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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>> SJUR NORSTEBO MOSHAGEN: Hello. Welcome everyone both here and online. Start by getting some very nice words from the member of Governing Council of Sami Parliament please.
>> OLE‑HENRIK BJORKMO LIFJELL: (Non‑English language)
Dear participants, I have the honor of opening welcome to people present here and online participant to this panel discussion, the panel discussion that highlights the importance of the subject of indigenous languages technology and AI. Start with let me express thanks to Unesco and IDIL for putting this subject on the agenda and promote disability of the international decade of the indigenous languages.
Digital and minority communities face barriers as limited digital infrastructure and digital tools supporting use of our languages. Large tech companies may not see indigenous languages as profitable markets and most online content dominated handful of global languages.
Many indigenous communities have oral traditions as cultural preservations and lack of written language is making digital session complex and sometimes inappropriate without community consent. Overcome these barriers, we need to follow up with following access. We need to reduce language loss and revitalize digital languages and technological development for indigenous languages, need to ensure importance of digital inclusion of indigenous languages also in digital platforms and AI.
Promote policy something we need to do, policy that used human rights principles and take accountability by use of national laws which will regulate and secure that indigenous communities have control and management of linguistic data collection that benefit our own communities.
AI generated data innovations need to be used in nondiscriminatory way and restrict digital turtles as well. Initiate further collaboration and foster dialogues with big tech companies' developers to include digital tools and language to indigenous communities speaking indigenous language Remind each other no language is too small to matter, elevating challenges faced by indigenous and minority language communities, the currents are helping to pave the path for more equitable digital future for everyone.
This panel debate is now open and I will encourage participants to establish connection to further exchange on the ongoing subjects raised under this Internet Governance Forum in the framework of the decade. So thank you.
(non‑English language) Thank you so much.
(applause)
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. My name is Sjur Norstebo Moshagen. I'm going to head this panel debate.
In my daily life, I'm heading this Sami language work at University of NTNU. I'm going to discuss barriers to indigenous language technology and AI uptake.
To help me with this, I have online David Gaspar, comoderator for the online participants. He's international consultant specializing in promotion of multilingualism, serves member of the secretary for the internet decade of indigenous languages at Unesco. He supports initiatives related to Unesco recommendation cyberspace, strong fostering digital linguistic digital space.
Would you like to say a few words? Present yourself.
>> DAVID GASPAR: Thank you. Good afternoon. Am I audible? This is David. I don't know if you can hear me. Thank you very much.
Hello. Good afternoon. Greetings from Paris. Thank you for the presentation. I am here from the Secretariat of International Indigenous Languages, online moderator today. Feel free to share your questions in the chat for those joining remotely and I'll pass them to our panelists during the question and answer session. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much, David. So yes, panelists today on site, Professor Health Technology Department of Computer Science at University on Trauma as well as adjunct professor Sami College, Lars Ailo Bongo, heading this Sami AI lab there.
Online, we have Dr. Outi Kaarina Laiti, National Audible Institute in Finland, computer game researcher, designer, and education specialist, blending Sami culture with tech and education.
Then again on site, we have Vaits Ernsteits, Livonian activist developing digital tools for endangered languages, work hard to shape the global digital inclusion policies.
Then the last one on site is Aili Keskitalo, former parliamentarian, digital rights advocate focusing on climate and just transition. Sami working for Amnesty International in Norway.
Finally, online, we have Kevin Chan working at Meta Global Digital Policy, empower indigenous language online.
That is our panelists for today. Before they are giving words, I'll say a few words on the topic of today.
So starting point for this could be global roadmap for multilingualism digital area that Unesco is working on. They have a draft from introduction, only draft, but I think it's quite well formulated, goes to the heart of the topic of today.
Global roadmap for indigenous languages in the digital era provides strategic framework for advancing language policies, diversity, and ensuring all language users, all language communities can thrive in the digital age recognizing that language rights are integral human rights. Role aims to empower every individual to use and preserve their language in digital spaces.
Question today is how is that, what is the actual status? What are the problems? What are the obstacles to actually do what they're trying to do on that part, and so I would say very few words on this. I've been working on language technology for their Sami languages last 20 years. Seen that conditions for third‑party languages, language technology is very different from the first party languages. So Apple and Microsoft treated very differently from tools by everyone else.
There are serious problems and for these tools, often they are completely blocked. So independent localization, for example, is also not possible or it might not be accessible if it's possible or might not be distributable. No platforms for providing translations piece of software without asking and getting permission from the original developer.
