I have just published a piece called “To Dig Where I Stand” on Marshall on Policy. It is not an essay on housing, infrastructure, energy, governance or any other policy topic, in away it's about all of them. It attempts to answer a question that I had not realised readers were asking:

“What exactly are these essays trying to do?”

The answer eventually led me to identify three principles that seem to have emerged from the writing itself:

• Understanding comes before prescription. • Sequencing is substance. • Relationships create outcomes.

They seem to have been present, sometimes only as undercurrents, in my essays about music, infrastructure, landscape and governance, long before I recognised them explicitly. Some assumptions run deep. Discovering them requires a degree of intellectual honesty, and perhaps a little perseverance.

That raises an intriguing possibility. Perhaps an essayist does not invent a method so much as discover one, much as a river discovers its course.

Update from the “should I start a YouTube channel” saga, for the three of you following along. Short version: I was about to make a common mistake, and a boring research afternoon talked me out of it.

Key takeaways

• “Topics I like that seem to do well” is a list of the most contested ground on the platform.
• Look at demand and competition together, not at what already looks successful.
• A beginner's only real edge is a niche with real search demand and weak, dated coverage.
• Low competition can also mean low demand. An empty niche is sometimes a warning, not an opening.

The mistake I almost made

The mistake was going to be personal finance. I like the topic, I know a fair amount, and every video I admired seemed to be in that world. So obviously I would make one too. This is how most channels are born and also how most channels die, and I could not see the problem from inside my own enthusiasm.

Why “topics I like doing well” is a trap

“Topics I like and see doing well” is a list of the most contested ground on the platform. The videos I admired were doing well despite brutal competition, made by people who had been at it for years with budgets I do not have. Walking into that as a beginner is not a plan. It is volunteering to be invisible.

Look at demand and competition together

What reoriented me was spending an afternoon looking at demand and competition side by side instead of chasing what looked successful. I used a tool to find a low-competition YouTube niche, which scans for where search interest is real but the existing coverage is thin, rather than where the big, obvious money already is. The difference between those two maps is the whole game, and I had been reading the wrong one.

The winnable niche next door

Broad personal finance was a wall: enormous demand, enormous competition, no room for a beginner. But a few sub-niches underneath it looked completely different. One specific corner, a narrow financial situation that a lot of people search and almost nobody makes good videos about, had steady demand and weak, dated coverage. That is not a smaller version of the crowded niche. It is a different, winnable niche that happens to live nearby.

A caveat: empty can mean no demand

One caution I want to keep visible, mostly for myself. Low competition can also mean low demand, and a niche being empty is sometimes a warning rather than an opening. The tool shows you where the gap is. It does not promise the gap is worth filling. That judgment, and whether I can actually make something good in that corner, is still on me.

The decision

I have not filmed anything yet, so this is a decision story, not a success story. The decision is that my first ten videos go to the narrow, underserved corner, not the broad, glamorous topic, because a beginner's only real advantage is picking a fight nobody bigger is bothering to have. If you are about to start a channel, spend one afternoon on demand and competition before you commit a year to the wrong niche.

Andreas from 82Mhz just published he is joining #Blaugust 2026. I remember I joined in 2024 and it was a fun way to keep blogging. I had an introduction post back then, and although most of it is still current, I will do a quick update here:

• I still work in construction as an estimator, and I am now considered a senior estimator in my team.
• I still love reading, and it is my main hobby, as attested by the posts on this blog. I am very much a sci-fi and fantasy reader, but I’ve been distancing myself from anything too dark or grim. I balance my reading with some fluffly romances sometimes. I’ve been better at dumping a book when it’s not working for me.
• Still an introvert and cherishing quiet time and actitivites that bring me calm: running, walking, reading, journaling, meditating and listening to music.
• I’ve started Bullet Journaling recently and it has been a big change for me. I plan on writing more about this experience. I am becoming more and more inclined to use paper and take notes by hand (I’m actually drafting this post by hand right now).
• I haven’t been playing a lot of video games lately, most of the time I will just prefer to sit down with a book. But I want to get back to some of the games I’ve started.

So for the 2026 Blaugust I want to go for the Silver Award with 15 posts in August.

I’ve been wishing to write and publish more frequently on this blog, so Blaugust is a great accountability tool to me keep me going.

Some Blaugust references I came across that inspired me to join:

• Let's do Blaugust by 82MHz
• Welcome to Blaugust by Tangent Space
• Blaugust 2026 is Coming! by Nerd Girl Thoughts

#Blaugust

31 July 2026

Visited Tobias's studio ahead of our upcoming conversation for the podcast and got to spend some time with the body of work he has been developing (he showed me nine paintings made over what I believe he said was the past eight or nine months). It's excellent, inspiring work, so I'm getting some notes down here.

Firstly, gridding; these paintings establish a conversation with gridding that isn't so much a system as it is an ongoing set of suggestions around the reactions a system might imply. A—let's say roughly nine—quadrant grid is repeatedly alluded to and yet never exists as a graspable solid framework. Even in one work where the quadrants are quite forward, hard-edged, and visible, their form-defining borderlines tilt, skew, echo, and overlap such that the effect is something like pieces of paper strewn around a flat surface or windows containing ranges of seasonal or emotional states. In fact, (and I know I'm prone to bringing him up), I sense something of Jasper Johns's Seasons (1987) etching and aquatint works (and the totality of his work more broadly speaking) in these paintings in that form seems to be mostly utilized and dilated to open the door for focus to constantly shift and for something else to appear on the surface. And that something else might hint at locatable subjects, (in working titles and early associative thoughts, Tobias mentioned words like “reservoir” and “diesel,” and I do sense a kind of lingering omnipotent noxiousness), but ultimately passes them by as it moves around in search of new formal relationships to unpack. It's not purely formal work, but it understands its way in.

Tobias mentioned Manet with regard to his ability to deploy structures around figures that create a certain leeway for perhaps more experimental whims or marks to feel justified within those structures, and I get what he means while looking at his work (although he also spoke of confronting limitations, and I think Manet's were ultimately the cause of some of his weirder and more spatially confounding and therefore more timeless paintings). But in Tobias's case, as I've already alluded to, I think his freedom unlocks from manipulating the structure itself. And therein lies a sort of twisting of subject into content and back again that makes the work generative and fresh. In paintings beyond the aforementioned most delineated one, the grid collapses, rotates, curls, disintegrates, compresses, duplicates, and glitches. In these ways, one of the main elements being constantly negated is rigidity. Which is further enforced by the mostly pale, subdued, often muddy, deceptively gentle palette. I say deceptively because the work doesn't read as gentle to me, but it does read as unified by a considered sensitivity.

More thoughts to come, but that's a start.

29 July 2026

“The General” by Bernadette Mayer, from The Old Style Is Finding out Something about a Whole New Set of Possibilities (1966-70)

Later in secret Later in secret the general Bends to remove something To lean against a fresco. The rules which run Around the walls The walls of court Determine a course, Declare if he had not:

Sulphur and pitch, sulphur and lead, sulphur and gum mastic, sulphur and varnish, mixed with the husks of pine-kernels, sawdust, isinglass, shells of snails, husks of beans, and seed of myrtle.

