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India’s latest report on Non Personal Data, published by the Union Ministry of Electronics and Information Technology’s (MEITY) Committee of Experts has defined parameters regarding who can seek Non Personal Data, High Value Datasets, what a community is and who can represent it as a trustee, rights over non personal data, sovereign access to data, meta-data directories, and addressed intellectual property concerns. They’ve exempt entire raw databases from data requests, taken private data access out of the ambit of this framework, and defined purposes for which data can be accessed. Above all, it recommends a separate Non Personal Data legislation for governing NPD.
India’s Revised Non-Personal Data Report: Less Than Meets the Eye
By Nikhil Sud
In July last year, an expert committee established by the Ministry of Electronics and Information Technology (MEITY) released a report on the Non-Personal Data (NPD) Governance Framework for India. My analysis of that report argued that the report had five key shortcomings that could undermine the report’s praiseworthy vision. In December 2020, the committee released an amended report, commendably taking several steps to remedy those shortcomings. However, scratching beneath the surface reveals that some of those steps are less reassuring than they seem.
1. The amended report only partly remedies the original’s flawed approach to competition law
Key takeaways:
Government has carte blanche: Both Personal Data Protection Bill, 2019 and the expert committee report on Non Personal Data give the government wide-ranging powers to collect and analyse data, without adequate safeguards
GDPR not ‘revolutionary’: GDPR only evolved existing privacy and data protection laws, it did not radically alter how companies collect and use data
Inferred data needs to be dealt specifically: There is a need to strenghten specific provisions to safeguard individual libery and community rights when it comes to inferred data
Privacy within context of hierarchies: Need to think of privacy within contexts and in terms of hierarchies, when swathes of data are analysed by artificial intelligence and automated tools
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