About this episode

Anoop Mishra discusses the complexities of measuring fairness in AI and its implications for organizations.

Many assume that if AI produces an answer quickly, it must be accurate and unbiased. But in this conversation, Anoop Mishra explains why fairness in AI is far more complex than most people realize and why measuring it may be one of the most important challenges facing organizations today. As an Applied AI and Responsible AI scientist, Anoop works at the intersection of technology, human behavior, ethics, and measurement science. His research focuses on helping organizations understand how fairness is perceived, measured, and managed throughout the AI development lifecycle. In this episode, we discuss: • Why fairness in AI is a socio-technical challenge, not just a technical one • How developer bias, user perspectives, and organizational priorities can shape AI outcomes • Why measuring fairness may be the key to building trustworthy AI systems • The challenges organizations face when deciding whether an AI system is ready for deployment • Anoop's work developing FairFlow, a framework designed to help teams evaluate AI readiness and stakeholder alignment This conversation is especially valuable for business leaders, technology professionals, researchers, policymakers, and anyone…

People in this episode

Guest: Anoop Mishra

Topics covered

• fairness in AI
• socio-technical challenges
• developer bias
• AI outcomes
• trustworthy AI systems
• AI readiness
• stakeholder alignment

Keywords

• AI fairness
• measurement science
• ethical AI
• organizational priorities
• FairFlow framework
• AI deployment
• responsible AI

Mentioned in this episode

Organizations: Nebraska Tech Collaborative

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