From here any direction is shown. The woods must be razed — resumption of growth The market growing, profusion, the question To hold — to hold Parts or acts in the act of disintegrating wholly. A sign over the hull — the evening In a complex of other evenings Behind the intervening ledge, the general.

I like to put parameters into Google and have it present me with a question that I might not come up with myself. It allows me to think about things that I might not normally. Today's question is as follows:

“Imagine a new global law mandates that every citizen must publicly wear a digital badge displaying the exact percentage of how much they actually like the person they are currently talking to.

How would your relationships change? Would you avoid people? Would it destroy polite habits in interactions?”

I am not sure that I'm going to answer these questions exactly, because I think the idea behind them is more intriguing. Psychologically, how would that change us? Could it be a positive change? Could it be a negative change? I think it would be an intriguing change.

We would have to become comfortable in our skin. I suppose it could go the exact opposite way considering how daft we can be, but if a generation grew up from the start having that and not being encouraged to ensure that they succeed in popularity, it could possibly be a pretty positive thing. I mean, unless someone is extremely good at acting, we have an instinct of whether a person likes us or not. We ignore it. This would force people to acknowledge it. But it would also allow people to no longer mask. Perhaps it would allow for greater professionalism. Perhaps it would help us become less insecure. Then again it could force more insecurity upon people with this abundant need to be liked that exists today.

Maybe I should answer the questions as opposed to just letting my mind wander off in a million directions like I tend to do. How would it change my relationships? I think it would make my relationships more honest in some cases, but in others I don't think it would change them at all. If anything it might give the person reassurance that, “Hey I actually enjoy your company.” In the ones where the score might be lower than the other person expects I think it would open up that opportunity to talk about why. Perhaps it would make communication better for most people since we tend to avoid those topics. I think most people are afraid of the answers they might receive.

I rather like the idea, since it would grant opportunity for self-growth. I don't like the idea because I think it would further numb our own awareness. Which perhaps brings about another question as we become more technically inclined. What trade-offs are worth trading off? Is easy access to such knowledge worth the loss of an instinctive comprehension? And would it feed our negative or our positive impulses?

For me, any question that is like this is not about the immediate or secondary or third possibilities. I prefer to look long range and then come backwards from the furthest point out that I can think of. We can't know what shifting any one thing is going to cause because there will be elements that come into existence that we never thought of before, and that will have pivotal changes in our course. But we can ponder beyond the immediate as far as risk versus reward goes and try to contemplate and comprehend the shifts across a wide spectrum.

I think one of the things that would probably happen is people would try to place such a thing on animals and then would get upset if their cat or dog doesn't like them in a moment. I wonder if they would take it out on the cat or dog versus figuring out why. People are so poor at figuring out why and trying to communicate and comprehend a different perspective, that I think it could really bring up some issues across a vast majority of people.

Would I avoid people? I already avoid people. 😹 I don't think it'd have an effect on the number of my interactions. Though from a curiosity standpoint, I would possibly engage with more people just to observe the like/dislike perspective. Yes. I can see how I could become amused by that for a short term if I'm being honest with myself. Reactions would likely sway how quickly I got bored. I find constant engagement with people to be exhausting as is. I think it'd be interesting to see the awareness form between perceived likability/popularity and reality in various persons. It'd also be interesting to witness how that factor might shift and affect things. There's a lot of possible parameters involved. It could be interesting to watch the birthing of awareness.

Would it destroy polite interactions and habits? I think it would evolve them. What would be interesting would be if a person were capable of masking well enough to throw off the measurement. If not, networking would become an absolute riot.

The more I think about it, the more options of what could occur flutter through my mind. It would certainly create a very different world than we live in now. Would it be for the better or worse, I do not know. How adaptable are we at that psychological level? Would it evolve our thinking and perception of others and self? Would it increase popularism or force it into extinction? Would everything lay somewhere in between? Would we have to become comfortable with being uncomfortable? It would be a very exciting experiment to run with persons willing to submit themselves to it. Especially when we consider the lie we tell ourselves of how we are being perceived quite often.

I think the question that I would be even more interested in seeing placed and hearing the response to would be if we looked into the mirror would we then get a result of how much we like or dislike ourself? And if that percentage number was accurate, would it encourage us to shift and like ourselves more? Curiouser and curiouser. I would be interested to see how much I like myself. I think I like myself somewhere around 90% or above. There are a few things that I would like to improve upon, but overall I have learned to be someone who I enjoy. I would like to see if that's true or not. Could I be lying to myself? Oh the questions that this brings up.

How about you? What do you think of such an event? And how much do you like yourself? Do you even know? Dun. Dun. Duuuuuuuuuuuuunnnnnnnn...

Written August 1, 2026. © 2026 AnOublietteofThought.

Eu nem acredito que estou fazendo isso em pleno ano de 2026, quando a IA está no seu momento mais supervalorizada e quando todos os olhos estão voltados para a facilidade que ela nos impõe.

Para começar, eu não sou uma anti-tecnologia – eu to muito longe disso (se é que posso voltar a ter o direito de usar travessão sem acharem que o texto é do chat). Atualmente trabalho como social media gerenciando minha própria agência de marketing digital, mas um dia, num passado tão tão distante (digamos uns 10 anos atrás?) me via formada em jornalismo escrevendo textos enormes e decorando livros ainda maiores. A pergunta é: aonde foi que eu me perdi?

Voltando ao assunto, o ano é 2026 e me vi nos últimos tempos sedenta por ler textos reais. Aqueles que são escritos por gente real, com erros reais, com pensamentos que vão e voltam. E, no meio de tanta criação de conteúdo que me vejo fazendo no Instagram para ajudar outras empresas a crescerem no digital, dentro de mim um sopro: e se a gente voltasse a fazer textão? Daqueles que ninguém mais lê. Daqueles que só lê quem realmente gosta de textão verdadeiro, feito à mão.

Pois bem. Deus tem seus jeitinhos de falar comigo. E cá estou eu, num sábado chuvoso, 7 da noite, com meu filho recém dormido no meu colo abrindo um blog para criar textos e conexões sobre assuntos que me vem à mente.

Da maternidade ao mundo digital, da vida cotidiana à fé. Vocês vão ver de tudo aqui… só não vão ver texto de IA. Porque Deus me teceu no ventre da minha mãe com um dom que não posso deixar desperdiçar em 2.200 carácteres de legenda do insta.

Bem-vindos ao meu mundo sem cortes.

Com amor,

Kyane Vives.

I’m thinking about the YouTube video that I was watching again that at one point talked about the different kinds of love according to an old study, there were things about passion, things about practicality about competition and so forth. I matched with someone today that I feel like I have pretty good synergy with communication style-wise. I wonder if this is something that I can hope for an a partner or if it’s one of those unimportant goals.

A creator I follow built a series around a single recurring on-screen host. The host was the identity of the whole thing, the reason viewers came back. The problem showed up once the series scaled: producing a believable, consistent host for every episode meant either filming the same person on a strict schedule forever or accepting that any shortcut left the host looking slightly off, usually because the mouth did not quite match the words. A series lives or dies on consistency, and the specific detail that kept breaking that consistency was lip sync.

