Personal data monetisation model in India : Reimagining the contours of the Digital Personal Data Protection Act, 2023 through a market-oriented approach analysis
In the digital age, ensuring data privacy has become increasingly difficult as businesses leverage personal data for profit, often at the expense of individual autonomy. This challenge is exacerbated in India by the Digital Personal Data Protection (DPDP) Act, 2023, which adopts a market-oriented approach, prioritising data processing and economic interests over robust privacy safeguards. The Act deepens existing asymmetries in bargaining power, allowing businesses to exploit the commercial value of personal data while individuals receive no direct benefit. In a society where privacy awareness is limited and financial vulnerability is widespread, this imbalance further exposes individuals to the risks of exploitation and surveillance. To address these concerns, this paper proposes a personal data monetisation model designed to strike a balance between commercial interests and consumer rights. By enabling individuals to license their personal data to businesses in exchange for monetary compensation, the model seeks to restore autonomy and ensure that the economic value of data accrues to its rightful owners. The operationalisation of this model, however, raises critical questions, including how to determine data value, protect privacy in a surveillance-driven economy and address the risks of centralising consent management. This paper critically examines these challenges and explores pathways to implement a framework that aligns economic empowerment with the preservation of privacy as a fundamental right, fostering a more equitable digital ecosystem.
Authors
- Sı́lvia Simon (ORCID: https://orcid.org/0000-0003-4935-1824)
- PK Singh
Publication Details
- Journal
- Journal of data protection & privacy.
- Published
- 2025-03-01
- DOI
- https://doi.org/10.69554/xdrr7205
- Primary Topic
- Privacy, Security, and Data Protection
- Type
- article
- Field-Weighted Citation Impact
- 0.00