Charting AI's Ethical Course in Healthcare Governance

In an article recently published in the journal Humanities and Social Sciences Communications, researchers demonstrated the need for robust ethics and governance frameworks to guide the development and use of artificial intelligence (AI) in healthcare.

Study: Charting AI
Study: Charting AI's Ethical Course in Healthcare Governance. Image credit: Billion Photos/Shutterstock

Background

In healthcare, regulating the application of AI and mitigating its challenges at the international, regional, and national levels is a crucial and complex topic. AI systems can potentially improve clinical trials and research, enhance health outcomes, facilitate early diagnosis and detection for more effective treatment, and empower both patients and healthcare employees who depend on health monitoring in developing countries or remote areas. However, AI possesses social, legal, and ethical risks like environmental impact, patient safety, algorithmic bias, and data privacy.

In this paper, the regulatory, ethical, and technical challenges of using AI in healthcare were identified and evaluated. The key challenges confronted by states in regulating AI use in healthcare were also identified, specifically the legal complexities and voids for better transparency and adequate regulation. Additionally, the author made a number of recommendations to mitigate risks, secure health data, and more efficiently regulate AI use in healthcare through the implementation of harmonized standards and global cooperation under the World Health Organization (WHO), in line with the organization's constitutional mandate to regulate both public and digital health.

Challenges of AI in healthcare

Performance, discrimination, errors and misdiagnosis, accountability and transparency, explainability, adoption and implementation, security, governance and regulation, ability to regulate third-party access to personal health data, bias, access and affordability to AI in developing countries, interoperability between various operating systems like Android and Apple, health equity, and data collection, storage, privacy, quality, accuracy, and availability are the major challenges of using AI in healthcare.

Ethical, regulatory, and technical challenges must be addressed by developing concrete regulations like representativity, interoperability, conditions for accessing health data, and the implementation of quality standards. Additionally, compliance with crucial regulations such as the Health Insurance Portability and Accountability Act (HIPAA), General Data Protection Regulation (GDPR), Data Act, or AI Act is also necessary. Self-regulation must be encouraged to develop public confidence in AI-driven applications.

Ensuring personal health data privacy

Various measures can be implemented to ensure the security and privacy of personal health data. All stakeholders, including healthcare providers, companies, and regulatory authorities, are responsible for ensuring data confidentiality and patient privacy.

Security awareness training, encryption, two-factor authentication, role-based access implementation, data access restrictions, using a VPN to secure data, conducting routine risk assessments, and educating healthcare personnel are the potential safeguards and measures to ensure effective data protection.

Solutions to regulate AI systems

Although the regulation of AI in healthcare is a complex issue, potential solutions exist to regulate AI systems adequately. Establishing legally binding standards and rules under the WHO, promoting accountability and transparency, strengthening regulatory oversight, fostering global cooperation, encouraging industry self-regulation, establishing an ‘AI culture’ with all important stakeholders, and ethically using personal health data are the solutions that can adequately regulate the use of AI in healthcare.

For instance, the European Commission categorized AI systems based on various levels of risk requiring less or more regulation. Under the AI Act, AI systems with unacceptable levels of risk must be banned, while AI systems with limited risk must comply with minimal transparency requirements to enable users to make informed decisions.

Similarly, the WHO has listed crucial regulatory considerations on AI for health at the multilateral level. Promoting safety, protecting autonomy, ensuring transparency, fostering responsibility, promoting sustainable AI, and ensuring equity are the WHO’s guiding principles for regulating AI in healthcare.

WHO has also advocated for better cooperation and coordination between all stakeholders and states to ensure greater medical and clinical benefits for patients. These WHO-developed principles can assist stakeholders in developing responsible and ethical AI systems based on five distinct themes, including compliance with guiding principles, engaging in dialogue and collaboration, balancing responsibility and innovation, building organizational awareness and culture, and using proper methods and tools.

AI ethics and governance

The existing applicable legal framework to global public health does not adequately protect privacy and personal data, which necessitates a new paradigm for reshaping global health and shifting towards a legal framework dedicated to AI in healthcare.

This new paradigm involves the implementation of legally binding rules by WHO members in the field of AI. The International Health Regulations (IHR) (2005) can be utilized by States Parties to enhance the degree of response to threats like privacy. WHO members can depend on IHR and EU regulations, such as the Data Act, AI Act, and GDPR, to negotiate new legally binding rules.

To summarize, AI must provide better health systems and facilitate access to healthcare according to the United Nations Sustainable Development Goals (UN SDGs), specifically in the least developed countries. European regulations can provide established standards and reliable legal frameworks, which can be implemented by every stakeholder for responsible and ethical AI systems. Additionally, WHO Members must cooperate actively and elaborate legally binding rules and new guidelines under the IHR.

Journal reference:
Samudrapom Dam

Written by

Samudrapom Dam

Samudrapom Dam is a freelance scientific and business writer based in Kolkata, India. He has been writing articles related to business and scientific topics for more than one and a half years. He has extensive experience in writing about advanced technologies, information technology, machinery, metals and metal products, clean technologies, finance and banking, automotive, household products, and the aerospace industry. He is passionate about the latest developments in advanced technologies, the ways these developments can be implemented in a real-world situation, and how these developments can positively impact common people.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Dam, Samudrapom. (2024, March 21). Charting AI's Ethical Course in Healthcare Governance. AZoAi. Retrieved on November 21, 2024 from https://www.azoai.com/news/20240321/Charting-AIs-Ethical-Course-in-Healthcare-Governance.aspx.

  • MLA

    Dam, Samudrapom. "Charting AI's Ethical Course in Healthcare Governance". AZoAi. 21 November 2024. <https://www.azoai.com/news/20240321/Charting-AIs-Ethical-Course-in-Healthcare-Governance.aspx>.

  • Chicago

    Dam, Samudrapom. "Charting AI's Ethical Course in Healthcare Governance". AZoAi. https://www.azoai.com/news/20240321/Charting-AIs-Ethical-Course-in-Healthcare-Governance.aspx. (accessed November 21, 2024).

  • Harvard

    Dam, Samudrapom. 2024. Charting AI's Ethical Course in Healthcare Governance. AZoAi, viewed 21 November 2024, https://www.azoai.com/news/20240321/Charting-AIs-Ethical-Course-in-Healthcare-Governance.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoAi.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Enhancing Explainability in Generative AI: Key Strategies