This is a real constraint for any content built around a recurring presenter or character. The host is the brand, so every episode has to look right, and the thing viewers notice first when it does not is speech that does not match the mouth. Getting that consistently correct, episode after episode, is exactly where a series-based format gets expensive and fragile.

Why consistency is hard to sustain

A recurring host is only an asset if it looks the same and reads as believable every time. Filming that consistently means a person and a schedule that never slip; any generated shortcut that gets the lip sync wrong undercuts the identity the series depends on. So creators either lock themselves into an unsustainable production cadence or watch the host quality drift across episodes.

A consistent, synced host every episode

What makes a series-based format sustainable is a tool that produces the same host with the mouth matched to the script, every time. That is part of what Leadde.ai does: you can generate an avatar from a single photo or use a built-in presenter, lock in that host, and produce each episode from a script with the speech synced to the delivery. Because the host is generated rather than filmed, it looks the same in episode fifty as in episode one, and the lip sync is handled so each episode avoids the mismatch that usually signals a shortcut. A correction is editing text and regenerating, not reshooting, and support for a wide range of languages lets the same host front the series in more than one.

Where it fits for series and character-led content

The uses are concrete. A creator sustains a recurring on-screen host across a long series without an endless filming schedule. A brand keeps a consistent presenter across a content program. A channel produces the same host in more than one language while keeping the identity intact. In each case the format depends on consistency, and the tool supplies a host that stays believable episode after episode.

Where it falls short

Being straight matters, because this is a synthetic host. It reads as generated on close attention, so for content where a genuinely human, filmed presence is the whole appeal, film a real person. It suits clear, spoken delivery more than expressive or physical performance, where the limits show. And you should only build a host from an image you have the right to use, with a real person's likeness requiring their consent, and never use it to make someone appear to say something they did not agree to. A consistent synthetic host is a fine creative choice; impersonating a real person is not.

A small first test

Don't rebuild the whole series on it. Produce two or three episodes with a consistent generated host on a free tier, using a face you are entitled to use, and check whether the host holds up believably across them, lip sync included. If a consistent, synced host stays convincing episode to episode, it is worth using for the series, and your recurring format stops depending on a filming schedule that never slips.

Until this month (July 2026), I was very hesitant to claim the term “disability pride”, as I don’t see autism or any other form of disability as something to be proud of. However, especially with the recent government attacks on disability access and programs, I can’t skimp on embracing whatever helps anymore.

I didn’t get diagnosed until nine and, before that, the only special ed help that I received was a program mostly for kids in broken homes in a retired principal’s house. But since that went only to the first grade, my mother homeschooled me for second, and the beginning of third, grade. However, just sitting doing a bunch of book- and paperwork lessons all day has never connected with my way of learning. That’s always been more my mother’s way of learning, and I think she assumed that just because I’m her daughter, I would automatically learn in the same way. She also couldn’t accept that I’m not the straight-A student that she was.

Special projects, art, and special demonstrations have always been more my way of learning. I can remember my mother doing exactly one project with me, and that was after I finished reading Laura Ingalls Wilder’s Little House on the Prairie. We made a replica of the house in Kansas out of a bunch of paper towel rolls with the roof and family out of cardboard cutouts—the latter, which my mother copied from illustrations in the book. My mother then insisted on putting all of the family cut-outs inside of the house replica and sealing it with the roof. She also wouldn’t cut out a door in it as she didn’t want me to reach back in to take them out.

I didn’t receive any special education at Shirley Elementary, my school in Arkansas. Since it was in a rural town, I’m not sure that Shirley even had much of a special education program. The only thing I remember closest to that was when *Mrs. Blanken, the counselor who tested me to make sure I was ready to be placed in a third-grade classroom. I believe that I was earning mostly C’s, so I wasn’t doing super badly. But, also considering the abuse that I was still enduring at home plus my parents’ separation and subsequent divorce, I never felt as if I really learned much from there.  I also hadn’t been diagnosed just yet.

It wasn’t until after my grandparents got me diagnosed at nine that I was able to receive the learning center assistance in subjects that I was the weakest in: math and reading comprehension. I didn’t connect with either one at all back then. Today, my reading comprehension and critical thinking skills are no contest to what they used to be. Although if you were to make me do a reading comprehension assignment now, I would still have to look back at the text to make sure I’m getting all of the important information and that I’m remembering everything right.

I was also in speech therapy through my school for almost three years, which I found very helpful, at least in the short term. Unfortunately, though, it didn’t help with my stress stammering in the long run. Though I sometimes also stammer when I haven’t verbalized in a little while. I hate it when that happens, too! Though I’ve found that warming up my old choir voice to my car music really helps me keep that in check.  I didn’t realize until very recently that music is also a sensory seeking thing for me.

However, the special education class that helped me the most was my Job Club class in high school. It prepared me for basic interview, and on-the-job etiquette, for considering the entirety of a job description before deciding whether to apply. And then, wearing our “uniform” of black pants and a white shirt, we would go out on mini unpaid internship-like fieldtrips to practice working. Usually with minimum-wage jobs like stocking, cleaning/busing tables, and helping out in food court restaurants. Though they “promoted” me to assisting a local elementary school art teacher when I told them that I was hoping to do that after college.

I believe that it’s partly thanks to my Job Club class that I’m the dedicated employee that I am today. That and I come from a family with a very strong work ethic.

It scares me that, without all of the special education assistance and therapies that I did have, I probably would’ve been thrown in an institution. It scares me that that could be the future for kids with disabilities again. That they will grow up being deprived of those rights, deprived of their sense of humanity, and deprived of their sense of individuality, not knowing the freedoms that my generation has been very fortunate to have. Which is what JFK and others, like Judith Heumann, worked so hard, even put their very lives on the line, to ensure wouldn’t happen again.

This is why disability advocacy is needed now more than ever. And why I consider myself to be one now.

 

 

Mehndi is an important part of many festivals and celebrations, and finger mehndi has become one of the most popular trends in recent years. Unlike full-hand mehndi, finger designs are simple, elegant, and easy to apply. They add a stylish touch without covering the entire hand, making them perfect for both traditional and modern looks.

Minimal floral patterns, leafy vines, geometric shapes, and Arabic-inspired designs are among the most loved styles. Whether you're attending a wedding, celebrating Eid, Karwa Chauth, Teej, or Diwali, finger mehndi designs complement every outfit beautifully.

Explore the Latest Finger Mehndi Design Collection

If you're searching for fresh and creative finger mehndi design ideas, you'll find a wide variety of elegant patterns that suit every occasion. From simple everyday styles to intricate festive designs, the collection includes high-quality images that inspire both beginners and experienced mehndi lovers.

The gallery features modern, Arabic, traditional, bridal, and minimalist finger mehndi styles, helping you choose the perfect design based on your personal preference.

Perfect for Festivals and Special Occasions

Finger mehndi is ideal for those who want a beautiful look without spending hours applying henna. These designs look amazing with rings, bracelets, bangles, and ethnic outfits, making them a popular choice for weddings and festive celebrations.

