How Human Knowledge Powers AI: Data Quality, Bias & Blockchain Payments | Rowan Stone

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Rowan Stone, CEO of Sapien, to explore how human knowledge powers the next generation of artificial intelligence. Together, they dive into the importance of high-quality data, the challenge of bias in AI, the role of blockchain payments in rewarding contributors, and the future balance between human input and machine learning.Rowan shares his journey from energy executive to crypto entrepreneur, building early DeFi protocols, co-creating Coinbase’s Layer 2, and eventually launching Sapien, a decentralized data platform that connects enterprises with a global network of contributors. He explains why data is the true bottleneck in AI, how Sapien incentivizes contributors from everyday people to doctors and engineers, and why human oversight remains essential even as AI becomes more advanced.Rowan Stone is a seasoned entrepreneur whose career spans energy, crypto, and AI. He co-founded multiple ventures in the blockchain space, including projects acquired by Coinbase, where he spent three years leading initiatives around stablecoins, tokenization, and Layer 2 solutions. Today, as CEO of Sapien, he focuses on sourcing and structuring human data for specialized AI models used in fields like autonomous vehicles, robotics, and healthcare. His mission is to democratize access to AI’s growth by enabling people everywhere to monetize their knowledge while ensuring enterprises get the high-quality data they need.Support This PodcastTo support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/Takeaways* AI is only as smart as the quality of data it’s fed.* The true bottleneck in AI is data, not algorithms or compute.* Everyone’s knowledge, from experts to everyday people, has value for training AI.* Global diversity in data contributors is key to reducing bias in AI.* Politically correct outputs can still be factually wrong, as seen in the Viking ship AI fail.* AI can enhance doctors’ diagnostic power while creating new income opportunities.* Self-driving cars still struggle because training is highly city-specific.* Incentive systems like staking and slashing help ensure high-quality data for AI.* Stablecoin payments enable instant, global compensation for AI contributors.* Human input will always be needed to handle real-world randomness and context.Timestamps00:00 Introduction01:14 From Energy to Crypto: A Personal Journey05:56 Understanding Sapien: The Decentralized Data Foundry10:33 Quality of AI Data: What Does It Mean?12:17 Contributors and Their Role in Data Annotation14:13 Scaling Contributor Networks and Quality Control20:47 Addressing Bias in AI Data25:31 Expert Contributors: Recruitment and Qualification Process29:28 AI as a Diagnostic Tool for Healthcare32:03 Challenges in Autonomous Vehicle Development35:01 The Intersection of Crypto and AI39:32 The Future of Human Expertise in AI43:39 The Role of Creativity in AI48:15 Getting Started with AI Model TrainingConnect with Rowan* Website: https://earn.sapien.io/ * LinkedIn: https://www.linkedin.com/in/rowan-stone/ * X: https://x.com/rowanrk6 * Other: https://www.sapien.io/ Connect with Vit* Website: https://vitlyoshin.com/contact/ * LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin Vit’s Projects* Podcast: https://www.anhourofinnovation.com/ * AI Assistant to build apps: https://appforgelab.com/

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