Navigating the Challenges of Responsible AI in Pharmaceutical Industries
Understanding Responsible AI in Pharma
Responsible AI is essential for success in today's tech-driven landscape. AI systems must be developed ethically while respecting privacy and minimizing bias. In the pharmaceutical sector, Sun Pharma is leading this effort, showcasing how AI governance can transform the industry.
AI Governance and Adoption Challenges
Even with the advantages AI brings, the journey towards responsible AI is fraught with obstacles. Dheeraj Sinha from Sun Pharma highlights the fragmented nature of solutions and complex regulations as key barriers.
- AI Governance: Establishing a council with compliance and legal experts.
- Data Mesh Architecture: Ensuring data lineage and governance for robust AI systems.
Strategizing for Responsible AI Implementation
To implement responsible AI, organizations must focus on both cultural change and structured governance. Rishi Aurora from IBM recommends combining automated tools and ethics boards for a comprehensive approach.
- Establish clear metrics for measuring AI success.
- Foster a culture of digital transformation within the company.
This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.