Many girls also choose finger mehndi for casual gatherings because it creates a fashionable appearance while remaining lightweight and elegant. Small floral motifs, dotted chains, and stylish finger bands can completely transform the look of your hands.

Easy, Stylish, and Trendy Designs

One of the biggest advantages of finger mehndi is its versatility. Whether you love traditional artwork or modern minimalist patterns, there is a design for everyone. These elegant patterns are also perfect for Instagram photos, Pinterest inspiration, WhatsApp status updates, and social media posts because they look clean, attractive, and highly aesthetic.

Beginners often prefer finger mehndi because it requires less time and fewer materials while still producing stunning results. Professional mehndi artists also use finger-focused designs to create unique combinations with wrist and palm patterns.

Why Finger Mehndi Design Is So Popular

Mehndi is an important part of many festivals and celebrations, and finger mehndi has become one of the most popular trends in recent years. Unlike full-hand mehndi, finger designs are simple, elegant, and easy to apply. They add a stylish touch without covering the entire hand, making them perfect for both traditional and modern looks.

Minimal floral patterns, leafy vines, geometric shapes, and Arabic-inspired designs are among the most loved styles. Whether you're attending a wedding, celebrating Eid, Karwa Chauth, Teej, or Diwali, finger mehndi designs complement every outfit beautifully.

Explore the Latest Finger Mehndi Design Collection

If you're searching for fresh and creative finger mehndi design ideas, you'll find a wide variety of elegant patterns that suit every occasion. From simple everyday styles to intricate festive designs, the collection includes high-quality images that inspire both beginners and experienced mehndi lovers.

The gallery features modern, Arabic, traditional, bridal, and minimalist finger mehndi styles, helping you choose the perfect design based on your personal preference.

Perfect for Festivals and Special Occasions

Finger mehndi is ideal for those who want a beautiful look without spending hours applying henna. These designs look amazing with rings, bracelets, bangles, and ethnic outfits, making them a popular choice for weddings and festive celebrations.

Many girls also choose finger mehndi for casual gatherings because it creates a fashionable appearance while remaining lightweight and elegant. Small floral motifs, dotted chains, and stylish finger bands can completely transform the look of your hands.

Easy, Stylish, and Trendy Designs

One of the biggest advantages of finger mehndi is its versatility. Whether you love traditional artwork or modern minimalist patterns, there is a design for everyone. These elegant patterns are also perfect for Instagram photos, Pinterest inspiration, WhatsApp status updates, and social media posts because they look clean, attractive, and highly aesthetic.

Beginners often prefer finger mehndi because it requires less time and fewer materials while still producing stunning results. Professional mehndi artists also use finger-focused designs to create unique combinations with wrist and palm patterns.

I can’t believe we are past 50 days of not working. It has gone way longer than I thought it would. I have decided today to stop checking every day. Instead, I will just wait for the email when there is an update. They always send an email, so instead of logging in anxiously every day, I will just wait.

I also got the seed of a somewhat crazy, somewhat ambitious life change that I may look more closely at in the coming months. It is something I considered a few years ago but ended up not pursuing due to the start of my last relationship. Seeing how things turned out, I wish I had ended that relationship sooner and started my quest back then instead. Now I am starting to have the same inkling and I would rather not look back in five years and wish what I wish I had done five years ago. I need to do very thorough research and be very patient, and brave.

I won’t get into the weeds of it because the truth is I don’t know if I have the guts to jump that far. I will sleep on it for a couple of months, or maybe when my situation gets a positive update. Just like everything else, for now we wait.

Thank you for your message. I am currently out of office with no set return date. I will get back to you when the time is right.

Street stalls + food trucks on Sunset Blvd between Figueroa & Beaudry…

Multiple days, things move around, some are closed on certain days.

1. Hyperfocus: The New Science of Attention, Productivity, and Creativity by Chris Bailey, 256p: Great read about focus with enough scientific data and practical insights. The author talks about “attentional space”, which is like our RAM or the available working memory capacity. He argues that because the amount of distraction machines we have available at our fingertips right now, our attentional space shrinks and our minds wander less, reducing the quality of our attention. The author explores “hyperfocus”, which is deep, intense focus on an activity, versus “scatterfocus” which is mind wandering. Both of these modes are important and there are nice diagrams to help understand the concepts.

2. Captain Vorpatril's Alliance (Vorkosigan Saga (Publication Order)) #15 by Lois McMaster Bujold, 580p: This time a fun adventure with Miles' cousin: Ivan Vorpatril. It's the Ivan book! It is packed with action and Ivan getting caught in hilarious situations. Miles and Ekaterin make some appearances, but we also see Simon, Alys, Gregor and even Cordelia in some scenes. There is mystery, a fake marriage situation, family secrets and failed engineering with sinking consequences. Tej's family had an interesting mafia vibe without malice, just pure family loyalty and eccentric choices. Overall a funny and lighthearted book, which matches Ivan's eternal optimism.

3. Children of Strife (Children of Time #4) by Adrian Tchaikovsky, 496p: I didn't find this book as enjoyable as the previous ones in the series. The pacing was off, with these three different timelines alternating. Some chapters felt repetitive, telling the same story already covered in previous books. The First Age chapters with the human terraformers was by far my least favorite timeline. The Second Age with the ark ship was so-so. The only timeline I was invested in was the Third Age with the excellent mantis-shrimp hero called Cato. I missed seeing the octopuses and the corvids. 

#readinglist #books #reading

In March 1890, an anthropologist named Jesse Walter Fewkes carried a wax-cylinder phonograph to Calais, Maine, and over three days recorded thirty-six cylinders of Passamaquoddy songs, creation stories, vocabulary and legend. The voices belonged mostly to two men, Peter Selmore and Newell Josephs. Fewkes was experimenting; he wanted to know whether the new machine could capture human speech in the field. The result is now understood to be the oldest surviving ethnographic field recording anywhere in the world. For more than a century those cylinders sat in institutional custody, first at the Peabody Museum of Archaeology and Ethnology at Harvard University and then, from 1970, inside the American Folklife Center at the Library of Congress, catalogued, preserved, and effectively unreachable by the community whose ancestors had sung into the horn. Of the original thirty-six, only twenty-six remain playable.

Nobody in 1890 asked Peter Selmore whether his voice could be digitised, indexed, transcribed by an algorithm, or fed into a statistical model that might one day predict the next word in a Passamaquoddy sentence. The question would have been unintelligible. The technologies that make it urgent did not exist, and the legal framework that might have answered it did not exist either. That gap between how the material was gathered and what can now be done with it is the precise location of a fight that reached the United Nations in the summer of 2026.

At the nineteenth session of the Expert Mechanism on the Rights of Indigenous Peoples, held at the Palais des Nations in Geneva from 13 to 17 July 2026 with a dedicated panel on artificial intelligence and the rights of Indigenous Peoples on its agenda, Indigenous advocates from several countries pressed a demand that a decade ago would have sounded speculative. They argued that artificial-intelligence systems are now being trained on, and deployed against, the vast holdings of Indigenous cultural material sitting in universities, museums, national libraries and government archives, and that the institutions holding those materials have no clear obligation to treat tribal authority over the knowledge as anything more than a courtesy. The oral histories, the language recordings, the ceremonial records, the photographs, the governance documents, much of it gathered under conditions that would fail any serious contemporary standard of informed consent, are being converted into training data and searchable outputs that serve outside purposes. The communities from which the knowledge originated are frequently the last to know.

