Modelling world agriculture as a learning machine? From mainstream models to Agribiom 1.0

Bruno Dorin & Pierre-Benoît Joly (2020)

Land Use Policy. Online first

Abstract. Models of world agriculture and food systems are used widely to predict future scenarios of land and resource uses. Starting with a brief history of world agriculture models since the 1960s, which shows their hybrid character as well as their limitations in representing real world diversity and options, this article then presents an alternative modelling experience. We argue that models are tools of evidence, hence “truth machines”, but also tools of government, with a multi-faceted political dimension. For instance, the virtual realities that conventional models build incorporate value judgements about the future that remain invisible and difficult to challenge. For ease of computation and comparison, they standardise functional forms and parameters, eliding observable diversity and blacklisting sociotechnical policy options such as those based on agroecology and biological synergies. They are designed for prediction and prescription rather than for supporting public debate, which is also a (comfortable) political stance. In contrast, the Agrimonde experience – a foresight initiative based on the Agribiom model – shows that a model of world agriculture can be constructed as a “learning machine” that leaves room for a variety of scientific and stakeholder knowledge as well as public debate. This model and its partners unveiled some virtual realities, processes and actors that were invisible in mainstream models, and asserted a vision of sustainable agri-food systems by 2050. Agribiom and Agrimonde improved knowledge, policy-making and democracy. Overall, they highlighted the need for epistemic plurality and for engaging seriously in the production of models as learning machines.”

Extract. “In this paper, we adopt a theoretical and conceptual framework inspired by economic sociology and STS (e.g. Callon, 1998; Pinch and Swedberg, 2008). More specifically, we draw on the seminal work of the statistician and historian Alain Desrosières (2014, posthumous book) who highlighted the dual role of economics as a tool of both evidence and government. We thus aim to identify different ways of designing economic models according to their political implications. […] In this paper, we adopt a theoretical and conceptual framework inspired by economic sociology and STS (e.g. Callon, 1998; Pinch and Swedberg, 2008). More specifically, we draw on the seminal work of the statistician and historian Alain Desrosières (2014, posthumous book) who highlighted the dual role of economics as a tool of both evidence and government. We thus aim to identify different ways of designing economic models according to their political implications.” (p. 1/2)

Link to the review



Citer ce billet
GdL (2020, 5 septembre). Modelling world agriculture as a learning machine? From mainstream models to Agribiom 1.0. Économie des conventions. Consulté le 21 mai 2024, à l’adresse https://doi.org/10.58079/n3wc