Potentials and Pitfalls of Artificial Intelligence in Promoting Health Literacy and Support

GenAI can help customize community health literacy materials, making these more inclusive and effective. Photo credit: ADB.

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Generative AI has the potential to improve community resilience with careful yet optimistic approach in promoting health interventions.

Introduction

Generative artificial intelligence (GenAI) has the potential to drive innovations in various fields, particularly in enhancing health literacy and implementing community health support. By utilizing large language models and advanced deep learning algorithms, GenAI can quickly generate text and vivid images in response to user prompts.

GenAI can become a significant instrument in building healthier, more informed, and more resilient communities. It can create intervention content tailored to diverse communities while its user-friendly applications enable easy navigation that makes it a powerful tool for engaging and empowering communities in providing support, such as digital mental health interventions.

While scholars have explored the possible applications of GenAI in online chatbots and other programs, others have cautioned against its premature implementation due to lack of evidence and its unpredictability.

Potentials in Health Promotion

GenAI can help promote the United Nations Sustainable Development Goals on health by designing effective communication strategies and tools, such as preparing communities for pandemic and adapting mental health interventions that reflect the language and culture of the communities.

Enhancing preventive measures and health literacy

GenAI tools can enhance community preparedness by customizing health literacy materials and toolkits—making these more inclusive and effective. Community members can utilize these tools to generate content that is both accessible and culturally relevant, empowering them to take proactive measures in protecting their health and building resilience against future crises.

During the COVID-19 epidemic, public health messaging often faced barriers due to reliance on written communication in official languages, which alienated linguistically diverse communities and those with high illiteracy rates. GenAI can help address these challenges by rapidly personalizing communications to meet specific linguistic and cultural needs, as well as expanding media formats to include images and audio for community-led campaigns.

During a pandemic, GenAI tools can deliver personalized resources and support at both the community and individual levels through chatbots and other digital platforms. These tools can effectively disseminate accurate information, offer mental health support, and provide tailored guidance based on real-time data and community feedback.

Empowering communities

Collaboration with trusted community leaders—such as faith and indigenous leaders—play an important role in health communication. They can help enhance the acceptance and reach of health messages, ensuring a wider range of perspectives.

Fostering digital literacy would enable communities to creatively engage with each other through their unique cultural experiences, enhancing cohesion and overall wellness. This approach brings greater trust and engagement within the community, ultimately leading to more effective public health initiatives and promoting community resilience and sustainable development.

Given that websites of official health agencies often present an overwhelming amount of information and may struggle to address specific inquiries, GenAI can swiftly simplify complex protocols and advisories into more digestible formats.

Additionally, with healthcare systems under significant strain, there has been a growing reliance on chatbots and conversational agents to handle patient queries. Specialized mental health resource chatbots have also been developed to assist healthcare workers and their families, providing essential support during challenging times.

Challenges of Using AI

Despite the promising potential of leveraging GenAI, several challenges need to be addressed: (i) privacy and ethical concerns, (ii) AI hallucinations, and (iii) AI literacy and mis-prompting.

Privacy and ethical concerns

Existing digital mental health applications using GenAI face a common set of significant barriers to implementation, such as data privacy and ethical issues, given the sensitive nature of the data involved. Ensuring informed consent and safeguarding patient confidentiality are critical. Robust data security measures should be implemented to reduce the risk of data breaches and misuse.

AI hallucinations

Issues such as bias in training data and hallucination errors are not uncommon. In the area of mental health, the plausibility of such outputs can lead to misguided therapeutic recommendations and other misinformation. The potential to produce factually correct but contextually inappropriate data and biased explanations necessitates a level of AI literacy among users. To address AI hallucinations, technical, procedural, and educational solutions are important to enhance the reliability of AI systems and ensure their safe and effective use.

AI literacy and mis-prompting

The effectiveness of GenAI relies heavily on users' ability to correctly interact with the technology. Lack of AI literacy or mis-prompting can lead to suboptimal or even harmful outcomes. For example, users’ biases in data may lead to misguided recommendations or wrong content due to poorly framed prompts—potentially hindering progress rather than promoting it.

Educating community members and stakeholders on AI literacy and how to effectively use these tools is crucial for maximizing their potential and ensuring the quality of co-created interventions. Aside from health literacy, training protocols for pilot programs and initiatives should incorporate digital inclusion and AI literacy, for example, tailor training materials to be culturally sensitive and train-the-trainer, local champions, and peer network learning initiatives (community leaders and local experts).

Going Forward

Generative AI offers immense potential in advancing community resilience and promoting sustainable development, particularly through its capacity to enhance health interventions.

Using AI to analyze complex data and predict trends can assist in developing more effective and resource-efficient strategies. However, to fully realize its transformative potential, it is crucial to prioritize capacity-building and equitable access. Empowering communities with the knowledge and tools to engage with AI can bridge the digital divide and ensure everyone can share the benefits.

An optimistic yet cautious approach focusing on ethical AI practices and inclusivity can foster more resilient, sustainable, and healthier communities.

Brian J. Hall
Director of Center for Global Health Equity, Professor of Global Public Health, NYU Shanghai

Brian J. Hall is a founding director of the Center for Global Health Equity at NYU Shanghai and an affiliated professor at School of Global Public Health, New York University. For more than a decade in the People’s Republic of China, he conducted epidemiologic investigations on the health of diverse populations. He is a prolific scholar, academic leader, and dedicated mentor. He earned his PhD in Clinical Health Psychology from Kent State University and completed his clinical internship at the Medical University of South Carolina.

Celia Forster
Master of Education candidate, Harvard Graduate School of Education

Celia Forster is a master of education candidate in Learning Design, Innovation, and Technology at the Harvard Graduate School of Education. She holds a bachelor’s degree in Interactive Media Arts and Social Science from NYU Shanghai. Her research centers on the culturally relevant implementation of emerging technology in international higher education settings.

Vasoontara Sbirakos Yiengprugsawan
Senior Universal Health Coverage Specialist (Service Delivery), Human and Social Development Office, Sectors Group, Asian Development Bank

Vasoontara Sbirakos Yiengprugsawan oversees ADB’s technical assistance on strengthening primary healthcare and management of chronic noncommunicable diseases and mental health. She has held senior health research positions in Australia, a WHO Fellowship with the Asia Pacific Observatory on Health Systems and Policies, and worked in policy and research with a UN Migration Agency in Geneva. She holds a PhD in Epidemiology, Economics and Population Health from Australian National University and MA in International Development from Syracuse University.

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