The question at the centre of the Geneva session was not whether this is happening. It plainly is. The question was whether anyone is legally, ethically or procedurally required to stop it, or to ask first.

How an Archive Becomes a Model

To understand what changed, it helps to be precise about the mechanism. A June 2026 analysis published in Governing by Kerri J. Malloy, an assistant professor of Native American and Indigenous Studies at San José State University and a citizen of the Yurok and Karuk peoples, laid out the sequence in unsentimental terms. AI systems scrape materials held in institutional archives and digital repositories without reference to tribal authority. Those materials are converted into training data or into searchable, generative outputs. The outputs serve the purposes of the party running the system, which is almost never the community whose knowledge was ingested. Malloy, whose scholarship centres on genocide, transitional justice and the mechanics of redress, frames this not as an accident of technology but as the latest expression of a much older pattern, in which knowledge is separated from the people who hold it and put to work elsewhere.

The point worth dwelling on is that the scraping requires no malice, or even any awareness that the material is Indigenous. A digitised photographic collection, a corpus of transcribed oral histories, a set of language recordings released under an open licence by a well-meaning library: to a web crawler assembling a training set, these are simply text, image and audio. The metadata that would flag a recording as ceremonial, restricted, seasonally sensitive, or governed by protocols about who may hear it and when, is either absent or discarded during ingestion. The model learns the patterns and forgets the provenance. What comes out the other side is a system that can generate plausible imitations of a cultural form, answer questions about restricted knowledge, or reconstruct fragments of a language, without any accountability toward the community.

This is the harm that data-sovereignty scholars have described for years under the heading of data colonialism, a term meant to make the analogy explicit: just as historical colonialism appropriated land and labour, the contemporary extraction of data and knowledge appropriates the raw material of culture and computation. The analogy is not rhetorical excess. The material sitting in these archives arrived there through the same institutions, and often the same expeditions, that removed ancestral remains and ceremonial objects. The wax cylinders and the funerary belongings travelled together. That the recordings can now be reanimated by machine learning does not sever them from that history. It extends it.

What Geneva Was Actually Arguing About

The Expert Mechanism on the Rights of Indigenous Peoples is not a court, and it cannot compel anyone to do anything. Established by the Human Rights Council in 2007 under resolution 6/36, it is a body of seven independent experts that provides the Council with advice and expertise and assists states in achieving the goals of the United Nations Declaration on the Rights of Indigenous Peoples. Its authority is persuasive rather than coercive. But the instrument it exists to interpret carries more weight than its soft-law status suggests, because a great many of its provisions are now treated as reflecting customary international norms.

That instrument, the Declaration adopted by the General Assembly in 2007, contains in Article 31 a passage that reads with uncanny prescience given what has happened since. Indigenous peoples, it states, have the right to maintain, control, protect and develop their cultural heritage, traditional knowledge and traditional cultural expressions, as well as the manifestations of their sciences, technologies and cultures, including human and genetic resources, seeds, medicines, knowledge of the properties of fauna and flora, oral traditions, literatures, designs, sport and traditional games, and visual and performing arts. They also have, it continues, the right to maintain, control, protect and develop their intellectual property over such cultural heritage, traditional knowledge and traditional cultural expressions.

Read in 2007, Article 31 was understood mostly as a shield against biopiracy and the commercial appropriation of designs and medicines. Read in 2026, the phrase “maintain, control, protect and develop” runs directly into the architecture of machine learning. If a community has the right to control its traditional cultural expressions, and an AI company ingests a digitised archive of those expressions to train a commercial model, the community's control has been overridden without its involvement. The Declaration also insists, repeatedly, on the principle of free, prior and informed consent, the requirement that Indigenous peoples be consulted and give agreement before measures affecting them are taken. The Expert Mechanism has previously produced a dedicated study on the repatriation of ceremonial objects, human remains and intangible cultural heritage, explicitly bringing the intangible, the songs and stories and knowledge, within the frame of restitution. The 2026 advocates were extending that logic one step further, into the training corpus.

The gap the Geneva delegates were pointing at is the gap between principle and obligation. The Declaration says communities have the right to control. It does not say that a university digitising its holdings must obtain consent before a third party scrapes them, nor that a museum must embed enforceable restrictions in the metadata it publishes, nor that an AI developer must check provenance before ingestion. Those operational duties do not yet exist in most jurisdictions. The advocates wanted them written down.

The Principles Built Before the Machines Arrived

What makes the current moment unusual is that Indigenous communities did not wait for the AI industry to arrive before building governance frameworks. The intellectual scaffolding was largely in place, developed through the 1990s and 2000s in the context of research ethics and health data, and it maps onto the machine-learning problem with remarkable directness.

The oldest of these frameworks is OCAP, the First Nations principles of Ownership, Control, Access and Possession, established in 1998 and now administered by the First Nations Information Governance Centre in Canada. OCAP holds that a First Nation collectively owns its information in the same way an individual owns personal information; that it may assert control over data at every stage of the research cycle; that it must be able to access information about itself regardless of who physically holds it; and that possession, the physical custody of data, is the mechanism that makes ownership more than symbolic. The last principle is the sharpest when applied to AI. Possession says that if you want to protect knowledge, you keep it where you can defend it. A model trained on a copy you no longer control is the negation of possession.

The more recent and internationally influential framework is the set of CARE Principles for Indigenous Data Governance, drafted at a workshop in Gaborone, Botswana, in November 2018 and published through the Global Indigenous Data Alliance. CARE stands for Collective Benefit, Authority to Control, Responsibility and Ethics, and it was written deliberately as a counterweight to the open-data movement's FAIR principles, which hold that data should be Findable, Accessible, Interoperable and Reusable. The tension between the two acronyms is the entire argument in miniature. FAIR optimises for sharing and reuse; it says nothing about power, history or consent. CARE was built to reinsert those considerations, to say that the ease with which data can be shared is not the same as the right to share it, and that governance must account for the power differentials that shaped how Indigenous data came to sit in institutional hands. The Authority to Control principle is unambiguous when applied to a training set: the authority to decide whether a corpus becomes model weights rests with the community, not the archive.

These frameworks share a feature that distinguishes them from most Western data-protection law. They treat knowledge as collective and relational rather than as individual property with a fixed author and an expiry date. Conventional intellectual-property regimes are built around individual ownership, novelty and a term that eventually lapses into the public domain. Indigenous knowledge is frequently held communally, transmitted orally across generations, and governed by protocols that have nothing to do with authorship and everything to do with relationship, season, initiation and place. When a song enters the public domain under copyright law, the community's protocols governing who may sing it do not lapse. The two systems are not merely different in detail; they are built on incompatible premises about what knowledge is and who it belongs to. The scraping of an archive collapses that incompatibility in favour of the system that ignores protocol.

