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Ten Languages, One House, and No Way to Connect Them: Sheriff Issaka on Building the Bridge Himself

Connected Conversations  | 

Sheriff Issaka on Building the Bridge Himself

Sheriff Issaka grew up surrounded by languages, then watched the people he loved most be unable to reach each other. In this episode of Connected Conversations, he tells Elena Petrova why he stopped waiting for a bridge and built one.

A house full of languages

Sheriff Issaka grew up in Ghana in a home where, by his own count, ten languages moved freely. He spoke one language with his mother, another with his father, a different one with his siblings, and still others with neighbors and at school. He did not think much of it at the time. Language was simply the air he breathed, and moving between so many of them felt ordinary.

The turning point came after he arrived in the United States for college. A close friend from China came to visit him in Ghana. They ate, played soccer in the streets, and had a wonderful time. But Sheriff kept noticing something. His friend spoke a few languages. The people in Sheriff's own circle spoke seven, nine, sometimes more. And between them, across a dozen languages in one room, there was almost no way to connect.

That gap is where the whole story begins. Sheriff could have accepted it as the way things are. Instead he decided to build the thing that was missing.

What it costs to be "low resource"

In technology, a language is called "low resource" when there is not enough digital text and speech for modern systems to learn from it. It sounds like a technical label. Sheriff's point is that it is really a human one.

If the systems that increasingly decide things, what you can access, how you are understood, whether a form even recognizes your name, cannot work in your language, then you are quietly left out of the future those systems are building. As Sheriff frames it, the real question is not about technology at all. It is about who gets to be understood, and who does not.

His answer has become one of the largest efforts of its kind. Through the African Languages Lab and his model MansaLLM, Sheriff and his team have built what he describes as the largest multimodal collection for African languages, with datasets and pipelines spanning roughly seventy languages and about thirty already in production. The guiding line, in his words, is "AI for Africans, by Africans."

Language goes to the heart

Sheriff reaches for a line he attributes to Nelson Mandela, noting he is paraphrasing. Speak to someone in a language they understand, and it goes to their head. Speak to them in their own language, and it goes to their heart.

That is the difference between being processed and being understood. It is why, for Sheriff, language is not a feature to be added later. It is the thing that decides whether a person is included at all. And it is why he is impatient with the idea that inclusion is something communities should wait to be granted. His phrase for it is simple: we don't wait for inclusion, we build it.

Go global, stay local

There is a warmer, funnier version of the same lesson, and it is a useful one for anyone working across cultures. Sheriff tells the story of three friends from three different countries, each one completely certain that a particular chocolate drink, Milo, was their own national beverage. Same product, three homes, three sets of people who felt it belonged to them.

The lesson underneath the laugh is serious. Technology dropped into a community without being adapted to it tends to fail, or worse, to cause harm. Localization is not translation. It is the difference between a tool that fits a community's actual life and one that ignores it. Outsiders keep trying to enter new markets and keep getting this wrong. The ones who succeed find trusted local partners and build with the community rather than for it.

Who is in the room

All of this builds to the challenge Sheriff leaves with every listener. When the next major AI systems are announced, he says, look closely at who is standing in the room announcing them. Ask how many of the people these systems will affect are actually represented among the people building them.

His conviction, and it is the through-line of the whole conversation, is that the communities least represented in these technologies are often the ones most affected by them. A system that cannot recognize a face, or that quietly decides someone's credit or access to care, is not abstract. It shapes real lives. The fix he argues for is not complicated to say, even if it is hard to do. Put people back at the center of what we build.

For the leaders listening

Sheriff's advice for anyone who wants to start is refreshingly plain. You are never too small to make a difference. Find the hardest problem in something you actually care about, start small, and move quickly. If you want to work across a new market or community, find people you can trust and build alongside them.

He closes with the question the show asks every guest: what conversation do more people need to be having right now? His answer is that we should be talking a lot more about people, and a lot less about technology for its own sake.

If you lead a team, serve a community, or build anything that other people have to live inside, this one is worth your time.

Listen to Episode 55 of Connected Conversations, hosted by Elena Petrova, Founder and CEO of Ad Astra, Inc. and AdAstraConnect.

Connected Conversations is produced by Ad Astra, Inc. 

You can watch/listen to this episode here:
🔴 YouTube: https://www.youtube.com/watch?v=YrYxcBTVQMg
🟢 Spotify: https://shorturl.at/J666g
⚫ Apple Podcast: https://shorturl.at/968Mc
🔵 Amazon Music: https://shorturl.at/jZiQJ

 

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Table of Contents The Evolution of AI Translation Where AI Translation Works Well Where AI Still Struggles Human Translators: The Gold Standard AI + Human Collaboration: The Future of Translation Real-World Industries Impacted Summary: Key Takeaways Final Thoughts The Promise and Pitfalls of AI in Translation From Google Translate to ChatGPT, AI translation tools are reshaping how we communicate across languages. They’re fast, affordable, and increasingly accessible, but are they truly ready to replace human translators? In fields like law, healthcare, education, and government, precision is non-negotiable. Even a single mistranslated clause or phrase can change outcomes, compliance status, or lives. Let’s explore where AI translation vs human translation currently stands, and why professional linguists remain indispensable for accuracy, ethics, and trust. 1. The Evolution of AI Translation Machine translation has evolved from rule-based systems in the 1950s to today’s neural machine translation (NMT) powered by deep learning. Modern engines like DeepL, Google Translate, and Microsoft Translator can interpret context better than ever, analyzing massive datasets to predict meaning. Yet, no matter how sophisticated, AI translation still depends on patterns, not understanding. As the Common Sense Advisory (CSA Research) notes, “AI can replicate language structures, but it cannot replicate intent.” 2. Where AI Translation Works Well AI translation shines when speed and scalability matter more than nuance. 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Real-World Industries Impacted AI’s integration into translation workflows varies by sector: Industry AI Strengths Human Necessities Healthcare Fast data processing for patient education Clinical accuracy, HIPAA compliance Legal Drafting routine documents Court-certified accuracy, liability prevention Education Localising e-learning modules Cultural adaptation, clarity for parents & students Government Automating public notices Compliance with Title VI, confidentiality Marketing Translating ads for quick testing Emotional tone, brand voice, idiom accuracy Across sectors, the hybrid model ensures efficiency and reliability - especially where precision equals protection. 7. Summary: Key Takeaways AI translation is fast, scalable, and cost-efficient—perfect for routine or large-scale projects. Human translation remains essential when meaning, compliance, or emotion are at stake. 💡 Key takeaway: AI is a powerful assistant, but it’s not a replacement. The most effective approach blends machine efficiency with human expertise, ensuring your message is not just translated, but truly understood. Final Thoughts - Ad Astra’s Approach to Translation in the AI Era At Ad Astra, we combine advanced AI translation technology with expert human linguists to deliver accuracy, security, and cultural precision. Our translation workflows ensure: Compliance with data privacy laws (HIPAA, FERPA, GDPR) Secure, encrypted platforms for document handling Native-level quality assurance by certified translators Whether you’re a hospital, law firm, school, or SaaS company, you can trust Ad Astra for translation that connects - not confuses. 📩 Contact us today to explore hybrid translation solutions that keep your communications human, accurate, and compliant.

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