Ep26: The #1 Habit of GREAT AI Teams - How to Build AI You Can TRUST

AI is everywhere, but Responsible AI and AI ethics have never mattered more. How can teams ensure they build trustworthy AI systems free of dangerous AI bias and problematic algorithmic bias? In this episode of the Data Neighbor Podcast, we're joined by Will Landecker, founder of Accountable Algorithm, to dive deep into AI safety, ethical AI, and best practices for responsible development.This episode explores foundational topics, including an introduction to Responsible AI, core Responsible AI principles, and practical strategies for addressing LLM hallucination, evaluating LLMs, and managing human-AI interaction. Learn what AI transparency, AI accountability, and AI fairness really mean, and how they impact your business and users.Will shares actionable insights on bias mitigation in AI, building fair AI models, and achieving AI explainability. We'll uncover the hidden AI blind spots that damage trust, discuss essential AI governance methods, and reveal tactics for effective AI risk management. From ethical machine learning frameworks to the latest strategies in detecting and preventing AI discrimination, this episode covers everything you need for developing truly ethical products.If you're a data scientist, product manager, engineer, or executive interested in the risks and rewards of AI, this is your essential guide to the complex intersection of AI and society. Discover how responsible practices aren't just good ethics—they're good business.Connect with Will Landecker:Website: https://accountablealgorithm.com/LinkedIn: https://www.linkedin.com/in/will-landecker-88b2a788/Connect with Shane, Sravya, and Hai (let us know which platform sent you!):Shane Butler: https://linkedin.openinapp.co/b02feSravya Madipalli: https://linkedin.openinapp.co/9be8cHai Guan: https://linkedin.openinapp.co/4qi1r#ai #responsibleai #aibias #aigovernance #aiethics #ethicalai #algorithmicbias #llmhallucination #aifairness #aisafety #aitransparency #aiexplainability #ethicalmachinelearning #biasmitigation #aiaccountability #aiandsociety #humanaiinteraction #trustworthyai #aiblindspots #risksai #machinelearning #aialignment #dataneighbor