And AI for indigenous languages, minority languages, quite open question. Open for many languages at the moment are, what you have seen so far, bad output is dominating for these languages partly due to lack of data, but also partly because of lack of community involvement and lack of quality assurance and testing and evaluation.
Major question in this discussion is how one adds one's language to models from big technology? How can Sami or any indigenous language be added to models from open A.I., from Apple, whoever?
So we can, as I said, been doing this for 20 years, we know that we have technology. We know we can make it work on the technological of it. We cannot always deliver the tools in the app and systems and context where user wanted to use them. That's the major problem.
There is some examples here that we have experienced. Not going to spend much more time on that. Just one short one.
Spellers approving tools online, office applications, we have no possibility to install these tools using so they behave as people expect them to.
So in conclusion is that language technology for digital languages often not even own technology and know technology. Not the issue. Platform owners make life hard for most of the world languages, but probably mostly without realizing it. I don't think it's bad or bad attempt behind it. Just ignorance or negligence. We need a new approach how human languages are included and approached in digital world, what we are going to discuss today.
>> LARS AILO BONGO: Thank you for inviting me to give this talk. So I'm going to talk about my future issues that may sort of hinder the use of indigenous language and indigenous AI, great potential to create maybe most important equity gap indigenous people are supposed to have with the lack of experts in fields like medicine or occasion that has language cultural knowledge needed to sort of understand and provide equitable service psychology. Very few tests form digital minority language. Tests don't work well with indigenous people. AI has to provide something where there is nothing there before.
Also, like in education, AI has a great potential to provide adaptive learning, which is very important for minority language speakers because the level of language has a great variation than majority languages. So a great potential for AI to sort of bridge these equity gaps.
Then again, if indigenous people are excluded from using AI, we are risk that this equity gap will just widen when the majority people start using AI for their health service and education service. Very important indigenous people are included in this new AI services.
Luckily, this is regulated by law. Pulled from the AI Act says that's not alluded to discriminate minority such as indigenous people. If there is education service or health service provided, it should work as well for like minority people as well as for the other people.
However, there is one big challenge, which is that indigenous people and other minorities are considered special category. This requires extra strong data protection and this is, for instance, regulated by the GDPR, it's not allowed even to collect this data unless you have a really good purpose.
Also, EU says it is allowed to actually collect ethical data if the purpose is to prove that this AI works as well for indigenous people as for other minorities. What illustrate indigenous people and AI provides dilemma are facing.
Let's say that we want to do adaptive learning, which is maybe the application that is highest on the priority list of many indigenous people. In order to do that, AI can help. You need to build this AI and adaptive learning. Important component of that is community tests and this IQ test. You want to do IQ test and works well for minority early language and cultures you need to build that using the minority language and culture in minorities.
That means you need collect data from this and say these are indigenous children and you need to collect basically indigenous IQ, need to test from indigenous people. This is, of course, very controversial because being indigenous person, I know myself historically supposed to resist research attempted to show that people are less intelligent, but I guess that is if we want this to exploit all opportunities that AI gives, including in the educational field, we must basically now start checking with this type of data.
We do this more ethical way that was done in the dark ages, build regulatory sandboxes, ensure data collection is done ethical and safe matter.
I think it is really important we need to start working on this in order to not leave digital and other minority people and languages behind when the new AI tools are going to be used in like foreign services health and education. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much, Lars. Next one out is Dr. Outi Kaarina Laiti. Please go ahead.
>> DR. OUTI KAARINA LAITI: Thank you. My slides are somewhere. We need to share the Zoom. Should be shared. I can see only myself on the screen, shared in the screen here. It's both you and the slide.
Okay. I can see, thank you.
I'm going to dive in and thank you for having me as indigenous woman. I come from the margins and it's always my pleasure to be talking about computing.
Programming has not been my passion. Games are, but since I was like 3 or 4, something like that, I wrote my first line of coding, wanted to play games, like Commodore 64 was a beauty in the 1980s. When Finland introduced 10 years ago a program as part of basic education, it was the starting point of doing programming research.
We have Sami people living in North Greenland and no one knew how to actually do this. Questions like how to teach programming in Sami languages, what are the cultural aspects of computing, they still exist after 10 years of educating, educating children in basic education. And this change was huge, like all teachers in all levels should teach programming from Africa to begin. Teachers should all do it starting from grade one. It guess it has been 10 years so we have like one generation of Sami basic education programmers ready, or maybe they're not, but anyway, can I get the next slide?
