Ethics vs. Algorithms: The Fight for Fair AI

As generative AI becomes more deeply embedded in decision-making processes across industries, concerns over bias, fairness, and accountability are intensifying. From recruitment tools that reinforce existing inequalities to facial recognition systems that struggle with diverse populations, AI’s potential for harm is as significant as its promise for progress.

This session will explore the ongoing challenge of mitigating bias in generative AI, examining the latest advancements in algorithmic fairness, synthetic data generation, and regulatory frameworks. Experts will discuss whether true neutrality in AI is achievable—or if bias is an inevitable byproduct of training models on real-world data. How can companies balance innovation with ethical responsibility? What role do policymakers, researchers, and AI developers play in shaping a more equitable future for AI?