Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)

International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)

📍Pune, India🗓️ 2-3 July 2026
<Previous Article In Volume
Next Article In Volume>

When Algorithms Fail the Farm: Rethinking Liability Frameworks for AI in Agriculture — A Comparative Study of India, the EU, and the United States

Authors
Arushi M. Mehta1, Simran Singh1, *
1School of Law, Manav Rachna University, Faridabad, India
*Corresponding author. Email: simran@mru.edu.in
Corresponding Author
Simran Singh
Available Online 9 October 2026.
DOI
10.2991/978-94-6239-791-0_35How to use a DOI?
Keywords
Artificial Intelligence; Agricultural AI; Algorithmic Accountability; AI Liability; Product Liability; Precision Agriculture; AI Governance; Comparative Law
Abstract

The emerging technological intelligence (AI) is rapidly transforming agriculture. Whether it is precision farming, predictive analytics or biotechnology integration, the agricultural sector is evolving with these technologies. While being promising by enhancing agricultural productivity and sustainability, the integration of AI has also introduced complex risks when algorithmic systems fail. This paper explores the legal issues surrounding liability for damage caused by AI in agriculture by analyzing case studies in India, EU, and the United States. It amicably argues that how existing liability frameworks rooted in tort law, product liability and limited criminal doctrines are not corresponding to this grey area that addresses the distributed, opaque and autonomous nature of AI systems and agricultural failures.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
Series
Advances in Intelligent Systems Research
Publication Date
9 October 2026
ISBN
978-94-6239-791-0
ISSN
1951-6851
DOI
10.2991/978-94-6239-791-0_35How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Arushi M. Mehta
AU  - Simran Singh
PY  - 2026
DA  - 2026/10/09
TI  - When Algorithms Fail the Farm: Rethinking Liability Frameworks for AI in Agriculture — A Comparative Study of India, the EU, and the United States
BT  - Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
PB  - Atlantis Press
SP  - 467
EP  - 478
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-791-0_35
DO  - 10.2991/978-94-6239-791-0_35
ID  - Mehta2026
ER  -