{"id":166,"date":"2026-01-05T09:52:29","date_gmt":"2026-01-05T09:52:29","guid":{"rendered":"https:\/\/yebbo.com\/ethiodiego\/?p=166"},"modified":"2026-01-06T05:41:10","modified_gmt":"2026-01-06T05:41:10","slug":"ai-gap-how-artificial-intelligence-is-repeating-the-mistakes-of-the-past","status":"publish","type":"post","link":"http:\/\/yebbo.com\/ethiodiego\/ai-gap-how-artificial-intelligence-is-repeating-the-mistakes-of-the-past\/","title":{"rendered":"AI Gap: How Artificial Intelligence Is Repeating the Mistakes of the Past"},"content":{"rendered":"\n
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“AI Gap: How Artificial Intelligence Is Repeating the Mistakes of the Past”
By Amde Mitiku, Senior Localization Engineer & Founder at Ethiotrans<\/p>\n<\/div>\n\n\n\n

In the late 1990s, as the world was transitioning from analog to digital, I wrote to Bill Gates to highlight a major flaw in Microsoft\u2019s software: the near-total neglect of non-Latin languages. At the time, many communities were forced to invent keyboard hacks and glyph substitutions just to communicate in their native tongues. It wasn\u2019t until Windows NT and later Windows XP \u2014 with the introduction of Unicode \u2014 that real progress was made. But this came after decades of technological exclusion.
Now, nearly 30 years later, we are witnessing history repeat itself.
The New Divide: The \u201cAI Gap\u201d
Artificial Intelligence is becoming an everyday tool \u2014 shaping education, communication, business, and governance. But instead of leveling the playing field, it\u2019s creating a new kind of inequality: an AI Gap \u2014 a divide between the empowered and the excluded, the paid and the free, the represented and the invisible.
Here\u2019s how.<\/p>\n\n\n\n

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1. Two Classes of AI Users: Paid vs. Free
Many AI tools now offer different response quality based on user payment tiers. Free users receive shorter, less detailed responses. Paid users receive deeper insights, better formatting, and more timely results.
This is creating a knowledge inequality. If information access and quality depend on your ability to pay, then AI is not democratizing knowledge \u2014 it\u2019s monetizing it.<\/p>\n\n\n\n

2. Built-in Bias: Whose Voices Count?
Ask a simple question like \u201cList countries around the world,\u201d and you\u2019ll likely see:
USA, UK, Germany, France, Australia…
But why this order?
Is it alphabetical? No.
Based on population? No.
GDP or military power? Possibly.
Developer bias? Most likely.
This is not a neutral list \u2014 it reflects the worldview of those who built or trained the system. This subtle bias shows up everywhere \u2014 from political summaries to language detection, from cultural references to historical prioritization.<\/p>\n\n\n\n

3. The Developer\u2019s Face is the AI\u2019s Face
AI is not just an intelligence. It\u2019s a mirror.
Behind every AI model is a developer, a data scientist, a curator. If that person (or company) is biased \u2014 intentionally or not \u2014 so is the AI.
AI has two faces: the algorithm, and the person behind it.
If inclusion and fairness aren’t core values in its training, exclusion becomes the default behavior.<\/p>\n\n\n\n

4. The Return of the Language Bottleneck
Today\u2019s AI systems excel in European FIGS languages (French, Italian, German, Spanish) and in dominant Asian languages like Chinese, Japanese, and Korean. This follows the same pattern we saw in early computing.
Languages from Africa, the Middle East, Southeast Asia, and Indigenous communities are still afterthoughts \u2014 either mistranslated, misunderstood, or totally unsupported.
This is disturbingly similar to the days before Unicode \u2014 when only 128 characters could fit on a keyboard, and global scripts were excluded by design.<\/p>\n\n\n\n

5. Global Means Everyone \u2014 Not Just the Majority
If AI is going to be a global tool, it must support global diversity:
Languages (written, spoken, and minority dialects)
Cultures (belief systems, expressions, customs)
Histories (not just Western-centric ones)
Politics and narratives (without reinforcing colonial frameworks)
As someone who\u2019s worked on language inclusion for decades, I can say:<\/p>\n\n\n\n

