Balancing innovation and ethics in AI governance for health technology assessment

Figures & data

Table 1. The UN and WHO’s principles on AI.

UN (2023) Guiding Principles: Governing AI for Humanity	WHO (2021) Ethical Principles for use of AI for Health
AI should be governed inclusively, by and for the benefit of all	Ensure inclusiveness and equity
AI must be governed in the public interest	Promote human well-being, human safety and the public interest
AI governance should be built in step with data governance and the promotion of data commons	Ensure transparency, explainability, and intelligibility
AI governance must be universal, networked and rooted in adaptive multi-stakeholder collaboration	Foster responsibility and accountability
AI governance should be anchored in the UN Charter, International Human Rights Law, and other agreed international commitments such as the Sustainable Development Goals	Protect autonomy
	Promote AI that is responsive and sustainable

Table 2. Principles and essential questions on governance of AI in HTA.

Principles	Essential questions
Inclusivity	How were applicable patient cohorts, populations, or samples defined and included for model training? How was the AI model and data monitored and evaluated for bias, and how were stakeholders engaged in this process? How were the limitations of the data identified, addressed, and communicated to relevant stakeholders?
Equity	How were diverse populations considered in the development and application of the AI tool? What measures were taken to prevent the AI tool from exacerbating existing health disparities? How were capacity and infrastructure constraints in diverse settings considered?
Well-being and Safety	What specific norms and standards were integrated to ensure well-being and safety in AI-enabled HTA models? How are adverse events or errors in the AI tool monitored, addressed, and communicated?
Public Interest	How are health outcomes quantified and aligned with public interest? What mechanisms are in place for public engagement and feedback regarding the AI tool?
Promoting Autonomy	How are stakeholders’ rights to self-determination and informed decision-making protected? How were data privacy and confidentiality maintained, and what processes are available for stakeholders to challenge or appeal outcomes/decisions made by the AI tool?
Sustainable	How was AI used to reduce the burden on healthcare decision-making, and what are the environmental impacts of deploying the AI tool? What processes are in place for the continuous improvement and maintenance of the AI tool?
Responsibility and Accountability	How were stakeholders responsible for AI outcomes identified, and how is accountability maintained? What mechanisms are in place for addressing errors, biases, or unintended consequences detected post-deployment?
Adaptive Multi- stakeholder Collaboration	How is the effectiveness of the existing multi-stakeholder network and structure regularly reviewed and updated? How were stakeholders from diverse backgrounds involved in the development and adaptation processes?
Transparency	How transparent are the AI decision-making processes, and how is information about AI tool performance shared with stakeholders? What strategies are in place to document and store specific parameters and configurations of the AI model for reproducibility?
Explainability	How are the criteria for identifying relevant HTA users established, and how are explanations tailored to different user groups? What training is provided to ensure responsible and informed use of AI tools?
Intelligibility	What validation methods are used for testing model responses, and how are model outputs validated for accuracy? How are the AI tool’s outputs communicated to end-users, and what feedback mechanisms are in place to improve intelligibility?