Explainability and transparency are critical for fostering trust and accountability in autonomous agents, yet achieving these qualities in complex systems presents significant technical hurdles. Panelists will explore the latest advancements in making agent decision-making processes interpretable, discussing methods for ensuring transparency, addressing potential biases, and building systems that provide actionable insights while maintaining high performance and autonomy.