Digital Technologies for Smallholder Agriculture: Tensions and Speculations

0Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.

Abstract

Big Tech, Big Agri, and agri-tech start-ups promise us that digital technologies will make agriculture more sustainable, painting high-tech visions of sensors, AI, and autonomous drones and robots running the data-driven farm. However, many such visions just reinforce the existing unsustainable industrial production paradigm. Since smallholder farms continue to produce most of thew world's food, we ask in this work-in-progress: What can we learn from them about the design of appropriate and responsible digital farming technologies? We report tentative findings from an ongoing engagement with smallholder farmers in Northern England, UK. We present six tensions related to the relationship between technology and farming practices and the nature of technologies themselves. We develop a set of values for design for nature-friendly and community-based smallholder agriculture and propose three unfinished evocative design speculations, which we plan to develop further and use in co-design work with farmers going forward.

References Powered by Scopus

Connected seeds and sensors: Co-designing internet of things for sustainable smart cities with urban food-growing communities

49Citations
N/AReaders
Get full text

Configuring the digital farmer: A nudge world in the making?

39Citations
N/AReaders
Get full text

Negotiating sustainable futures in communities through participatory speculative design and experiments in living

34Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Prost, S., Collingham, H., & Rogers, J. (2024). Digital Technologies for Smallholder Agriculture: Tensions and Speculations. In DIS 2024 - Proceedings of the 2024 ACM Designing Interactive Systems Conference (pp. 261–265). Association for Computing Machinery, Inc. https://doi.org/10.1145/3656156.3663714

Readers over time

‘24‘2502468

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

50%

Researcher 2

33%

Professor / Associate Prof. 1

17%

Readers' Discipline

Tooltip

Computer Science 3

50%

Engineering 1

17%

Social Sciences 1

17%

Agricultural and Biological Sciences 1

17%

Save time finding and organizing research with Mendeley

Sign up for free
0