AI is transforming pharma and healthcare, from accelerating drug discovery to improving diagnostics. With this power comes a critical challenge: ensuring AI-driven decisions are fair, unbiased, and trustworthy. Studies show that biased AI models in healthcare have resulted in black patients receiving nearly 20% less care than white patients with the same health conditions. Without proactive measures, AI risks perpetuating disparities rather than closing the gaps in healthcare access and treatment.

Join our panel discussion on Responsible AI to explore practical solutions for building fair, accountable AI systems.

Key discussion points include:

• Transparency & Explainability: Best practices for making AI decisions interpretable and accountable to clinicians, regulators, and patients.
• Inclusive AI Development: Ensuring AI models are trained on diverse, representative datasets to improve healthcare equity.
• Building Public & Physician Trust: Strategies for increasing confidence in AI-driven decisions and demonstrating responsible AI leadership.