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The Data Delusion

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The Data Delusion: Protecting Individual Data Isn't Enough When The Harm is Collective

Author: Martin Tisné, Managing Director, Luminate

Editor: Marietje Schaake, International Policy Director, Cyber Policy Center

The threat of digital discrimination

On March 17, 2018, questions about data privacy exploded with the scandal of the previously unknown consulting company Cambridge Analytica. Lawmakers are still grappling with updating laws to counter the harms of big data and AI.

In the Spring of 2020, the Covid-19 pandemic brought questions about sufficient legal protections back to the public debate, with urgent warnings about the privacy implications of contact tracing apps. But the surveillance consequences of the pandemic’s aftermath are much bigger than any app: transport, education, health systems and offices are being turned into vast surveillance networks. If we only consider individual trade-offs between privacy sacrifices and alleged health benefits, we will miss the point. The collective nature of big data means people are more impacted by other people’s data than by data about them. Like climate change, the threat is societal and personal.

In the era of big data and AI, people can suffer because of how the sum of individual data is analysed and sorted into groups by algorithms. Novel forms of collective data-driven harms are appearing as a result: online housing, job and credit ads discriminating on the basis of race and gender, women disqualified from jobs on the basis of gender and foreign actors targeting light-right groups, pulling them to the far-right. Our public debate, governments, and laws are ill-equipped to deal with these collective, as opposed to individual, harms.

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