The Labels That Travel With the Knowledge

If the principles are the theory, a handful of practical tools have emerged to make them operational, and their design reveals how hard the problem actually is.

The most widely adopted is the system of Traditional Knowledge and Biocultural Labels developed by Local Contexts, an organisation co-founded by the legal scholar Jane Anderson and the digital-humanities scholar Kim Christen, and now co-directed by Christen, Anderson, Māui Hudson of Whakatōhea and James Francis of the Penobscot Nation. The Labels are not licences in the copyright sense. They are metadata, attached to cultural material, that carry the community's own statements about provenance, protocol and permission: who the cultural authority is, what traditional protocols govern access, and what uses the community regards as acceptable. A Provenance Label identifies the group that holds authority over the material. A Protocol Label communicates the customary rules attached to it. A Permission Label states what the community has approved. The point is to make Indigenous authority legible inside the metadata of a digitised collection, so that a curator, a researcher, or in principle an automated system, encounters the community's terms at the moment of access rather than never.

The companion tool comes from the same hand: Mukurtu, a free, open-source content-management system first built in 2007 by Christen and the developer Craig Dietrich for the Warumungu Aboriginal community in central Australia, and now maintained at Washington State University. Mukurtu was designed around a premise that most archives find alien: that access should be differential rather than uniform. A single item in a Mukurtu archive can be visible to the general public in one form, to community members in another, to a particular family or ceremonial group in a third, and to no one outside a restricted circle at all. Where a conventional digital repository asks how to maximise open access, Mukurtu asks who is allowed to see what, and encodes the answer.

The Passamaquoddy cylinders became the demonstration case for all of this. When the Library of Congress launched its Ancestral Voices project, engineers at its National Audiovisual Conservation Center used an Archéophone playback machine and digital restoration systems to extract sound from the 1890 wax that had been physically unplayable, and then, crucially, handed curatorial control back toward the Tribe. Passamaquoddy speakers transcribed and translated the recordings; elders reviewed them; the material was described using Mukurtu and tagged with Local Contexts Traditional Knowledge Labels, so that the digitised voices now travel with the community's own statements of authority and protocol attached. It is the closest thing to a model of how digital repatriation can work when an institution chooses to share power rather than merely access.

But the Passamaquoddy case also exposes the limit of the whole apparatus, and it is a limit the Geneva advocates understood well. Labels and differential access work only inside systems that agree to honour them. A Traditional Knowledge Label is metadata; a web crawler assembling a training corpus is under no obligation to read it, and a large language model does not preserve it. The moment a labelled recording is copied outside the governed platform, whether by an open-data release, a partner institution's mirror, or a scraper that ignores robots directives, the protocol evaporates. The tools that Indigenous communities built to assert authority were designed for a world of human curators making deliberate choices about individual items. They were not designed for a world of automated ingestion at web scale, where the default is to take everything and ask nothing.

When Revitalisation and Extraction Use the Same Tool

The uncomfortable truth threaded through the whole debate is that the technology now driving the extraction is the same technology offering some communities their best hope of linguistic survival. This is not a case where the harm and the benefit are cleanly separable. They run through the identical set of tools.

An analysis published in July 2026 by researchers at the University of Melbourne made the double edge explicit. The same AI systems that can support Indigenous language revitalisation, generating learning materials, reconstructing grammatical patterns from fragmentary historical records, filling gaps in documentation left by generations of suppression, can, if they are built and controlled by outside institutions, deepen the very patterns of extraction they appear to remedy. The mechanism is concentration of authority. A language model that becomes the authoritative interface to a language, trained on the community's own recordings but owned and operated by a university or a company, does not restore control. It relocates it. The community becomes a user of a system built from its own knowledge, dependent on an institution it cannot govern. The Melbourne researchers were echoing a broader body of work, including a systematic review by the same group published in 2025, that has repeatedly found the governance question, who owns and controls the system, to be more decisive than the technical question of whether the tool works. A separate 2026 review in AI & Society, examining AI projects in Irish Gaelic, Māori, Guaraní and Inuktitut through the lens of data colonialism, reached the same place by a different route: what divides the initiatives that empower communities from those that reproduce extractive structures is not the model but who holds the data and sets the terms.

The counter-example that everyone in this field cites is Te Hiku Media, a charitable media organisation based in Kaitaia, in the far north of New Zealand's North Island, and belonging collectively to the Far North iwi of Ngāti Kuri, Te Aupōuri, NgāiTakoto, Te Rarawa and Ngāti Kahu. Facing the same problem every Indigenous community faces, that the large technology firms had little commercial interest in a language spoken by a few hundred thousand people, Te Hiku built its own. Through a crowdsourcing campaign called Kōrero Māori, it gathered more than three hundred hours of labelled speech in ten days, from more than 2,500 people reading over 200,000 phrases, and in 2021 released an automatic speech-recognition model for te reo Māori that reportedly reached around ninety-two per cent accuracy, outperforming the offerings of far larger companies on the language. The decisive move was not technical but legal. Te Hiku placed the resulting data and models under what it calls the Kaitiakitanga Licence, a bespoke instrument built on the Māori concept of guardianship, which keeps data sovereignty inside the community, prohibits uses that would surveil or discriminate, and ensures the data is used for the benefit of Māori. The organisation refused, publicly and repeatedly, to hand its speech corpus to outside firms, on the grounds that the community had gathered the data as a taonga, a treasure held in trust, not as a commodity to be sold.

Te Hiku is the proof of concept for the Geneva argument, because it demonstrates that Indigenous-governed AI is not a contradiction in terms. The community built the tool, kept the data, wrote the licence, and set the terms of use. What Te Hiku had, that most communities do not, was the technical capacity, the funding and the pre-existing organisational strength to do all of that itself. The Melbourne researchers' warning is aimed at the far more common situation, in which the community lacks the capacity to build its own system and the institution holding the material builds one instead, positioning itself, however benevolently, as the permanent intermediary between a people and its own language.

The Consent That Was Never Given

Every strand of this returns to the conditions under which the material was collected in the first place, and here the historical record is not ambiguous. The great archives of Indigenous cultural material were assembled overwhelmingly during the late nineteenth and twentieth centuries, in a period when the collecting institutions operated on the salvage assumption, the belief that Indigenous peoples were vanishing and that their cultures had to be recorded before they disappeared. The people recorded were rarely in any position to refuse, frequently were not asked, and could not conceivably have consented to uses that had not been invented. Fewkes did not, and could not, obtain Peter Selmore's agreement for a use case that would arrive one hundred and thirty years later.

This is what makes the informed-consent argument so difficult to wave away. When an institution says that its collection is lawfully held and that it is free to license or release it, the claim is legally true and ethically hollow, because the original acquisition would fail every element of the standard that institution would now apply to a living research subject. Contemporary research ethics require that consent be informed, specific, revocable and given by someone with the authority to give it. The archival material fails on all four counts. It was gathered without meaningful information about future use, without specificity, without any mechanism of revocation, and often from individuals who held the knowledge under community protocols that did not give them the personal authority to alienate it. A speaker might share a song with a visiting anthropologist without possessing the right, under his own community's law, to release it to the world.

