Here's the final chapter of the World Health Organization's (WHO) document, "Benefits and Risks of Using Artificial Intelligence for Pharmaceutical Development and Delivery: Challenges in Governance." This chapter is crucial as it highlights the importance of data access in the pharmaceutical sector. It also discusses the role of both the public and private sectors. And it outlines essential next steps for effective governance.
Chapter 6: Challenges in governance
Effective data governance is essential for the continuous progress of artificial intelligence (AI) in the health sector, particularly in the development of drugs and vaccines. This governance entails significant privacy considerations, especially when the use of data extends beyond the original consent provided by users.
Legal and ethical challenges emerge when proprietary datasets, often safeguarded by intellectual property rights, are restricted from broader use. Such limitations can hinder collaboration and stifle innovation.
To address these issues, multinational frameworks like the European Health Data Space are being developed to standardize data governance. These frameworks aim to facilitate secure data sharing for research and policy-making, ultimately promoting a more collaborative and innovative environment in health AI.
The chapter includes:
- Governance of data
- Ownership and intellectual property
- Governance of the private sector
- Regulatory oversight and approval of AI-developed medicines and vaccines
Chapter 7: Next steps
Conclusion
Ethical and legal considerations surrounding data use and sharing, intellectual property rights, and the protection of privacy are critical. Collaborative efforts and open data initiatives can enhance AI's potential while ensuring equitable access and innovation.
Regulatory oversight is essential to address challenges such as data quality, algorithm transparency, and compliance with ethical standards. Strong cooperation among governments, academic institutions, and the private sector is mandatory to foster an environment that maximizes the benefits of AI in healthcare while mitigating risks.
