Abstract
The advent of Big Data coupled with the profiling of users has lead to the development of services and decision-making processes that are highly personalized, but also raise fundamental privacy and ethical issues. In particular, the absence of transparency has lead to the loss of control of individuals on the collection and use on their personal information while making it impossible for an individual to question the decision taken by the algorithm and to make it accountable for it. Nonetheless, transparency is only a prerequisite to be able to analyze the possible biases that personalized algorithms could have (e.g., discriminating against a particular group in the population) and then potentially correct them. In this position paper, I will review in a non-exhaustive manner some of the main privacy and ethical challenges associated with Big Data that have emerged in recent years before highlighting a few approaches that are currently investigated to address these challenges.
Sébastien Gambs is supported by the Canada Research Chair program as well as by a Discovery Grant and a Discovery Accelerator Supplement Grant from NSERC.
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Gambs, S. (2019). Privacy and Ethical Challenges in Big Data. In: Zincir-Heywood, N., Bonfante, G., Debbabi, M., Garcia-Alfaro, J. (eds) Foundations and Practice of Security. FPS 2018. Lecture Notes in Computer Science(), vol 11358. Springer, Cham. https://doi.org/10.1007/978-3-030-18419-3_2
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