The AI moment forces this latent problem into the open because it dramatically raises the stakes of the downstream use. For a century the material mostly sat inert, and the injustice of its acquisition, while real, was static. Digitisation made it copyable. Machine learning makes it generative. A model trained on a corpus of restricted ceremonial knowledge does not merely store that knowledge; it can produce new outputs in its style, answer questions about it, and disseminate approximations of it to anyone who asks. The original failure of consent is thereby compounded and multiplied, and the community's ability to enforce its own protocols, already eroded by digitisation, collapses entirely. The advocates in Geneva were not raising a historical grievance for its own sake. They were pointing out that the historical grievance is now the input to an industrial process.

Where the Law Stops Short

The obvious question is why existing law does not already resolve this, and the answer is that the relevant instruments were built for adjacent problems and stop short of the AI training set.

The most significant recent development is the WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge, adopted at a diplomatic conference in Geneva in May 2024 after decades of negotiation. It is the first WIPO treaty to deal with the interface between intellectual property and Indigenous knowledge, and its central mechanism, in Article 3, requires patent applicants to disclose the source or origin of genetic resources and associated traditional knowledge on which an invention is based. This matters, but its reach is narrow. It applies to patents, not to training data. It addresses the specific problem of patents being granted over Indigenous knowledge without acknowledgement, not the general problem of that knowledge being ingested by a model. And it enters into force only after fifteen states ratify it. Malawi deposited its instrument on 5 December 2024 and Uganda followed on 9 July 2025. That is the entire tally. Thirteen further ratifications are required, and more than two years after adoption the treaty is still not in force. The treaty is a disclosure requirement for one narrow channel of appropriation, not a consent requirement for the broad one, and even that narrow requirement is not yet law anywhere.

In the United States, the closest analogue is the Native American Graves Protection and Repatriation Act, whose revised regulations took effect in January 2024 and notably strengthened the requirement that institutions obtain consent from lineal descendants or tribes before exhibiting or conducting research on covered items. Those revisions prompted several major museums to close or cover Native American displays overnight while they sought the necessary consent. But NAGPRA governs human remains, funerary objects, sacred objects and objects of cultural patrimony in physical custody. It does not cleanly reach digitised sound, transcribed oral history or a language corpus, and it certainly does not reach a model trained on them. The statute that forced museums to reckon with consent for physical objects has no obvious purchase on the intangible material now flowing into AI systems.

Copyright, the tool a technology company would most naturally invoke, cuts the wrong way entirely. Much archival Indigenous material is old enough to be in the public domain, which under copyright law means it may be freely used, and the ongoing legal battles over whether training AI on copyrighted material constitutes fair use are, from an Indigenous-knowledge perspective, almost beside the point. The community's objection is not that its copyright has been infringed; it is that copyright never captured the interest at stake. A song can be simultaneously in the copyright public domain and subject to strict community protocols about who may perform it. The law that governs the copy has nothing to say about the protocol. This is the misalignment that CARE, OCAP and the Traditional Knowledge Labels were invented to address, and it is why the Geneva advocates were appealing to human-rights instruments rather than intellectual-property ones. The rights they are asserting do not fit inside the categories the technology industry recognises.

Procurement as the Real Decision Point

If the frameworks exist and the law lags, the practical question becomes where in the process an obligation could actually bite, and here the answer is less about technology than about timing.

Malloy's Governing analysis ends not with a call for better algorithms but with a call for meaningful tribal consultation before AI systems are designed and deployed, rather than notification after the fact. This is a deceptively large claim. In the ordinary institutional workflow, an organisation decides to acquire or build an AI system, selects a vendor, signs a contract, and only then, if at all, convenes a consultation about ethics and community impact. By that stage the architecture is fixed, the money is committed, and the consultation can influence little beyond the wording of a usage policy. Authority exercised after procurement is not authority at all; it is public relations. For tribal control to be real, the community's right to say no, or to set conditions, has to be available at the point where saying no would actually change the outcome, which is before the institution commits to building the thing.

This reframes the debate away from the familiar terrain of algorithmic transparency and bias auditing, which are downstream remedies, and toward the upstream decision that determines whether a system gets built at all. It aligns with the free, prior and informed consent standard in a way that most technology governance conspicuously does not, because the word that governance frameworks routinely underweight is prior. Consent obtained after deployment is not prior consent. A consultation convened to smooth the reception of a decision already taken is not consent in any meaningful sense. The whole argument is about procedural sequencing: who is in the room, and at what stage, is where Indigenous authority is either honoured or hollowed out.

What earlier involvement looks like in practice is beginning to be documented. A March 2026 paper by Dora Zhao and colleagues describes a series of co-design workshops with twenty-two public school educators in Hawai'i, convened around the educators' own concerns about cultural misrepresentation and bias in AI systems. Its argument is that auditing an AI system should be understood as a community-oriented process rather than the work of isolated individuals. The tools that emerged from those workshops were shaped by the participants' concerns because the participants were in the room while the tools were still taking shape, which is precisely the condition that late-stage consultation cannot reproduce.

The practical implications are concrete. A university library deciding whether to make its Indigenous collections available to an AI vendor would, under this logic, be obliged to consult the relevant communities before issuing the tender, not after signing it. A national museum contemplating a generative-AI interface to its holdings would need to bring the source communities into the design while fundamental choices, what is included, what is excluded, who governs access, remain open. Most institutions do the opposite, treating community consultation as a late-stage validation exercise, which is exactly the failure mode Malloy identifies.

Sovereignty as a Precondition, Not a Courtesy

The most ambitious of the recent contributions tries to move the whole conversation from ethics to architecture. A 2026 paper in AI & Society setting out a pluralistic, participatory approach to global AI governance argues that Indigenous knowledge systems and the right of Indigenous peoples to self-determination, underpinned by free, prior and informed consent and the CARE Principles, must be foundational to AI regulation rather than an optional addition to it. Its foundational move is to treat the right of a cultural community to exclude, limit, or set conditions on AI use of its knowledge not as an ethical enhancement but as a structural requirement of the system. In that framing, the ability of a community to say no is not a feature to be added if resources permit. It is a precondition of the system being legitimate at all. A knowledge system that cannot represent and enforce the exclusion is, on this account, defective by design, in the same way that a database without access controls would be considered defective.

This is the intellectual heart of what the Geneva advocates were reaching toward, and it inverts the default. The prevailing institutional posture treats tribal authority as something to be accommodated where feasible: a nice-to-have, honoured when a community is organised enough to demand it and convenient enough to grant. The sovereignty argument insists on the reverse. Authority over the knowledge is the starting condition. The burden is not on the community to prove why its knowledge should be withheld, but on the institution and the developer to establish that they have the right to use it at all. This is the same inversion that free, prior and informed consent performs in every other domain of Indigenous rights: consent is presumed absent until it is actively and legitimately given, rather than presumed present until someone objects.

