ZOLEO binding international law, platform AI governance.
>> TAYYABA IFTIKHAR: Perfect. Alexandra, would you want to go next?
>> ALEXANDRA KRASTINS LOPES: I would like to leave you with a key action point, that we must move from adaptation to institutional implementation. I think adequate first foresight cannot remain theoretical aspiration, foresight, or a paragraph regulation or corporate statement. We need to build core structures of governance within companies and organizations in general.
>> TAYYABA IFTIKHAR: Ethical foresight should not be corporate statement. Thank you so much.
We're going to go online to our online speakers. Vance, if you want to go ahead with the two or three sentences to this question, what is the most urgent action we must take today to align AI governance with ethical foresight?
>> VANCE LOCKTON: I would say it's to shift the narrative around AI, away from AI being either inevitability or whole necessary piece of future economies to think about what outcomes we want from future society and how AI can be built into those, factor into those.
>> TAYYABA IFTIKHAR: Perfect. If you want to go next.
>> MORITZ von KNEBEL: Add to that. Generally speaking, adding nuance to the dialogue, overcoming simple dichotomies, innovation versus regulation. You can have innovation through regulation. Had this for decades. Overcoming US versus China, human rights‑based versus risk‑based approach. Yeah, breaking away with these dichotomies is not helpful and ignore nuance embedded in these debates.
>> TAYYABA IFTIKHAR: You can elaborate more. Such an interesting point to make, adds so much value to the discussion. Might give you one more minute.
>> MORITZ von KNEBEL: Maybe I'll touch on the question raised in the chat. Balances ethics and innovation, or regulation and innovation. Balancing ethics, again, something submitted to as you can choose. You can either regulate or innovate. Use that crossroads, but we can't fall behind, yeah. We've got to innovate, innovate, innovate, whereas the reality on the ground is that safe and trustworthy frameworks that give companies also predictability about the future and safety and know that customers will like to ensure their policy is safe, integral to innovation, seen this in the past of the nuclear education. Aviation industry took off after we had safety standards in place. Made it possible to scale operation. Very fascinating example for those interested.
Done work on this, writing up case studies, different safety standards industries and how they contribute to the development of technology. Yeah, going against the, we have to choose. The U.K. is an example of very pro‑innovative regulatory approach. Didn't say we're not going to regulate thinking about how regulation can serve innovation, and I think there are many ways that we can do that. Often, unfortunately, gets annoyed easier to craft NRI narrative. Two things, and often two people and two camps against each other.
>> TAYYABA IFTIKHAR: Thank you so much. What I take away from this building safe and trustworthy frameworks is definitely key.
Thank you again to all of our speakers for the depth and thoughtfulness you have brought to the conversation. I have learned a lot and I'm sure my colleagues, my online moderators have also, and audience also have learned a lot. I learned many new concepts.
Thank you to these brilliant speakers. Also want to thank our audience here and online for their presence and conversation as well your presence on the final day of IGF 2025 is very important to us. Thank you to the wonderful IGF media team for coordinating the technical aspects.
Before we close, I would love to invite everyone on for a picture. First we're going to have a picture with speakers, and then I'm going to invite audience if they can come on the stage and have a picture with the speakers and myself. Thank you very much.