AI is not there yet. And unless we act, it will never get there.AI<\/a> isn\u2019t just a new technology\u2014it\u2019s a reflection of the past, coded into silicon. In many ways, AI is inheriting the historical biases and power structures that have long shaped global technology and knowledge systems. One stark example is the linguistic and cultural imbalance baked into many AI models today.<\/p>\n\n\n\n

Much like the early days of computing, when Western companies prioritized FIGS languages (French, Italian, German, Spanish) and left billions without proper digital representation, today\u2019s AI models show a similar trend. Back then, users of African, Middle Eastern, South Asian, and Indigenous languages had to create custom glyphs and keyboard layouts just to communicate digitally. It took decades and the introduction of Unicode for these languages to gain equal footing. Now, history may be repeating itse…<\/p>\n\n\n\n

As a senior localization engineer who wrote to Microsoft in 1999 about their neglect of non-Latin scripts, I\u2019ve watched this pattern unfold firsthand. It took more than 30 years for platforms like Windows to begin offering proper support. Now, AI threatens to replicate the same bottleneck, where access and representation are determined by economic and linguistic dominance\u2014not inclusion.<\/p>\n\n\n\n

In other words:
AI is inheriting the mistakes of the past.
It is unknowingly driven by colonial logic\u2014favoring the powerful, the rich, and the dominant narratives\u2014while marginalizing voices that fall outside its training data.<\/p>\n\n\n\n

AI is the two-faced coin of its creator and its dataset. If either the developer or the data miner is biased, the entire system becomes biased. It is not neutral by default.<\/p>\n\n\n\n

Until developers, data curators, and AI companies actively correct these imbalances, we are not building truly global intelligence\u2014we are simply reinforcing the old hierarchy with a new, shinier interface.<\/p>\n\n\n\n

THE AI GAP: TWO WORLDS, ONE SYSTEM<\/p>\n\n\n\n

AI isn\u2019t just a new technology\u2014it\u2019s a reflection of the past, coded into silicon. In many ways, AI is inheriting the historical biases and power structures that have long shaped global technology and knowledge systems. One stark example is the linguistic and cultural imbalance baked into many AI models today.<\/p>\n\n\n\n

Much like the early days of computing, when Western companies prioritized FIGS languages (French, Italian, German, Spanish) and left billions without proper digital representation, today\u2019s AI models show a similar trend. Back then, users of African, Middle Eastern, South Asian, and Indigenous languages had to create custom glyphs and keyboard layouts just to communicate digitally. It took decades and the introduction of Unicode for these languages to gain equal footing. Now, history may be repeating itse…<\/p>\n\n\n\n

As a senior localization engineer who wrote to Microsoft in 1999 about their neglect of non-Latin scripts, I\u2019ve watched this pattern unfold firsthand. It took more than 30 years for platforms like Windows to begin offering proper support. Now, AI threatens to replicate the same bottleneck, where access and representation are determined by economic and linguistic dominance\u2014not inclusion.<\/p>\n\n\n\n

In other words:
AI is inheriting the mistakes of the past.
It is unknowingly driven by colonial logic\u2014favoring the powerful, the rich, and the dominant narratives\u2014while marginalizing voices that fall outside its training data.<\/p>\n\n\n\n

AI is the two-faced coin of its creator and its dataset. If either the developer or the data miner is biased, the entire system becomes biased. It is not neutral by default.<\/p>\n\n\n\n

Until developers, data curators, and AI companies actively correct these imbalances, we are not building truly global intelligence\u2014we are simply reinforcing the old hierarchy with a new, shinier interface.<\/p>\n\n\n\n

Final Thought: The Choice Is Ours
AI is not destiny. It’s a design.
Developers, companies, and communities have a responsibility to ensure the next generation of technology doesn\u2019t replicate the exclusion of the past. If we let market forces and convenience dictate everything, the AI Gap will grow wider than ever.
Let\u2019s learn from history, not repeat it<\/p>\n","protected":false},"excerpt":{"rendered":"

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