The tradition this draws on is now substantial and cannot be dismissed as marginal. The Indigenous Protocol and Artificial Intelligence Position Paper, produced in 2020 out of workshops led by the scholar and artist Jason Edward Lewis and involving more than thirty researchers and artists, argued years ahead of the current wave that AI must be designed in partnership with specific communities rather than around assumed universal values, that Indigenous communities must retain full control over their own data, and that ethical scrutiny must extend across the entire development process. That work has since grown into Abundant Intelligences, an Indigenous-led international research programme rethinking what AI could be if it were placed inside Indigenous knowledge systems rather than extracting from them. UNESCO has moved in the same direction, releasing guidance on Indigenous data sovereignty in AI and a report on Indigenous people-centred artificial intelligence developed with communities across Latin America and the Caribbean, insisting that the digitisation of Indigenous data must guarantee self-determination, governance and free, prior and informed consent. The direction of travel in the normative literature is unmistakable. It has simply not yet been translated into binding obligation.

That translation is what the July 2026 session in Geneva was ultimately about. The advocates were not asking whether AI can be used on Indigenous knowledge, a question the archives and the models have already answered. They were asking whether the institutions holding these materials carry any enforceable duty to treat tribal authority as a precondition of deployment rather than a gesture of goodwill. On the current state of the law the answer is mostly no. There are principles without teeth, labels without reach, a treaty confined to patents and still short of the ratifications it needs, a repatriation statute confined to physical objects, and a copyright regime that measures the wrong thing. What there is not, yet, is a rule that says an archive must ask before it lets a model in.

The wax cylinders in Calais have travelled a long way from the horn Fewkes spoke into. They have been catalogued, restored, digitised, labelled and, in the Passamaquoddy case, partly returned. Whether the next generation of that material, the recordings not yet governed by a Traditional Knowledge Label, the collections not yet subject to a differential-access system, the languages not yet defended by a community strong enough to write its own licence, is treated as a training set or as a trust will depend on decisions that institutions are making right now, mostly without asking. The people who sang into the machine could not consent to what would be done with their voices. The least their descendants are owed is the standing to decide.

References

1. Malloy, Kerri J. “The Protection That Tribal Nations' Data Needs.” Governing, 9 June 2026. https://www.governing.com/management-and-administration/the-protection-that-tribal-nations-data-needs
2. Office of the United Nations High Commissioner for Human Rights. “Expert Mechanism on the Rights of Indigenous Peoples.” https://www.ohchr.org/en/hrc-subsidiaries/expert-mechanism-on-indigenous-peoples
3. Office of the United Nations High Commissioner for Human Rights. “Indigenous Peoples' rights in conflict situations and Artificial Intelligence on the agenda at Expert Mechanism session.” July 2026. https://www.ohchr.org/en/press-releases/2026/07/indigenous-peoples-rights-conflict-situations-and-artificial-intelligence
4. United Nations. “United Nations Declaration on the Rights of Indigenous Peoples,” Article 31, 2007. https://www.un.org/development/desa/indigenouspeoples/declaration-on-the-rights-of-indigenous-peoples.html
5. First Nations Information Governance Centre. “The First Nations Principles of OCAP.” https://fnigc.ca/ocap-training/
6. Carroll, S. R., et al. “The CARE Principles for Indigenous Data Governance.” Data Science Journal, 2020. https://datascience.codata.org/articles/10.5334/dsj-2020-043
7. Global Indigenous Data Alliance. “CARE Principles for Indigenous Data Governance.” https://www.gida-global.org/careprinciples
8. Local Contexts. “Traditional Knowledge (TK) Labels.” https://localcontexts.org/labels/traditional-knowledge-labels/
9. Mukurtu CMS. “About Mukurtu.” Center for Digital Scholarship and Curation, Washington State University. https://mukurtu.org/
10. Institute of Museum and Library Services. “Mukurtu Software Preserves Indigenous Digital Heritage.” https://www.imls.gov/grant-spotlights/mukurtu-software-preserves-indigenous-digital-heritage-through-technologies-today
11. Library of Congress. “Ancestral Voices — About this Collection.” https://www.loc.gov/collections/ancestral-voices/about-this-collection/
12. National Recording Preservation Board, Library of Congress. “Jesse Walter Fewkes field recordings of the Passamaquoddy Indians (1890).” https://www.loc.gov/static/programs/national-recording-preservation-board/documents/Fewkes-Passamaquoddy-Indians-field-recordings_Revak.pdf
13. NPR. “Historic Recordings Revitalize Language For Passamaquoddy Tribal Members,” 3 September 2019. https://www.npr.org/2019/09/03/748604202/historic-recordings-revitalize-language-for-passamaquoddy-tribal-members
14. Te Hiku Media. “Kaitiakitanga Licence and Kōrero Māori.” https://tehiku.nz/te-hiku-tech/
15. NVIDIA Blog. “Māori Speech AI Model Helps Preserve and Promote New Zealand Indigenous Language.” https://blogs.nvidia.com/blog/te-hiku-media-maori-speech-ai/
16. Perera, M., Vidanaarachchi, R., Chandrashekeran, S., Kennedy, M., Kennedy, B., and Halgamuge, S. “Indigenous peoples and artificial intelligence: A systematic review and future directions.” Big Data & Society, 2025. https://journals.sagepub.com/doi/10.1177/20539517251349170
17. Vidanaarachchi, Rajith, Perera, Maneesha, Chandrashekeran, Sangeetha, Kennedy, Brendan, and Halgamuge, Saman. “AI must be built with Indigenous Knowledges, not against them.” Pursuit, University of Melbourne, 3 July 2026. https://pursuit.unimelb.edu.au/articles/ai-must-be-built-with-indigenous-knowledges,-not-against-them
18. “Data colonialism and indigenous languages in AI: a critical review of existing initiatives and their struggles with data sovereignty.” AI & Society, 2026. https://link.springer.com/article/10.1007/s00146-026-03091-w
19. World Intellectual Property Organization. “Summary of the WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge (2024).” https://www.wipo.int/en/web/treaties/ip/gratk/summary_gratk
20. National Park Service. “Native American Graves Protection and Repatriation Act — Revised Regulations (2024).” https://www.nps.gov/subjects/nagpra/index.htm
21. Zhao, Dora, et al. “Whose Knowledge Counts? Co-Designing Community-Centered AI Auditing Tools with Educators in Hawai'i.” arXiv:2603.16646, March 2026. https://arxiv.org/abs/2603.16646
22. “Pluralistic AI governance: Indigenous knowledge and the right of Indigenous peoples to self-determination.” AI & Society, 2026. https://link.springer.com/article/10.1007/s00146-026-02938-6
23. Lewis, Jason Edward (ed.). “Indigenous Protocol and Artificial Intelligence Position Paper.” Indigenous AI Working Group and CIFAR, 2020. https://spectrum.library.concordia.ca/986506/
24. Lewis, J. E., Whaanga, H., and Yolgörmez, C. “Abundant intelligences: placing AI within Indigenous knowledge frameworks.” AI & Society, 2024. https://link.springer.com/article/10.1007/s00146-024-02099-4
25. UNESCO. “New report and guidelines for indigenous data sovereignty in artificial intelligence developments.” Global AI Ethics and Governance Observatory. https://www.unesco.org/ethics-ai/en/articles/new-report-and-guidelines-indigenous-data-sovereignty-artificial-intelligence-developments

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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