Black Boxes in the Field: Trade Secrets, Algorithmic Opacity, and a Tiered Disclosure Framework for AgTech in India

DOI

10.2991/978-94-6239-791-0_34How to use a DOI?

Keywords

Trade Secrets; Algorithmic Accountability; AgTech; Plant Variety Protection; Comparative Intellectual Property Law

Abstract

Agricultural technology platforms in India have now been increasingly contributing to decisions that impact the farmers of the country significantly. This includes routine recommendations on what variety should preferably be planted, the amount of pesticide dosing. It also includes parametric crop insurance triggers under the Pradhan Mantri Fasal Bima Yojana and digital credit scoring channelled through the AgriStack framework. The machine learning models driving these decisions are protected as trade secrets. This generates a structural conflict between commercial confidentiality and accountability. India’s trade secrets regime is common-law driven. It is now poised for codification through the Protection of Trade Secrets Bill, 2024. This Act however was designed for static formulae and customer lists. It is therefore structurally ill-equipped to mediate the identified conflict in algorithmic decision-making. This paper uses a doctrinal method anchored in comparative studies to argue that AgTech trade secrets warrant differentiated treatment. This differentiated treatment implies disaggregating the protected asset. It would be divided into training data, model architecture, parameters, and outputs. These would then have customised disclosure obligations proportionate to the harm-potential of the agricultural decision the model informs. The paper draws on the EU Trade Secrets Directive (2016/943) [22], the US Defend Trade Secrets Act (2016), and the EU Artificial Intelligence Act (2024). Through these it extracts four borrowable mechanisms. These are - confidentiality clubs, risk-based classification, explanation rights, and regulator access models. The paper also assesses their feasibility under Indian institutional conditions. The paper proposes a three-tier disclosure framework. It gives an enforcement architecture and supports it by suggestions for concrete amendments to the proposed Trade Secrets Bill and sectoral interventions through the PPV&FR Authority and IRDAI.

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.

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TY  - CONF
AU  - Unmesha S. Patil
AU  - Apurva Bhilare
AU  - G. Manu Joseph
PY  - 2026
DA  - 2026/10/09
TI  - Black Boxes in the Field: Trade Secrets, Algorithmic Opacity, and a Tiered Disclosure Framework for AgTech in India
BT  - Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
PB  - Atlantis Press
SP  - 455
EP  - 466
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-791-0_34
DO  - 10.2991/978-94-6239-791-0_34
ID  - Patil2026
ER  -