AI in research showcase - Lynn Hendricks
Human-Centred AI: Prof Lynn Hendricks' Work at the Intersection of Health Equity and Innovation
For Prof Lynn Hendricks, artificial intelligence is not primarily a technology story. It is a story about people, equity, participation, and the future of health communication. Her work explores how AI can help bridge the gap between scientific knowledge and lived experience, while ensuring that innovation remains grounded in ethics, inclusion, and community partnership. An overview of her projects and grants is available on her website at https://sites.google.com/view/lynnhendricks/.
Liela Groenewald, Head of the Doctoral Office, Tygerberg, engaged with Hendricks about her route to AI and her thinking on its potential to transform health research and communication.
Also see: SU researcher profile | Google scholar profile | OrcID
Please share a little about yourself and what sparked your interest in your field of research.
"I am Prof Lynn Avril Hendricks. I am an Associate Professor and I lead the COCREATE Research Equity Hub in the Division of Health Systems and Public Health at Stellenbosch University as well as the Public Square in the Social and Environmental Determinants of Health.
"My work sits at the intersection of social medicine, health equity, research ethics, and community engaged scholarship. My academic journey has been intentionally transdisciplinary. With training in psychology, social science, public health, epidemiology, and health research methods, I have always been drawn to complex questions that require perspectives from multiple disciplines."
"This has shaped an approach that brings together health sciences, social sciences, humanities, arts, and emerging technologies to address contemporary health challenges. A question I have been exploring for a while is 'how can we create more inclusive, ethical, and responsive ecosystems of health and knowledge production'?".
"Growing up on the Cape Flats exposed me to the realities of inequality and the ways in which health is influenced by far more than healthcare alone. These experiences sparked my interest in social medicine and a commitment to understanding how poverty, violence, exclusion, environment, culture, and power shape health outcomes. They also inspired a lifelong dedication to health equity and social justice."
"A central theme of my work is research equity. I am interested in whose voices are represented in evidence, who gets to produce knowledge, and how communities can be meaningfully involved in shaping research agendas and solutions. This has led me to develop participatory, creative, and community engaged approaches that position communities as partners in research rather than subjects of study."
"My interest in the medical humanities emerges from a belief that stories, lived experiences, creativity, and ethical reflection are essential to understanding health and healthcare. Through documentaries, exhibitions, storytelling, arts based methods, and digital innovation, I seek to bridge the gap between evidence and human experience."
"More recently, my work has explored the opportunities and challenges presented by artificial intelligence in health research and communication. I am particularly interested in ensuring that technological innovation remains grounded in ethics, equity, and human connection."
"Ultimately, I believe that the future of social medicine lies in bringing science, ethics, humanities, technology, and lived experience into conversation. Through my research, teaching, and leadership, I aim to contribute to more equitable health systems, more inclusive research practices, and healthier communities," Hendricks explains.
"Perhaps the most important lesson is the need for humility. As researchers, we must remain open to innovation while being honest about limitations and potential harms. For me, the goal is not simply to develop new AI tools, but to ensure that innovation advances equity, strengthens human connection, and contributes to healthier and more inclusive societies," she reflects.
What excites you most about the future of AI in health research?
"There is much to be excited about. What excites me most about the future of AI in health research is its potential to make knowledge, healthcare, and research more accessible, personalised, and inclusive."
"For many years, health research has generated important evidence, yet there remains a significant gap between knowledge production and the people who could benefit most from it. AI offers opportunities to bridge that gap by translating complex information into formats that are more understandable, culturally relevant, and responsive to individual needs."
"This has particular relevance in diverse and resource constrained settings where access to healthcare professionals and health information may be limited. I am especially excited about the potential of AI to strengthen health communication, support patient engagement, and empower individuals to play a more active role in managing their health."
"I also see enormous opportunities for AI to support researchers by reducing administrative burdens, enhancing data analysis, and accelerating the translation of evidence into practice."
"I believe some of the most important innovations will emerge at the intersection of AI and social medicine. The future is not simply about building smarter technologies. It is about developing technologies that are ethical, equitable, and grounded in human experience."
"For me, the greatest promise of AI is not replacing people, but helping us connect knowledge, care, and communities in new and meaningful ways," Hendricks says.
How did AI become part of your research journey?
"AI became part of my research journey through my interest in health equity, communication, and community engagement rather than through technology itself. Much of my work focuses on addressing the gap between health information and people's everyday realities," says Hendricks.
