In 2023, the World Health Organization (WHO)[1] issued a new publication outlining key regulatory considerations regarding artificial intelligence (AI) in health. This document underscores the importance of ensuring AI systems’ safety and effectiveness, promptly making them available to those in need, and fostering dialogue among various stakeholders, including developers, regulators, manufacturers, health workers, and patients.
As health care data becomes more accessible and analytic techniques advance rapidly (including machine learning, logic-based approaches, and statistical methods), AI tools have the potential to transform the health sector.
The WHO recognizes AI’s capacity to enhance health outcomes by:
Strengthening clinical trials.
Improving medical diagnosis, treatment, self-care, and person-centered care.
Augmenting health care professionals’ knowledge and competencies.
For instance, AI can be particularly beneficial in settings with a shortage of medical specialists, aiding in tasks like interpreting retinal scans and radiology images.
However, the rapid deployment of AI technologies, including large language models (LLMs), sometimes occurs without a complete understanding of their performance implications. This deployment can either benefit or harm end-users, including health care professionals and patients. Additionally, when AI systems handle health data, they may access sensitive personal information. Therefore, robust legal and regulatory frameworks are essential to safeguard privacy, security, and data integrity.
Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, emphasizes that while AI holds great promise for health, it also presents serious challenges related to unethical data collection, cybersecurity threats, and the amplification of biases or misinformation. The newly issued guidance aims to assist countries in effectively regulating AI, harnessing its potential for various health applications, from cancer treatment to tuberculosis detection.
Federal Laws, Statutes, and Regulations
Federal laws provide a consistent framework across the country. To achieve uniformity, federal laws should balance national standards with state-specific needs. They should also
be adaptable ensuring that the laws keep pace with technological advancements.
Federal agencies should work closely with states. And Federal and State agencies should periodically review and update regulations.
FDA Regulations:
FDA oversight ensures safety and efficacy.
The challenge is balancing regulation with innovation. Some AI applications may not fit traditional regulatory pathways.
The FDA should issue clear guidelines for AI devices. Additionally, ' Fast-Track Approvals' could streamline approval processes for low-risk AI.
State Laws and Regulations:
State laws address local nuances. Differing state requirements results in fragmentation which can hinder interoperability. And inequity results from uneven access to AI-based healthcare.
States should collaborate on common standards and ensure equitable distribution of AI benefits to all communities.
Public Health Laws:
Public health laws protect population health. But balancing individual rights with public health needs is a challenge. During emergency situations, there arises a rapid deployment of AI. Thus, privacy may be safeguarded by developing guidelines for AI data sharing. Emergency protocols should pre-approve AI tools for pandemic response.
Medical Malpractice and AI:
AI can reduce diagnostic errors. But the challenges are (1) determining responsibility in AI-related errors, and (2) defining the standard of care and the role of AI in medical practice.
Clear guidelines can help in establish standards for AI use and define shared responsibility and liability for AI-related mistakes.
Telemedicine:
Telemedicine has expanded access to medical care. It involves a multidisciplinary healthcare team.
AI-driven telehealth should maintain high standards to ensure quality. It is important to regularly assess telemedicine AI tools.
Some communities do not have access to the Internet. Disparity in internet connectivity should be addressed and bridge the digital divide.
Liability of Manufacturers, Developers, and Distributors:
Manufacturers, Developers, and Distributors are stakeholders and may be held accountable. They should educate healthcare professionals and patients. They should evaluate potential harm from AI apps and ensure that AI medical apps are reliable. Transparency is also helpful in disclosing AI limitations.
In summary, navigating the legal landscape of medical AI requires a delicate balance between innovation, patient safety, and ethical considerations. Collaborative efforts among federal and state bodies, regulatory agencies, and industry stakeholders are essential to create a robust legal framework that fosters responsible AI adoption.
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