Artificial intelligence (AI) will impact the health of humans via improvements to systems and service delivery and AI will also impact environmental health—notably through data-driven sustainability improvements in food production.
Food production is one of the largest contributors to greenhouse gas emissions, (e.g. through methane production at large cattle feedlots) as well as soil and biodiversity degradation. AI promises to revolutionize agriculture and drastically reduce its environmental impact by indicating the precise use of resources through big data-driven advice generated by machine learning (ML). However, this sustainability promise of AI remains largely untested. Preliminary studies suggest that while AI may help solve environmental problems it may consequently raise social issues such as exaggerating power inequity felt in the food system. For instance, robotics technologies are being applied to horticulture, displacing already vulnerable temporary foreign agricultural laborers.
The research aims to shed light on both the environmental and social impacts of big data and AI in food production, with a focus on what policy-makers could do to enable the sustainability gains presented by emerging digitization while fairly distributing its risks. We will develop tools and a framework to support policymakers in Canada and abroad in implementing and exploring what constitutes “smart” changes—ones that support healthier and more sustainable AI-powered healthcare and food production. Our research approach takes an interdisciplinary and critical social science perspective to study the evolving relationship between innovation and the agro-environment.
Launched as part of the Alex Trebek Forum for Dialogue’s Project on AI for Healthy Humans and Environments, this research stream is co-stewarded by the Institute for Science, Society and Policy, the Centre for Law, Technology and Society and the Centre for Health Law, Policy and Ethics.