In May 2023, the World Health Organization (WHO) issued a statement calling for caution in the use of AI-based tools that use large linguistic models. The aim is to ensure the safety, autonomy, and well-being of individuals, as well as to preserve public health. As these tools become increasingly popular and are used experimentally in healthcare, it is necessary to examine the risks associated with their use and take appropriate measures to protect individuals and reduce inequity in access to care.
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Necessary precautions
While WHO recognizes the potential of large linguistic models and other AI-based technologies to improve access to health information, support decision-making, and facilitate diagnosis in resource-limited settings, it also expresses concern about the lack of precautions that often accompany the implementation of these technologies. WHO stresses the importance of core values such as transparency, inclusiveness, public collaboration, expert oversight, and rigorous evaluations.
Risks associated with large linguistic models
The hasty adoption of systems based on large linguistic models without rigorous evaluation can lead to errors by healthcare personnel, cause harm to patients, and erode confidence in AI. In addition, there are specific concerns related to these models:
- Biases in the training data: the data used to train the models may contain biases, which could generate misleading or inaccurate information. This poses risks to health, equity, and inclusiveness.
- Incorrect or seriously flawed answers: Although the answers generated by large linguistic models may appear authoritative and plausible, there is a possibility that they may be completely incorrect or contain serious errors, especially in the context of health.
- Non-consensual use of data and lack of privacy protection: models may be trained on data for which prior consent has not been obtained, and sensitive health data that users enter into an application to obtain an answer may not be adequately protected.
- Generation of compelling misinformation: There is a risk that large linguistic models may be misused to generate and disseminate compelling misinformation in the form of textual or audiovisual content that the public cannot easily distinguish from trusted health content.
Ethical and safety considerations
It is critical to ensure that the use of AI in healthcare complies with established ethical principles, such as protecting patient autonomy, promoting patient welfare and safety, ensuring transparency and accountability, and promoting equity and inclusivity. In addition, appropriate measures should be taken to address potential risks associated with the use of AI, such as protecting confidential data and minimizing algorithmic bias.
Collaboration and expert oversight
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The evaluation of the benefits of AI should be a collaborative process involving experts in different disciplines, including health professionals, researchers, ethicists, and patient representatives. This collaboration allows for a comprehensive and multidimensional evaluation of AI, considering both its technical aspects and its ethical and social implications. It is also necessary to establish oversight and regulatory mechanisms to ensure compliance with ethical and quality standards in the implementation of AI in health services.
In this regard, WHO recommends that the implementation of AI in health services should be gradual and subject to continuous monitoring. This allows the real effects of AI in healthcare to be assessed and adjustments to be made as needed, and promotes research and knowledge sharing on the implementation and outcomes of AI in different healthcare settings, to improve its effectiveness and optimize its use.
About AlgoNew
At AlgoNew, we add intelligence to your digital interactions so you can deliver a personalized and efficient experience to your customers. How do we do it? Through a combination of intelligent decision management, natural language processing, and advanced analytics.
We use algorithms to help you make informed decisions in real-time and improve the efficiency of your processes. In other words, we make sure that every action you take is based on relevant data and artificial intelligence, resulting in faster and more accurate decision-making.
Conversation management, on the other hand, refers to how you interact with your customers through digital platforms such as chatbots or virtual assistants. We use natural language processing technology to understand and respond to customer requests effectively and naturally. This means your customers can interact with digital systems in the same way they would with a human, which enhances the user experience.
Finally, we use advanced data analytics to gain valuable insights from your digital interactions. We analyze the data generated from your interactions to identify patterns and trends that can help you improve your business. This can include things like identifying common problems your customers have and how to solve them efficiently or identifying areas for improvement in your business processes.
This combination of intelligence that we offer at AlgoNew can help you significantly improve your digital interactions with customers. It helps you make informed, data-driven decisions, interact with them effectively and naturally, and gain valuable insights into your business processes.
All leads to a better customer experience and greater business efficiency!
