Panchayati Raj & Indigenous Model of Data Governance

Introduction

Data is a valuable asset in today's world, and has now come to be an intrinsic part of our daily lives. With the advancement of technology, our personal, professional, and social information is constantly collected, stored, and processed, by various digital platforms which have since infiltrated our lives. The Digital Personal Data Protection (DPDP) Act, 2023, was therefore enacted with the aim of safeguarding individual privacy. However, it is noteworthy that this act adopts a centralized governance structure. Such an approach to data governance is largely influenced by the European Union’s General Data Protection Regulation (GDPR), and consequently strays away from the indigenous community-centric ideology present in India. As such, arises the need for an alternative model of data governance that truly reflects the Indian idea of self-rule or Swaraj.

The Problem of Centralization in the DPDP Act & its Indigenous Solution

The DPDP Act promotes a centralized form of governance, which is naturally opposed to the indigenous community-driven society; as a result, citizens are kept far away from the decision-making processes regarding their data. Unlike the Western emphasis on individualism and liberal privacy, Indian governance has historically leaned towards community participation and local self-governance. This principle is also embedded in the country’s Panchayati Raj system, which constitutionally embodies the notion of local self-rule under the 73rd Amendment introduced Part IX and Schedule 11 of the Constitution of India.

Drawing inspiration from this grass root level governance traditions, a Panchayati Raj-based data governance framework appears not only feasible but also necessary for true “good data governance”. This model can decentralize data oversight, bringing governance closer to the people and enabling participative protection of personal and community data.

A similar ideology of self-governance can be observed in the case of Smithsonian Institutes which have issued certain notices reflecting the CARE principles. With this, they try to ensure that collective cultural material or data cannot be reused without prior consent or discussion with the indigenous people.

Panchayati Data Governance Model

The Panchayati-Raj driven community model of data protection proposes the establishment of Village Data Committees (VDCs) at the Gram Panchayat and Municipal Corporation level. These committees would oversee local data collection, ensure fair and informed consent of the community to such collection & storage, and act as an immediate redressal body for grievances concerning data misuse. It is proposed that the VDCs should consist of community-acknowledged representatives, citizen volunteers, and digital literacy facilitators. As such, these VDC would function as the first line of defense for data rights at the village level.

Further, the concept of community data fiduciaries can also be introduced as against the centralized form of data fiduciaries present in the DPDP Act,2023. While individual consent shall remain an essential element, community-held data, such as collective health records or village demographic information can be managed by these fiduciaries on behalf of the community. This not only decentralizes control but also preserves the collective integrity of data that inherently belongs to the community as a whole.

Furthermore, these VDCs reflect the international CARE principles. CARE stands for - collective benefit, authority to control, responsibility, and ethics. These principles try to ensure that data governance is socially accountable and ethically transparent.

The proposed model not only enables participative data governance bringing it closer to the people, it also ensures greater transparency and community trust. Such localization can reduce the exploitation stemming from the uninformed consent of individuals and create a participatory ecosystem where citizens are actively involved in decisions regarding their personal and communal data.

Challenges

While the proposed model closely aligns with indigenous community-driven governance, it has its own set of crucial drawbacks.

• To quote Mansuri and Rao (2013), decentralized institutions often face the risk of being dominated by influential local figures who might manipulate community processes for personal gain. The same could prove to be true for the proposed model with local elites gaining undue control due to their influence on the said community. Without adequate safeguards, data governance committees could become yet another institution for reinforcing existing local power dynamics.
• Another challenge is that of diverse self-governance structures. Differences and variations in local standards, practices, and capacities may lead to inconsistencies in data protection across regions. This could hinder the implementation of uniform national digital regulations and create loopholes in the system.
• Stemming from the above is yet another concern regarding the decentralized framework which might dilute the uniform enforcement of data protection principles, consequentially creating ambiguities between local and central authorities.
• One of the most crucial of all the drawbacks is the current infrastructural and capacity limitations of many Panchayati Raj Institutions. It raises concerns about their capability to handle the technical complexities of data governance.

Addressing the Challenges

Although these criticisms are valid, they can easily be addressed.

• Local Panchayati Raj Institutions can handle community-specific data governance, while the central Data Protection Board sets minimum national standards, ensures regulatory consistency, and deals with extremely sensitive data.
• Furthermore, with regular audits by independently appointed agencies, alongside mandatory public disclosure of decisions, we can mitigate the risks of undue influence of local elites in the system and enhance its accountability. Publicly accessible records of data processing decisions can further protect the system from local political influence.
• Regarding the existing digital divide in rural India, it is necessary to invest in government-sponsored digital literacy programs specifically tailored for Panchayati Raj members. Training workshops should be conducted which would include modules on the DPDP Act, cybersecurity, and ethical data handling. These can enable the local bodies to make informed decisions and effectively carry out their duties.

Conclusion

This decentralized yet structured approach to data governance can effectively blend India’s indigenous traditions with modern governance frameworks. It enables the participatory form of community-driven governance and the philosophy of Swaraj while also ensuring that India’s digital governance remains functioning and relevant.

In conclusion, as stated by Gandhiji in Hind Swaraj (1909), true self-rule lies not merely in political independence but in the ability of communities to self-govern. Applying this principle to the digital realm through a Panchayati Raj-based data governance model can create an indigenous Indian model of data protection that neither blindly follows Western frameworks nor remains bounded in centralization.

References:

1. M.K. Gandhi, Hind Swaraj (Navajivan Publ’g House 1909), https://www.gandhiheritageportal.org/gu/bookdetail/MTEwOTg=/hind-swaraj.
2. L. van Kempen, Book Review, Localizing Development: Does Participation Work?, by Ghazala Mansuri & Vijayendra Rao, 112 J. Econ. 201, 201–205 (2014), http://www.jstor.org/stable/43574374.
3. Stephanie Russo Carroll et al., The CARE Principles for Indigenous Data Governance, 19 Data Sci. J. 43 (2020), https://doi.org/10.5334/dsj-2020-043.
4. The Digital Personal Data Protection Act, 2023, No. 30, Acts of Parliament, 2023 (India), https://www.meity.gov.in/content/digital-personal-data-protection-act-2023.
5. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the Protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of Such Data (General Data Protection Regulation) (GDPR), 2016 O.J. (L 119) 1, https://eur-lex.europa.eu/eli/reg/2016/679/oj.

Note:

The author affirms that this article is an entirely original work, never before submitted for publication at any journal, blog or other publication avenue. Any unintentional resemblance to previously published material is purely coincidental. This article is intended solely for academic and scholarly discussion. The author takes personal responsibility for any potential infringement of intellectual property rights belonging to any individuals, organizations, governments, or institutions.