Then the games. Nearly all games I know that go under digital game umbrella, they are all for education and in that languaging education, especially. We call this serious games. And then we have a lot of developing content in games. These can like go under the same umbrella or Sami games developing content in platforms like Second Life, Minecraft, which I called it indigenous Metaverse. It's growing rapidly and most of these platforms are privately owned. We have semiprivate platforms in universities, York University has own indigenous Metaverse in development. Helsinki University certainly is not indigenous, but it has some indigenous content.
I have done extended reality projects since 2018. So Sami game, yeah, the major issue is you cannot use utilities to extend reality to language education. We don't have the tools to have discussions in virtual reality if we don't use like voiceover IP or something like that.
It's easier to use nonhuman‑centered design in games for multiple reasons, but ethical questions are one representing, before I'm doing nonplayable/playable Sami characters, what should I represent and what are they talking about if they are talking and how they are talking. It's not ethical questions. Next slide please.
There has to be some progress because Finland introduced this programming in basic education. For example, National Divisional Institute published this guide for media education and programming in three Sami languages.
Speaking in Finland, picture is actually from school Sami Programming Guide, which is the colisting I have seen for a while. We have huge media archives that has been used to train like automatic speech recognition tools. Problem, we are missing text equivalent that we could use. We have an archives group combining both like the textual version of speech and actual speech. Development is quite slow. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. The next speaker is?
>> VALTS ERNSTRETIS: Thank you for inviting me to the panel. Crucial for the IGF as well kind of works.
Just a couple of words about my background. So I represent originally indigenous Livonian population. 35 years since official recognition of Livonia. And I've been active for promoting Lovish issues past 30 years.
Last six years, I'm being six years working University Lovia. Established one of the key action areas that we work with is building digital resources and looking to approach for extremely under‑resourced, scattered data conditions because the community very small, less than 20 speakers. In general, we have to find a way.
This is logical that we have been also recently quite active in maybe more global initiatives and wanted to present those instruments that currently exist supporting developments in digital areas for indigenous languages so which are, as you all know, international indigenous languages. And just last year, there was ad hoc group, especially designated ad hoc group established additional quality and domain. Also participants.
There has been, this year, one very interesting initiative that went out, which is global survey indigenous languages, which is closing next month, provides both data or perception of what is the actual state of indigenous languages globally in the digital area. Also motivates those participants to think about technologies and issues that they have on the past to digital equality.
Then February, Paris conference took place, Language Technology For All 2025, and from that conference grew out maybe freshest Unesco initiative which is global roadmap for the multilingualism digital area, and this is the document that might define the future for languages and especially digital languages because it envisions future where equal opportunities entering digital domains so ensured for all languages.
Currently, technology captures mostly top 200 languages of the world, but the majority of languages were second row or in last row, as maybe some. So majority of those languages are in indigenous languages. This is precise. This is mechanism that in most work addresses the indigenous issues.
Very shortly, summarizing up roadmaps, current roadmap, roadmap consultation process. Easily look up Unesco web page and take part in it.
Three key moments in the road map. There are in‑program input/output issues. Everything. Input addresses ability to produce and contain digital data, kind of preconditioner for any language to enter. So before we start technology, we have to start with being capable of producing anything in digital format whether it's sound data or spoken early languages written data. Technologies about that. Lots of constriction. Countries don't allow digital usage certain languages this and or languages that, simply doesn't have any writing system so access to technology is this one part.
The second part is output Sjur was talking about. Imagine if have ability to produce digital data, we don't have technologies like Sami languages or Livonian, not able to use them, not able to get them in and not only on daily products, but also on cloud computing on such products like game and educational instruments. This is another aspect that we need to tackle about basically when wanted to achieve end goal is technology is multilingual by design, so whatever language there is, any technology is adaptable for it to be used by user of that language.
Regarding process, there are kind of middle of that roadmap sits an idea that communities, language speakers, have to be involved in one or another way in all the stages of technology development. This is not the only issue about how you handle data. This is also about how technology is developed. This is a question of whether technology is published if it doesn't mean, for example, standard of the community and many more. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. Then Aili.
>> AILI KESKITALO: Thank you for the floor. I'm here today as Sami language user, Jack's mother raising a young women in a language that has often been pushed aside in public systems or education and increasingly in technology, but I'm also here as an advocate for indigenous people's rights and human rights, believing that technology should serve rights and not markets.
