Big Data and AI in Agriculture

Farming is said to be undergoing a digital “revolution.” For example, new tractors are now fitted with sensors that passively collect data on the farm, on farm equipment and even farmers. This data is aggregated with those from other farms into “big data” which are used in machine learning to advise farmers on when to spray, seed and harvest.

I am part of a small but growing international group of critical social scientists who study the societal impacts of digitization in agriculture. My work focuses on the potential that big data and the digital tools for collecting, aggregating and analyzing them is poised to reproduce long-standing and inequitable relationships of power in the agri-food sector. I have several projects on this area and the goal for all of them is to leverage rural community-grounded methods (e.g. participatory technology assessments, focus groups, field observation) that take me across Canada in order to shed light on farmer engagement with emergent technologies, specifically engagement among small and diverse farmers. I ask questions like: What types of big data are currently in use by farmers, governments and corporations in the agri-food system? What kinds of knowledge about food, farming and farmers are big data helping to shape? What power relationships are generated, reinforced or disrupted by the application of big data in the agri-food sector? A secondary goal is to bring farmer feedback directly to federal policy-makers.

Justice and Recognition in Impact Assessment

On 17 October 2013, a conflict over shale gas development came to a head when members of the Elsipogtog First Nation (a Mi’kmaq people) and U.S.-based SWN Corporation confronted each other at the town of Rexton, New Brunswick. Those on the ground in this high-profile conflict argue that it was as much about historical injustice and unsettled land claims as it is about resource development.

My research projects on the topic of impact assessment focus on injustice, recognizing that it is at the centre of environmental governance disputes and the societal disruptions raised by development. Moreover, my research is premised on a justice framework that has three dimensions—procedural, distributional, and cultural—and it addresses a gap in environmental governance scholarship and practice around the third dimension of justice. My ultimate objective is practical: to outline what a justice-oriented approach to meaningful participation in large industrial development would entail for impact review processes in Canada and around the world.

Algorithmic Impact Assessment

I have several collaborative team projects looking at algorithms in-the-making (their design and designers) and in-the-wild (how they get used, by whom, and for what purposes). My work in this area attempts to forward a truly interdisciplinary approach that combines law, ethics and sociology to algorithmic assessment. Indeed, these projects are not just particular assessments of individual algorithms but they all attempt to advance the normative position that technologies cannot just be considered in relation to whether they comply with the law, but also how they fit with broader social values and justice.

Canadian Network for Science and Democracy

I help run the Canadian Network for Science and Democracy which groups thinkers and practitioners broadly focused on science and technology in democratic society, and scholars who advance their thinking through deeply contextual approaches and with patterned and thick description.

It is inspired by the Science and Democracy Network which advances scholarship operating under the idiom of co-production. In States of Knowledge (2004), Sheila Jasanoff presented us with an “idiom” for sense-making that moved against the grain of dominant patterns of thought which carve the world into nature and culture, science and politics, and so on. The idiom of co-production, accordingly, bridges a range of critical frameworks from biopolitics to feminist philosophy of science; it also provides us analytical purchase on complex phenomena such as global climate change, which are necessarily entanglements among people, ideas and ideologies, material objects and institutions.

The scholars united under this virtual domain work on pressing democratic questions involving phenomena that necessitate consideration of their complex and historic entanglements. For example, thinking about how to responsibly design machine “intelligence” necessarily requires thinking about the gendered nature of computer labour and long-standing technological inequities. Or, thinking about how to power the world’s future at once requires finding ways of accounting for claims to unceded land and alternative conceptions of environmental “resources.”