When Bias Goes Viral: Protecting Your Brand from Biases in Generative AI

Bias in generative AI is no longer an academic concern, it’s a real-world risk to brand trust, product integrity, and social responsibility. This session presents the BEATS framework, a statistically rigorous evaluation methodology, designed to uncover and assess latent biases in LLM outputs and a AI governance framework to proactively identify and mitigate risky AI generated outputs.

Attendees will gain insights into:

• Detecting and quantifying bias across demographic and contextual dimensions
• Evaluating fairness and ethical alignment in model responses
• Embedding bias monitoring and ethical guardrails throughout the AI lifecycle
• Implementing governance strategies for risk mitigation, compliance, and responsible AI deployment

This session will deliver practical, research informed strategies to help organizations future-proof their AI systems while preserving fairness, equity, and brand integrity.

Speakers: Alok Abhishek, researcher; Tushar Bandopadhyay, KronML

Attend in person, or watch on online via Zoom or YouTube