The Role of AI within the Health and Climate Change Nexus: A Worthy Big Bet?

Posted août 8, 2024

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

When it comes to global health and climate interventions, strategic partnerships are key.

By Alison Malmqvist, Vice President, Global Fundraising and Communications, PSI, and Martin Dale, Global Director, Digital Health and Monitoring, PSI

From self-driving cars to ChatGPT, it is easy to imagine a future where artificial intelligence (AI) can do just about anything. But when it comes to AI solving the world’s most pressing health and climate challenges, let’s be realistic. These advances are promising – but we can’t underestimate what it will take to unlock this opportunity.

The hype around AI is warranted – increased presence of emerging technology such as AI can potentially transform the health sector, bringing new opportunities. There are companies already leveraging AI to transform healthcare by improving health diagnostics, disease surveillance, drug development, and to identify and address inefficiencies in health systems. The volume and interconnectivity of data will accelerate advances in health sciences and practices, enabling rapid identification of health trends, new discoveries, and greater efficiency across systems and sectors.

That said, there is inherent risk in AI-powered health interventions and it will take time to safely and effectively integrate them into health systems – time we don’t have to address the climate crises of today.

The immediate opportunity to unlock the potential of AI to jointly address health and climate challenges relies on our ability to build on what is already working. One example is disease surveillance;

Disease surveillance systems in low and middle-income countries (LMIC) are a valuable public health tool. We, along with other global health organizations, have made significant progress collecting disease-specific data for routine surveillance in LMICs, though there is still more to be done. For endemic diseases like malaria, the global health community is beginning to understand how to pair health and climate-related data to analyze disease patterns.
We are adapting our surveillance systems to account for climate change. Disease surveillance combined with weather pattern and animal health analyses allows us to help Ministries of Health (MoH) respond appropriately to present outbreaks and prepare for those of the future. For example, if we see an upsurge in malaria, we can use weather patterns to understand the environmental conditions most conducive to transmission.
Predictive analytics is where AI gets involved – to predict the likelihood of outbreaks under specific conditions in specific geographies. AI-powered predictive analytics can be used for early warning systems for infectious diseases, detecting new outbreaks, and predicting the trend of epidemics. The evidence-base is growing, and—for it to be an ace up health systems’ sleeves – it must continue to deepen. Global health and climate communities must collaboratively invest in integrating AI within surveillance systems.

Are we ready for AI?

AI presents significant promise for the global health and climate community. However, we’re up against a number of considerations:

What are the inherent risks of using AI systems and how can we mitigate them?
How can we stay consistent with which data we’re using and how AI is deployed?
How can we ensure high quality and representative population data?
What does it take to validate a particular model over time?
How do we address machine learning biases so they do not exacerbate health inequities?
How do we bring key stakeholders such as MoHs along the journey in order to build trust in the use of AI?

AI development has been western-centric to a significant degree, but our health and climate challenges are global. COVID-19 proved that health innovations developed in the West do not benefit the rest of the world without strategic investments and international partnerships. While countries like the U.S. received their second and third COVID-19 vaccines and national economies began to recover, many countries in the global south were still waiting on vaccine relief.

We can’t repeat history; the health consequences of climate change are global, and already disproportionately impact LMICs. AI innovations, largely happening in the West, must be built and implemented with a global scope, so that potential can lead to impact for populations around the world. There are many AI actors emerging in LMICs. Funding must be distributed equitably to bring these players along the journey and more attention should be placed on fostering partnerships between AI actors in the west and LMICs.

Progress in the use of digital platforms for disease surveillance did not happen overnight – nor will it for AI. Alongside MoHs, the global health and climate community should work collaboratively to help source data, ensure appropriate privacy protections are put in place, convene the right stakeholders to co-create AI models, and help build a case for how data sharing will tangibly benefit the countries involved.

AI models have a place in addressing present and future climate and health challenges, but they need to be built in strong collaboration with governments and local actors in LMICs, where the health consequences will be most severe.

PSI has worked collaboratively with governments and local actors in over 40 LMICs across five decades. We will leverage our deep-rooted relationships in LMICs and our connections to global AI actors to foster much needed collaboration on the use of AI to jointly address health and climate challenges.

By harnessing technical innovation through multi-sectoral partnerships we can help communities and health system actors anticipate, prepare for, and adapt to the effects of a changing climate.

We work at the intersection of climate and health. Learn more here.