For us, it's not just about innovation. It's about justice. It's about right to exist fully in our own language, not only traditional settings, also in emails and voices, assistance learning apps and eventually in AI systems. Ability to use your own language including digital space is essential for dignity, cultural continuity and meaningful participation in society.
Today, over 98% of the world's languages lack basic digital tools. This is not a gap. It's a threat. It means that unless we act, our languages are risking going digitally extinct. We see the potential. We have heard about it today. Sami institutions like the Sami Parliament's joint project, tech taking steps to develop language technology on our own terms with open source tools, ethical frameworks, and strong demands from state responsibility. Still, we face barriers and we have thought about them already today in a closed call from big tech. Lack of funding, not enough access to data to try the systems that we need.
At the same time, as was explained, we must be careful. AI is not neutral. It can replicate colonial logics if we are not involved from the beginning. As rights holders, not just users, language is power, and in this digital age, the right to speak your language must include the right to shape the tools that carry it forward.
That is my message. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. Last speaker before approaching the questions. That is Kevin Chun from Meta. Please go ahead.
>> KEVIN CHAN: Thank you very much. Good to see you again. Maybe we just move to the first next slide if you will.
I wanted to start by just sharing that obviously been referred to by few other people on the panel, obviously important decade to be thinking about these very important issues. We are in the decade for indigenous languages and at Meta, have been putting together some initiatives working closely with indigenous peoples and with Unesco and other language partners to think through how we can help support with, in particular, some of our open source technologies with AI. Prefer panelists talked a bit about open source versus closed source technologies it.
Open source technologies effectively are ones where technical technologies, we have built some kind of AI model, but then make it freely available to anybody else who wants to use it and what that allows you to do, so you end up taking the model, you can refine it, finetune it, you can add additional functionality and features to it, and then you own what it is afterwards.
So we do believe, and I think as was previously mentioned, we do believe that open source AI technology can be a very valuable technology. So in this context, I want to just leave to start the conversation. One, is initiative that we help drive in Canada, Incorporated, which is an entity up in Nunavut, Canada's arctic, tech tourism to translate the platform into Nunavut last year and online language translator for 200 languages with the help of Unesco and Hugging Face, which is powered by Meta's open source ITU model called No Language Left Behind. Also a new language and technology partnership that we recently announced as well. Move to the next slide, please.
I just wanted to again call out kind of one of the initial projects we did which was I guess maybe two years ago, we launched again with NTI's help and really was a long period of collaboration to go because we wanted to do this properly. We wanted to, in any way, we were welcomed by the community to do so and the community had expertise and we obviously didn't.
We want to make sure that we did this properly and it did take about five years, but we're very, very pleased to be able to bring at least the desktop version of Facebook, I think, in the kind of minimal way because you wouldn't say everything was translated, key parts to the platform transformed in Nunavut.
Pleased that the Governor General of Canada, who is Mary Simon herself, is an indigenous Nunavut. Shared the good news on Facebook when we launched that day and very pleased that our friends at Unesco were very supportive of us championing and helping to drive this kind of initiative during the international decade.
Next slide if I may is just a video. I think we can play it if you hover around the video, move the cursor. There we go. It's just nonaudio video shows what you the next initiative is. No Language Left Behind Online translator, 200 languages in terms of translation, it's text to text and it's to include many, of course, not nowhere near comprehensive list of the thousands of indigenous languages that exist, but it does among the 200, many of these languages are indigenous languages.
And you can see video, you can select your origin language, you select kind of language you intend to translate to, and can see, put the text in and there's another window below that gives you the translated output.
This again is something that is open source and so folks are able to, for example, access model on places like GitHub and iterate on it, and so there is potential and opportunity to expand the language set to include other indigenous languages, and you can do this freely. The technology is offered out to the world and to the community freely to do that.
Then maybe the last slide if I can, this is the language technology partnership, which is something we announced actually in Paris earlier this spring, in February. And the project, we're once again working with partners around the world on and that is to try to really push the frontiers of language technology in particular, trying to help support low‑resource languages. And so what we have been seeking collaboration on, only do this with the agreement of partners, is to have, available different portions of data for languages to help train a model that we hope will be able to be quite powerful in terms of translating and in terms of transcribing different languages that will unfortunately may be not as supported as we would like. We would like many, looking for partners that can provide 10‑hour speech recordings with transcription or some amount of written text.
