Digital Delivery and Data System for Farmer Income Support
This report, jointly published by the Centre for Internet & Society and Privacy International, highlights the digital systems deployed by the government to augment farmer income. It analyses the PM-Kisan and Kalia schemes in Odisha and Andhra Pradesh.
Executive Summary
This study provides an in-depth analysis of two direct cash transfer schemes in India – Krushak Assistance for Livelihood and Income Augmentation (KALIA) and Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) – which aim to provide income support to farmers. The paper examines the role of data systems in the delivery and transfer of funds to the beneficiaries of these schemes, and analyses their technological framework and processes.
We find that the use of digital technologies, such as direct benefit transfer (DBT) systems, can improve the efficiency and ensure timely transfer of funds. However, we observe that the technology-only system is not designed with the last beneficiaries in mind; these people not only have no or minimal digital literacy but are also faced with a lack of technological infrastructure, including internet connectivity and access to the system that is largely digital.
Necessary processes need to be implemented and personnel on the ground enhanced in the existing system, to promptly address the grievances of farmers and other challenges.
This study critically analyses the direct cash transfer scheme and its impact on the beneficiaries. We find that despite the benefits of direct benefit transfer (DBT) systems, there have been many instances of failures, such as the exclusion of several eligible households from the database.
The study also looks at gender as one of the components shaping the impact of digitisation on beneficiaries. We also identify infrastructural and policy constraints, in sync with the technological framework adopted and implemented, that impact the implementation of digital systems for the delivery of welfare. These include a lack of reliable internet connectivity in rural areas and low digital literacy among farmers. We analyse policy frameworks at the central and state levels and find discrepancies between the discourse of these schemes and their implementation on the ground.
We conclude the study by discussing the implications of datafication, which is the process of collecting, analysing, and managing data through the lens of data justice. Datafication can play a crucial role in improving the efficiency and transparency of income support schemes for farmers. However, it is important to ensure that the interests of primary beneficiaries are considered – the system should work as an enabling, not a disabling, factor. This appears to be the case in many instances since the current system does not give primacy to the interests of farmers. We offer recommendations for policymakers and other stakeholders to strengthen these schemes and improve the welfare of farmers and end users.
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