Welcome to "AI with Shaily," hosted by Shailendra Kumar, where we dive deep into the fascinating world of artificial intelligence with a focus on what truly matters 🤖✨. In this episode, Shaily explores a groundbreaking shift in how experts are addressing bias in large language models—the powerful AI systems that chat, write, and even create art for us 🎨💬.

Traditionally, bias in AI has been seen as a problem stemming from skewed data or unfair algorithms. But Shaily introduces a fresh perspective: the real challenge lies much deeper, at the core of AI’s very foundations—the *ontological frameworks* that shape these models’ understanding of the world 🌍🔍. Ontology here means the AI’s worldview, the basic assumptions about what exists and how things connect.

At the April 2025 CHI Conference, Stanford researchers demonstrated this beautifully. They asked a language model to draw a "tree," but surprisingly, the AI’s initial images lacked roots 🌳❌. Why? Because the AI’s ontological lens—its conceptual and cultural framing of a "tree"—didn’t include roots as essential. Only when prompted with a phrase like “everything in the world is connected” did the roots appear, revealing how the AI’s knowledge is limited by inherited worldviews 🌐🌱.

Shaily reflects on his own journey, admitting that early in his AI training days, his personal perspective unknowingly influenced model design. It’s like teaching someone a language but only sharing your hometown slang—this narrows what they can understand or "see" 🗣️🏡. Now, it’s clear that AI creators must critically examine their own assumptions to help models develop richer, more diverse perspectives.

Experts like James Landay emphasize that tackling bias requires going beyond fixing “value bias.” Instead, we need to scrutinize these ontological assumptions embedded throughout the AI lifecycle—from data collection to output generation 🧠🔄. Imagine AI systems that can understand multiple cultural viewpoints, recognize interconnectedness, and adapt flexibly—that’s the exciting potential here 🌏🤝.

Emerging research is combining ontology learning with natural language processing to analyze bias in media and other domains. This could lead to scalable, culturally sensitive AI tools that don’t just patch bias superficially but grasp its deep roots 🌱📊.

Shaily leaves listeners with a thought-provoking question: If AI begins to think with a more inclusive, interconnected worldview, how might that transform its interactions with us and the decisions it influences? Could it help bridge cultural divides or reveal insights previously unseen? 🤔🌈

For AI enthusiasts, Shaily offers a bonus tip: Always question the underlying assumptions—the invisible lenses through which AI interprets the world. Success isn’t just about feeding AI more data; it’s about building *better* frameworks 🛠️🔍.

Quoting philosopher Alfred North Whitehead, Shaily reminds us, “It is the business of the future to be dangerous,” but with thoughtful design, AI can also be wonderfully transformative 🚀🌟.

Stay connected with Shaily on YouTube, Twitter, LinkedIn, and Medium (links in the show notes), and don’t forget to subscribe for more insights into AI’s evolving landscape. Shaily invites you to share your thoughts on this ontological approach to AI bias in the comments—let’s keep the conversation going! 💬📲

Thanks for tuning into AI with Shaily, where curiosity meets clarity. Until next time, keep questioning and keep innovating! 🙌🤖✨

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