Here, we've seen 200 plus sentences. What we hoped to do is in the coming months, with these partnerships, is to again build new open source speech technologies and our commitment would be, that's if we are successful in making some of these breakthroughs in terms of translation and transcription, we would want to then make these technologies freely open to the globalized community for them to build applications and further research. And if there is something in this, please do feel to reach out to me and I will try to do my best to connect you to the right teams to look at this. You can search more online. There is a portal where you can learn more and submit information there. Thank you very much. I'll pause here.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much Kevin. All panelists introduced their slides and we can go on to the questions.
With over 7,000 languages in the world, it's clear that no platform can realistically support them all themselves. Owners constrained security concern and limited resources, end of centralizing control over language ability leaving many communities without access to own languages in the digital space. How can you shift that mindset and what would it take for them to open the platform to communities in their own languages in their digital space.
For the question, was thinking that maybe Lars could go the first on this one.
>> LARS AILO BONGO: Maybe I'm approaching this issue a bit differently from the other panelists. It's not building, or I'm not interested building the models, thereby not having that need to have a platform to run this. More AI applications use the technology that is provided, hopefully, by this kind platform.
My concern is more on the practical issues of being allowed to do this. We need to address also the challenge of not just building models, but also applications, especially the high risk that are useful will be used in education, health service, and other important public services.
>> SJUR NORSTEBO MOSHAGEN: Thank you. What is your take on this question?
>> DR. OUTI KAARINA LAITI: I have a short answer to this question. I'm speaking from the perspective, for example, basic education where we see language as a human right, of course. So we should shift progress from a feature or localization or liability towards that language as a human right and it is that on platforms as well. So that strengthens the platforms when this is a philosophical question.
So this is a philosophical answer. Need to kind of start seeing probabilities in this and instead, not talk about it localization any more.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much.
Kevin, what do you think about what OUTI just said?
>> KEVIN CHAN: just had to unmute it? Sounds okay. Yes. You can hear me?
>> SJUR NORSTEBO MOSHAGEN: We hear you.
>> KEVIN CHAN: I agree very much with what was expressed by first panelist, intervention. It may not be necessarily about the models themselves, but more about the application layers.
I agree, going back to what I had mentioned about open source, open source models. Meta makes some. Other companies make them as well. This is, I think, going to be very important sector by which indigenous communities, people who are available, very committed to supporting, protecting, and promoting, low resource languages, this is very important way I think by way you can actually see applications built on top precisely because models are free for people to use, and so with the right amount of training and work to build applications on top of these models, you very much, I think, can get models that are conversant in different languages.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much.
I think to go on to the next question. AI technology still relies heavily on large volume of text data, even those requirements gradually decrease technology, develops how can you ensure that AI is developed for indigenous and minority language communities in a way that keeps data in the shape and controlling this data in the hands of those communities? How can we ensure that AI‑generated concept is such quality that supports rather than harms language and its speakers?
What do you think?
>> ERNST NOORMAN: Approached previous EU mind shift because, well, there is this thing, so in order to use language with technology, need large amounts of data and that data ends for small communities. Always hypersensitive. Don't even need sensitive data to actually collide with GDPR. Already there. What is actually needed is this community, what I mentioned previously, community involvement and all stages of technology because we need community contribution in order to get technology running at the same time. We need to make sure that technology that is produced not harmful. It is ready, it corresponds for what the community needs.
And so there is no other way around. This is not done by legislation. That much, this is really mind shift because we run, for example, with developers, even with, academia should be kind of very well aware of issues we run in those situations. We have to explain them that, well, why this is not working, but why this is not okay. And we do need mind shift in listening to indigenous people in whole stages of the process.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much.
>> AILI KESKITALO: Yes. I would stop you, agreeing on the demand of shifting of the mindset and I think shift will need to be from thinking about getting permission to entering into true partnerships, individuals, people with language communities, language where users are not just passive users cocreators. That would maybe build in the trust that is needed for their data collection because it is being about data sovereignty as well and principles when it comes to principles often used in other compacts.
When it comes to indigenous people's rights, it's the principle of free prior uninformed concept, and that should be used also when it comes to data collection and the application of that data.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. Time is running way too fast for us. I think we should see how is it.
David, any questions from the online audience?
>> DAVID CASTILLO: No. No online questions. Think you.
>> SJUR NORSTEBO MOSHAGEN: Any questions from the audience in the room? Yes, we have, one. Please.
>> HARRY WONG: Distinguished speakers, so excited because you know this panel respects indigenous languages, culture, so much. Also, we have Meta and to work with UNESCO and to protect languages and cultures. So I think there is a strong conflict between data ownership and the way to collect the data.
