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In the data analytics society, each individual’s disclosure of personal information imposes costs on others. This disclosure enables companies, deploying novel forms of data analytics, to infer new knowledge about other people and to use this knowledge to engage in potentially harmful activities. These harms go beyond privacy and include difficult to detect price discrimination, preference manipulation, and even social exclusion. Currently existing, individual-focused, data protection regimes leave law unable to account for these social costs or to manage them.  This Article suggests a way out, by proposing to re-conceptualize the problem of social costs of data analytics through the new frame of “data management law.” It offers a critical comparison of the two existing models of data governance: the American “notice and choice” approach and the European “personal data protection” regime (currently expressed in the General Data Protection Regulation). Tracing their origin to a single report issued in 1973, the article demonstrates how they developed differently under the influence of different ideologies (market-centered liberalism, and human rights, respectively). It also shows how both ultimately failed at addressing the challenges outlined already forty-five years ago.  To tackle these challenges, this Article argues for three normative shifts. First, it proposes to go beyond “privacy” and towards “social costs of data management” as the framework for conceptualizing and mitigating negative effects of corporations’ data usage. Second, it argues to go beyond the individual interests, to account for collective ones, and to replace contracts with regulation as the means of creating norms governing data management. Third, it argues that the nature of the decisions about these norms is political, and so political means, in place of technocratic solutions, need to be employed.

Data Management Law for the 2020s: The Lost Origins and the New Needs