What You Should Know:
– The next generation of ethical generative artificial intelligence (GenAI) provides new hope to transform public health; however, advances in technology must never come at the cost of patient rights, according to a recent webinar.
– The insights were the consensus amongst top African and American health AI experts who participated in a recent webinar about the impact of GenAI on healthcare hosted by Vantage Health Technology, a social enterprise focussed on health equity globally. Through Vantage, the company has provided AI-led health-tech support to multiple public healthcare systems and diseases including in Africa and the USA for close to a decade.
Insights from Health AI Experts
“We need to change this paradigm to be more effective by matching the supply and demand sides of our health systems in new digital ways.” Dr Sargent, who is a Harvard alumnus and former World Economic Forum Social Entrepreneur of the Year, says that while GenAI has the potential to revolutionize how healthcare supply and demand are balanced, it is not the be-all-and-end-all of health tech. “The aim is not to get distracted by a shiny new toy – we need to put the patient first by protecting privacy and training our models against bias. We must always remember that technology is just a tool in service of patient care and supporting the healthcare workforce to improve health outcomes.”
Using GenAI to tackle specific diseases such as HIV and AIDS
Jaya Plmanabhan, chief scientist at innovation consultancy Newfire Global who trains health AI models for a living, says he is particularly excited about how large language models could be trained to revolutionize virtual expertise on diseases such as HIV and AIDS. “We call these ‘Role Specific Domain Models’ and they have the potential to be programmed to know everything about a particular disease, to better guide healthcare professionals on how to treat patients. This is a tremendously exciting prospect in the mission to end new HIV infections by 2030.”
These Private Language Models (PLMs) become oracles on a subject and are especially useful in helping solve hard problems in HIV management, such as loss to follow-up – a term for patients who drop off treatment. “Trying to find patients is critical to ensure that they don’t become resistant to drugs due to skipping doses. We can make our outreach much more engaging through conversational messages in their mother tongue and this can help us get people back into the clinic and back into care,” explains Ruan Viljoen, Chief Technology Officer of the BroadReach Group.
Viljoen added GenAI can help solve practical problems, such as frontline healthcare workers being overburdened and not having enough time. “What are the repetitive, administrative tasks that are stealing their time? For instance, GenAI can help nurses with automated note-taking in patient interviews, relieving an administrative burden. The goal is not to replace the role but to free up their time for value-added work.”
Heeding the risks and creating guardrails
Vedantha Singh, an AI ethics in healthcare researcher and virologist from the University of Cape Town, said the top ethical considerations for AI in healthcare are privacy, accuracy, and fairness. She urged at all AI systems should start with guardrails and ethics within their foundational design.
“There is a perception that there are no regulations for the use of AI in healthcare, but to assume we are operating in the wild west is not true. International bodies are sharing guidelines and regulation is slowly evolving – including in Africa. Egypt, Rwanda and Mauritius already have strong AI policies,” says Singh. This includes an emphasis on human labor not being completely replaced and giving patients agency over how their data is used.
Singh says that companies must embed ethical guardrails – aka ‘guardrails by design’ in their health products from the start.