So if we want to help, a large internet models work well for the digital language, we have to throw out the data and then finetuning the larger model so the contributor becomes yourself, unfortunately, so that is because the traditional architecture of the internet so mega.
Meta have to be centralized platform to resolve this. New paradigm shift in any protocol was invented fully. This year will be triggered with data ownership, apply for GDP and data be collected in a way that is anti‑digital colonization.
I'm Harry Wong from Singapore IGF, founding member of the Singapore Internet Government Forum and cofounder for Lingo AI. Founding father of the Worldwide Web called Tim Berners‑Lee invented ChatGPT and our internet became centralized. Then he felt sorry about this, then he invested in a protocol to correct the internet. The new protocol called Solid, and Lingo AI works with Solid and Meta Life.
And we can collect the data with data ownership owned by all contributors and users of the data sets can be used by authorization, permission, large language models, companies worldwide or locally.
Local data is important because model can work with local data sets, become everybody's AI agent. It's your personal agent. While working solution also already available, for example, Sami contributors all contribute data, but they control two parts that they own by themselves. They can authorize to Meta or authorize to open A.I., authorize to no agent large language model companies, but they keep ownership and fully apply for GDPR. So happy to join this kind of panel.
So my question will be if we have such solutions, if internet had a have solutions to prodigals resulting in tools and to try and to work this way and to help to protect indigenous languages and cultures based on languages. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. Just a few seconds. The ADG from UNESCO would like to have some closing remarks. We might have time for one short question after that. Take closing remarks now. Please go ahead.
>> TAWFIK JELASSI: Good afternoon all of you excellencies, distinguished panelists, esteemed participants. As we come to the close of this important session, I would like first to express sincere gratitude to all speakers and panelists for substantial and insightful inputs which we have this afternoon, and extend special thanks to Mrs. Tennyson, Regional Development of Norway. Already showed us commitment, engagement, and support, especially in the context of the international decade of indigenous languages. The commitment and leadership of Norway has been instrumental in advancing our shared goal to safeguard and revitalize indigenous languages in the digital age.
Also, I would like to express deep gratitude to the members of the International Decade of Indigenous Languages, members of ad hoc group for their invaluable contributions, especially to the global survey, which took place in indigenous languages.
Also excited to see the survey findings and to explore how we can further collaborate with indigenous communities placed worldwide to advance this vital work.
Title this afternoon's session is not just tech. Reminds us of fundamental truth, technology alone cannot solve challenges that we face. And yes, indigenous language and technologies exist and AI holds transformative potential; however, if the systems in which these tools are, if the systems are not inclusive, do not respect cultural and linguistic rights, then the technology by itself is just another barrier. Instead, fully playing it small as a bridge between communities and cultures.
I think we heard this clearly today. Barriers to update for indigenous language and technologies are not technical. They are structural, they are political, and they are ethical.
From the spread of proprietary platforms to expressive data collection regimes, particular exclusion of indigenous people from digital policymaking, these are the conditions that determine whether indigenous languages can truly thrive in cyberspace.
At Unesco, we stand with indigenous people to affirm the right to fully participate, to also have equal footing in indigenous space in their own languages. Indigenous communities must not only benefit from these technologies, they must be central to design its development and its governance.
Their knowledge systems, their world view, and languages, discourage not just valuable, essential to shape and ethical and inclusive digital future. Vision behind international decade of indigenous language is not just preservation, but through empowerment, we are proud to support projects like the Mayan language preservation and digital language project in partnership with MasterWord. This project has created new talking glossaries, localized websites, and universal keyboard, empowers millions of speakers of this language across the Americas.
Still, many challenges remain. AI systems continue to reflect linguistic hierarchy. Data remains scarce or inaccessible. Indigenous women and girls face barriers accessing and shaping this technology. We must address these gaps by investing in open‑community‑driven innovation and promoting gender‑responsive digital inclusion.
As a next step, UNESCO invites you all to contribute to the roadmap for language technologies, roadmap which is now online for public consultation. Your contribution will help us shape this global process.
In closing, let me share wise words of Nelson Mandela who said, quote, talk to a man in a language he understands, that goes to his head. Talk to him in his own language, that goes to his heart. End of the quote.
Let's work together. Digital future speaks not only to minds, but to hearts, through linguistic justice, cultural dignity, and inclusive technology. Thank you.
>> SJUR NORSTEBO MOSHAGEN: Thank you very much. That is the end of the panel discussion. Time is out. Thank you all participants in the audience. Thank you very much.
[applause.
