WHO issues ethical guidelines for AI in healthcare, focusing on large multi-modal models

The World Health Organization (WHO) recently released detailed guidance on the ethics and governance of artificial intelligence (AI) in healthcare, with a specific focus on large multi-modal models (LMMs). This comprehensive guidance comes as AI technologies, particularly LMMs, are increasingly integrated into healthcare systems globally, revolutionizing the way health services are delivered and managed.

Study: Ethics and governance of artificial intelligence for health. Guidance on large multi-modal models. Image Credit: metamorworks / Shutterstock.com

Key aspects of WHO guidance

The guidance document delves into various aspects of AI application in healthcare, addressing the urgent need for ethical considerations and robust governance frameworks.

Ethical use of AI in healthcare

Emphasizing the importance of respecting patient autonomy, the WHO outlines the need for AI systems to be transparent and intelligible. This is crucial to maintain the responsibility and accountability of AI-assisted decisions in healthcare.

LMMs

LMMs, which are capable of processing and interpreting diverse data types, including biosensor data, genomic information, and environmental factors, are at the forefront of AI in healthcare. Moreover, LMMs offer immense potential in diagnostics, clinical care, and medical research. However, their use raises concerns about data privacy, potential biases in decision-making, and the risk of job displacement in the health sector.

Balancing benefits and risks

WHO guidance advocates for a balanced approach to AI in healthcare, in which researchers maximize the benefits of AI for improving healthcare delivery and research while addressing the risks associated with its use. This includes ensuring data privacy, preventing biases, and aligning AI technologies with sustainability and public health goals.

Recommendations for governments and stakeholders

The WHO guidance emphasizes the critical role of governments in regulating AI in healthcare. For example, governments are encouraged to establish regulatory frameworks to develop and enforce standards for the development and deployment of AI in healthcare. This involves ensuring AI systems are transparent, comply with ethical standards, and respect human rights.

Independent audits and impact assessments

The WHO recommends mandatory independent audits and impact assessments of AI systems, particularly those deployed on a large scale. These assessments should focus on data protection, human rights implications, and the impacts of AI on diverse populations.

Inclusive stakeholder engagement

The WHO guidance underscores the importance of involving a wide range of stakeholders, including healthcare professionals, patients, AI developers, and civil society, in the AI development process. This approach will ensure that AI systems are inclusive, equitable, and address the needs of all sections of society.

Potential and challenges of AI in healthcare

AI in healthcare offers significant potential for improving patient outcomes, enhancing the efficiency of healthcare systems, and accelerating medical research. LMMs, in particular, have the ability to analyze vast amounts of data, thereby leading to more accurate diagnoses, personalized treatment plans, and a better understanding of complex medical conditions.

However, the integration of AI in healthcare also presents significant challenges. These include concerns over data privacy, the risk of AI systems perpetuating existing biases, and the ethical implications of AI-assisted decision-making in healthcare. The WHO guidance aims to address these challenges by providing a framework for the ethical and responsible use of AI in healthcare.

Global implications and future directions

The release of the WHO guidance on AI in healthcare is a milestone in the global effort to harness the benefits of AI while mitigating its risks. Moreover, these guidelines highlight the need for international collaboration and shared standards in developing and deploying AI technologies in healthcare.

Looking forward, the WHO guidance sets the stage for ongoing dialogue and development in this rapidly evolving field. To this end, the WHO presents an opportunity for governments, healthcare providers, AI developers, and civil society to work together to ensure that AI in healthcare is used ethically and responsibly for the greater good of public health.

Conclusions

The comprehensive guidance by the WHO on the ethics and governance of AI in healthcare, with a focus on LMMs, marks a significant step forward in addressing the complex challenges and opportunities presented by AI in healthcare.

By providing clear recommendations and highlighting the need for balanced, ethical, and inclusive approaches, the WHO is leading the way in ensuring that AI technologies are harnessed to improve healthcare outcomes, enhance patient care, and advance global health equity. As AI continues to transform healthcare, this guidance will serve as a crucial reference for policymakers, healthcare providers, and AI developers worldwide.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

Citations

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

  • APA

    Kumar Malesu, Vijay. (2024, January 23). WHO issues ethical guidelines for AI in healthcare, focusing on large multi-modal models. News-Medical. Retrieved on November 13, 2024 from https://www.news-medical.net/news/20240123/WHO-issues-ethical-guidelines-for-AI-in-healthcare-focusing-on-large-multi-modal-models.aspx.

  • MLA

    Kumar Malesu, Vijay. "WHO issues ethical guidelines for AI in healthcare, focusing on large multi-modal models". News-Medical. 13 November 2024. <https://www.news-medical.net/news/20240123/WHO-issues-ethical-guidelines-for-AI-in-healthcare-focusing-on-large-multi-modal-models.aspx>.

  • Chicago

    Kumar Malesu, Vijay. "WHO issues ethical guidelines for AI in healthcare, focusing on large multi-modal models". News-Medical. https://www.news-medical.net/news/20240123/WHO-issues-ethical-guidelines-for-AI-in-healthcare-focusing-on-large-multi-modal-models.aspx. (accessed November 13, 2024).

  • Harvard

    Kumar Malesu, Vijay. 2024. WHO issues ethical guidelines for AI in healthcare, focusing on large multi-modal models. News-Medical, viewed 13 November 2024, https://www.news-medical.net/news/20240123/WHO-issues-ethical-guidelines-for-AI-in-healthcare-focusing-on-large-multi-modal-models.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
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...
New UCL hub to advance cancer detection with imaging tech