In the last few blogs, we discussed some fundamentals of privacy theory – spanning the historical origins of the ‘right to privacy’ in legal jurisprudence in the USA, to contemporary scholarship delving into the implications of data-driven and machine learning environments for our understandings of privacy. This week, we list out some critical scholarship on the theoretical foundations of privacy, and its relationship with regulatory practice in India (apart from the readings already listed).
A few months ago, two Uber drivers from the United Kingdom, Azeem Hanif and Alfie Wellcoat filed a case against Uber alleging discrimination by its algorithm. They brought the case in a District Court in Amsterdam, where Uber’s headquarters is located. One of their central claims is that Uber’s algorithmic interference determines the nature of their rides: which drivers get the short ride or the nice ride, and the other way round. The automated decision-making process lacks transparency and is based on arbitrary factors, they allege, and drivers are in the dark about how the AI decides these questions.
In the last few posts, we posed some questions for algorithms as an artefact for governance, including the implications of different forms of algorithms embedded in computing and information infrastructure, their relationships with governing and administration, and their relevance for specific legal domains. Here, we share some readings to critically study, understand and critique algorithmic systems are particularly relevant for lawyers.
In the last post, we examined the Government of India’s Draft Report on Non-Personal Data, and its justifications for regulating NPD for ‘economic benefit’. This post examines the concept of ‘group privacy’, which has been presented as a justification for the regulation of NPD.
In the previous post, we introduced the Draft Report of the Committee on Non-Personal Data Regulation and analyzed its conception of ‘Non-Personal Data’ (“NPD”) as a category for regulation. There, we wrote about how the contours of NPD (as defined under the Draft Report) will necessarily entail conflicts with the proposed personal data protection regime in India. In this post, we set out to examine and critique the Committee’s justifications for why ‘Non-Personal Data’ should be regulated, in particular, on the ‘economic value’ justification for regulation.
By all accounts, we are in the midst of an ‘information revolution’. Like technological revolutions…