AI Has An Anglophone Bias—Which Is Why Global Content Owners Need To Act Now
In the sprawling algorithmic architecture of artificial intelligence, there's a fundamental truth we keep ignoring: AI is only as good as the data it’s trained on. And right now, that data looks disturbingly homogenous.
It is a subtle but powerful replay of colonisation and Western dominance, dressed in innovation’s language. AI models powering everything from virtual assistants to media recommendation engines are fed mostly with Anglo-American datasets and hence reflecting a narrow band of cultural expression, linguistic nuance, and societal perspective. It has now created a majority of AI algorithms with built-in bias - not by intent, but by omission. Systems trained on the same stories, the same accents, the same aesthetic logics. And that is neither ethical, nor sustainable.
This is where content owners - especially those holding vast international, regional, and non-English libraries - must recognize the urgency and the opportunity. AI needs your content. Not for another streaming service and its entertainment value. We need your content so that the world can learn, see, hear and partake in the richness of our stories and the complexity of our earth. Our globe is more than one nuance of how to view it – it is a diverse and rich landscape; and this must be reflected in the video data on which AI is trained these days.
And yes, you can and should be paid for it.
From Archives to Algorithms: The New Licensing Frontier
AI content licensing is not science fiction anymore and lately I have worked more with content owners to make the impact on algorithm training with their video data a reality. Because developers are buying high-quality video, audio, and image data to train machine learning systems on everything from visual recognition to emotional inference. What these models learn is based on the patterns they observe in the content: how faces move, how people speak, how social dynamics play out on screen.
Crucially, this material is not published or made public. It functions like a textbook for machines: input, not output.
For rights holders, this is a unique monetization pathway. It breathes new financial life into underutilized or archival content, without competing with existing distribution channels. We're talking about thousands of hours of movies, documentaries, dramas, soap operas, sports, music, and children’s content just sitting in digital vaults, waiting to be useful again.
But there is a catch: the licensing window is shrinking. As the AI race accelerates, early suppliers are being rewarded with premium prices. Once enough material has been acquired, the pricing will inevitably fall, and latecomers will find themselves negotiating in a buyer’s market. And the algorithm might forever perpetuate its own bias – unless you step in.
Beyond Revenue: The Ethical Imperative
Yes, this is a business opportunity. But it is also an ethical obligation.
Because the real threat isn’t AI replacing humans. The threat is in AI replicating only a narrow slice of them. When algorithms trained on predominantly Western media are used globally (for instance, to recommend shows, drive hiring decisions, even influence policy) we risk amplifying a distorted view of what humanity looks like, sounds like, and values.
If you're a content owner sitting on years of programming from the Philippines, Brazil, Kenya, South Korea, or Eastern Europe, you are sitting on more than on a data asset. You are the key to creating an algorithm antidote, you are helping to tipping the balance.
Participating in AI licensing means actively shaping the future of machine intelligence. It’s about taking responsibility for what kind of “intelligence” we are cultivating.
As you know me, I have always made one thing clear to the world: diversity, at large, and now in data is not a nice-to-have. It's the only way to train systems that don’t just reflect existing inequalities and to begin to correct them.
The Bias That Hides in the Code
This is where the conversation becomes urgent. Algorithmic bias isn’t just about a chatbot misunderstanding a dialect. It's about automated decisions reflecting and reinforcing societal gaps: be it through facial recognition that fails on darker skin tones, language models that erase regional idioms, or recommendation engines that systematically under-represent local content.
AI systems are like children: they learn from what they’re exposed to. If we only feed them a diet of American sitcoms, Hollywood thrillers, and British documentaries, we shouldn't be surprised when they speak with a monocultural accent.
As I have long argued, the global media industry must stop chasing Silicon Valley’s shadow and start asserting its own narrative sovereignty. This is precisely that moment. Not by evangelizing “diversity,” but by betting on it – literally with your content and revenue. By licensing content that expands the cognitive boundaries of machine learning.
Licensing as Leadership
I am not doing a call for charity sake here. It’s a call for leadership. I am calling us all to reclaim relevance in an era where data has become the raw material of power.
TV executives, film libraries, national broadcasters and everyone who owns video content, this is your moment to get involved, shape the rules, and set the standards. Waiting for a few years to see how things pan out are not an option. Action is needed immediately. Take it now.
Because once the training phase is over, the models will be baked. And then, they will reflect what we fed them- or failed to.
What You Can Do
Audit your archives: Identify content that is original, high-quality, and diverse in culture, language, age group, or genre.
Engage ethical intermediaries: Work with licensing professionals who understand both traditional media rights and the AI training landscape. I am gaining more and more experience on being a reliable navigator in this new terrain. So reach out, if interested.
Negotiate safeguards: Ensure your content is not reused outside of agreed parameters. You are supplying data files and not distribution licenses for copyright use.
Think long-term: This is not a one-time check only. Together with a trusted partner, I build a system to contribute to a more balanced AI ecosystem. And yes, you’ll likely be asked for more content again.
Don’t Miss the Train
It’s not a question of whether AI will be part of the media industry, because we know it already is. The real question is: whose content will define it?
If we do nothing, the usual suspects will dominate. Again. If we act now, global storytellers can finally have a voice: not just in viewers’ homes, but in the very code that will shape tomorrow’s cultural logic.
This is an invitation to step up and to help train the machines to see us all around the world. And in the process, make money while doing good. That’s a business model worth exporting.
To learn more about how you can take part in this important initiative, contact Christian Knaebel directly.
