I have already written about delegating imagination and creativity to technology and what is at stake when we do so. The weakness isn’t just in the tech, it’s in us.
AI simply reflects the values, gaps, and biases of the data we feed it. Without care, it can rewrite or flatten history, rather than preserve it with integrity.
I’d like for us to pause a minute and stop worrying about AI replacing this or that and instead ask a different questions: what data it’s learning from and how that shapes the output?
We need to particularly pay attention to source bias and historical erasure.
AI models are trained on vast amounts of data pulled from the internet, books, articles, and other digital archives. But this data often reflects:
Eurocentric or colonial perspectives, especially in history and culture.
Omissions of marginalised voices, either because those stories were never recorded, or they were actively suppressed.
Mainstream overrepresentation, where dominant narratives drown out alternative or indigenous ones.
This is not specific or unique to AI. It is already part of our “behaviours” and the culture of grabbing attention at any cost. We use it in sensational titles, often not grounded in fact check, we manufacture or appropriate stories for likes or attention, and so on… AI reflects only what’s available (or popular). When this is the only source, it can reinforce historical erasure or present biased “truths” as neutral fact.
Let’s do not forget the current and ramping antiscientific trends and the dangers of pseudoscience spreading misinformation or disinformation when not carefully filtered or when not understood.
In this context AI can become a megaphone for misinformation, not a filter for truth.
Are we, by using AI, amplifying exclusion, plagiarising under the guise of “style”? And, by doing this, are we contributing to:
Underrepresentation of non-Western, LGBTQ+, disabled, or BIPOC voices.
Cultural appropriation risks, where styles or narratives are used out of context or without consent.
A tendency for AI to default to “norms” that exclude many people’s realities.
I do not have a definite unswear and, I know that technology can only be “as human as we are capable to be.” In this case, it can only be as inclusive, respectful, caring as we can be.
So, whenever you are using AI, as we all do to a certain extent, or reading anything as matter of fact, please check your sources. Include diverse, representative, and verified sources.
We are not simply the passive recipient of AI. We can train it to recognise context and avoid appropriation or erasure.
In whatever you do, be mindful not to erase history, not to amplify harm, and do reflect inclusive and responsible knowledge.
How? Simply asking what stories are being told, and who’s missing?
Become curious of which communities, languages, regions, and perspectives are underrepresented or misrepresented. Intentionally bring in oral histories, indigenous knowledge systems, queer archives, disability justice writing, non-Western scientific perspectives, etc.
Don’t extract sacred or communal knowledge without invitation.
AI should assist, not replace, our judgment. We can always, and more and more need to: review to evaluate any model; add cultural context before deployment, especially in educational, legal, or medical AI use.
Can we start focusing on pluralism and not rely solely on objectivity?
There are so many technical and regulatory requirements we need to learn and consider when we are being lured by convenience. A question I always ask myself is: who is paying for my convenience?
Cultural awareness, inclusion, curiosity, deep reflection become essential to question and shape the use of AI.
We have a great opportunity, not just a challenge, to embody all these qualities, and become wholeheartedly human.
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