A governance model for the application of AI in health care
Abstract As the efficacy of artificial intelligence (AI) in improving aspects of healthcare delivery is increasingly becoming evident, it becomes likely that AI will be incorporated in routine clinical care in the near future. This promise has led to growing focus and investment in AI medical applications both from governmental organizations and technological companies. However, concern has been expressed about the ethical and regulatory aspects of the application of AI in health care. These concerns include the possibility of biases, lack of transparency with certain AI algorithms, privacy concerns with the data used for training AI models, and safety and liability issues with AI application in clinical environments. While there has been extensive discussion about the ethics of AI in health care, there has been little dialogue or recommendations as to how to practically address these concerns in health care. In this article, we propose a governance model that aims to not only address
Abstract As the efficacy of artificial intelligence (AI) in improving aspects of healthcare delivery is increasingly becoming evident, it becomes likely that AI will be incorporated in routine clinical care in the near future. This promise has led to growing focus and investment in AI medical applications both from governmental organizations and technological companies. However, concern has been expressed about the ethical and regulatory aspects of the application of AI in health care. These concerns include the possibility of biases, lack of transparency with certain AI algorithms, privacy concerns with the data used for training AI models, and safety and liability issues with AI application in clinical environments. While there has been extensive discussion about the ethics of AI in health care, there has been little dialogue or recommendations as to how to practically address these concerns in health care. In this article, we propose a governance model that aims to not only address the ethical and regulatory issues that arise out of the application of AI in health care, but also stimulate further discussion about governance of AI in health care.
Executive Summary
This article proposes a governance model for the application of artificial intelligence (AI) in healthcare, aiming to address ethical and regulatory concerns. The model is designed to stimulate further discussion on the governance of AI in healthcare, where concerns include biases, transparency, privacy, and safety issues. The authors recognize the growing investment in AI medical applications and the need for a practical approach to address these concerns. The proposed governance model is tailored to the healthcare sector and is expected to provide a framework for regulatory bodies, healthcare providers, and technology companies to navigate the complexities of AI adoption in healthcare. The article's focus on governance is timely, given the increasing integration of AI in healthcare and the need for regulatory clarity.
Key Points
- ▸ AI adoption in healthcare is increasing, driven by its potential to improve healthcare delivery.
- ▸ Concerns about AI in healthcare include biases, lack of transparency, privacy issues, and safety risks.
- ▸ A governance model is proposed to address these concerns and stimulate discussion on AI governance in healthcare.
Merits
Comprehensive Analysis
The article provides a thorough analysis of the ethical and regulatory concerns surrounding AI adoption in healthcare, highlighting the need for a governance framework.
Practical Approach
The proposed governance model is designed to be practical and actionable, providing a framework for regulatory bodies, healthcare providers, and technology companies to navigate AI adoption in healthcare.
Timely Contribution
The article's focus on governance is timely, given the increasing integration of AI in healthcare and the need for regulatory clarity.
Demerits
Limited Scope
The article's focus on healthcare governance may limit its applicability to other sectors, where AI adoption is also increasing.
Lack of Empirical Evidence
The article relies on general concerns and principles, but lacks empirical evidence to support the effectiveness of the proposed governance model.
Expert Commentary
The article's proposal for a governance model is a timely and necessary contribution to the conversation on AI adoption in healthcare. However, the model's effectiveness will depend on its adaptability to different healthcare settings and the ability of regulatory bodies to implement and enforce it. As AI adoption continues to increase, it is essential to develop and refine governance frameworks that balance the benefits of AI with the need for transparency, accountability, and regulatory clarity. The article's focus on healthcare governance highlights the need for a sector-specific approach, which can be adapted and refined for other sectors where AI adoption is also increasing.
Recommendations
- ✓ Regulatory bodies should develop and implement sector-specific governance frameworks for AI adoption in healthcare and other sectors.
- ✓ Healthcare providers and technology companies should work together to develop and refine governance models that balance the benefits of AI with the need for transparency, accountability, and regulatory clarity.