"Whether working with young women living with HIV, adolescents navigating sexual and reproductive health, or communities affected by chronic disease, I repeatedly encountered the same challenge: evidence often fails to reach people in ways that are accessible, meaningful, and responsive to their lived experiences."
"I became interested in AI because it offered new possibilities for democratising access to knowledge and supporting more personalised and scalable forms of health communication. Rather than viewing AI as a replacement for human relationships, I see it as a tool that can strengthen health education, patient engagement, and community participation, particularly in settings where access to healthcare professionals and specialised support is limited."
"My work has explored AI supported storytelling approaches for health communication, particularly for people living with chronic conditions such as diabetes, HIV, and tuberculosis. I am interested in how generative AI can support culturally relevant narratives, visual stories, and conversational tools that make health information more engaging and understandable."
"At the same time, my background in social medicine, health ethics, and research equity has shaped a critical perspective on AI. Questions of power, bias, representation, digital inclusion, and data justice are central to my work. I believe AI systems should be developed with communities rather than simply for communities, ensuring that the voices of those most affected by health inequities help shape their design and use."
"What excites me most about AI is not the technology itself, but its potential to create more inclusive ways of sharing knowledge, amplifying diverse voices, and supporting health and wellbeing. My research therefore explores how AI can be harnessed in ways that are ethical, human centred, and responsive to the needs of diverse communities," she says.
"I have also learned the importance of maintaining human oversight. AI can support communication, analysis, and efficiency, but it cannot replace human judgement, ethical reasoning, empathy, or lived experience. In health research, trust remains a fundamentally human relationship.
"This was a key lesson from the StoryRx project, where all AI generated stories underwent review by medical evaluators before being shared with patients. While AI helped create personalised and engaging content, clinical experts were essential in ensuring that the information was accurate, appropriate, safe, and aligned with current medical guidance. This combination of technological innovation and human expertise was critical to building trust and ensuring responsible use of AI in healthcare."
"At the same time, AI has enormous potential to democratise knowledge and expand access to information. Used responsibly, it can help bridge communication gaps and make research more accessible. However, these opportunities must be balanced with attention to privacy, accountability, transparency, and digital inclusion."
Can you describe a moment when AI made a meaningful difference in your research?
One project in particular has helped demonstrate how AI can support more meaningful and accessible health communication.
"One of the most meaningful moments in my AI research journey came through the StoryRx project, which I co lead with my colleague Prof Simone Titus. The project is funded through the South African Medical Research Council Catalyzing Equitable AI Use to Improve Global Health initiative and is supported by Microsoft Africa Research Institute.
"StoryRx explores how generative AI can be used to create culturally relevant health stories and communication tools for people living with chronic conditions such as diabetes, HIV, and tuberculosis. The project emerged from a simple but important observation: health information is often scientifically accurate but fails to connect with people's everyday lives, experiences, and cultural contexts.
"One particularly memorable moment was seeing how participants responded to AI generated stories that reflected their own realities. Rather than engaging with generic health messages, people encountered narratives that resonated with their experiences, challenges, families, and communities. The conversations that followed were richer, more reflective, and more personal than what we often see with traditional health education materials.
"What made this especially meaningful was that the project demonstrated how AI could be used not simply to automate communication, but to make health information more human, accessible, and relevant. For someone whose work is grounded in social medicine, health equity, and research equity, this was an important reminder that technology can support connection rather than replace it.
"At the same time, the project reinforced the importance of ethical and equitable AI development. Questions about representation, language, cultural relevance, and inclusion became central to the research. These conversations reminded us that the success of AI in health depends not only on technical performance but also on whose voices are included in its design and whose needs it ultimately serves.
"StoryRx has shown me that AI has the potential to transform health communication, particularly in contexts where traditional approaches have struggled to reach diverse populations. More importantly, it has strengthened my belief that the future of AI in health must be guided by principles of equity, ethics, and community partnership," Hendricks notes.
What have you learned about using AI responsibly and effectively?
For Hendricks, responsible AI begins with recognising that technology alone cannot solve social challenges.
"One of the most important lessons I have learned is that responsible AI is fundamentally about people, not technology. The success of AI depends less on what the technology can do and more on how, why, and for whom it is used.
"AI systems are never neutral. They reflect the data they are trained on and the assumptions built into them. Questions of bias, representation, inclusion, and power therefore need to be considered from the beginning.
"Through projects such as StoryRx, I have learned that meaningful community engagement is essential. People who are intended to benefit from AI should help shape its design, testing, and evaluation. This helps ensure that AI tools are relevant, accessible, and responsive to real needs.
