Artificial Intelligence and Big Data in the Age of COVID-19
Francisco J. Bariffi () and
Julia M. Puaschunder ()
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Francisco J. Bariffi: University Carlos III of Madrid, Spain
Julia M. Puaschunder: The New School, Department of Economics, School of Public Engagement, USA
RAIS Conference Proceedings 2021 from Research Association for Interdisciplinary Studies
The view that the COVID-19 pandemic has set in motion profound changes in our modern societies is practically unanimous. The global effort to contain, cure, and eradicate COVID-19 has been greatly benefited by the use, development and/or adaptation of technological tools for mass surveillance based on artificial intelligence and robotics systems. The management of the COVID-19 pandemic yet has also revealed many shortcomings generated from the need to make decisions â€œin extremisâ€ . Systematic lockdowns of entire populations pushed humans to increase exposure to digital devices in order to achieve some sort of social connection. Some nations with the capable technology development used AI systems to access individual digital data in order to control and contain the SARS-CoV-2. Massive surveillance of entire populations is now possible. In this way, the problem arises of how to establish an adequate balance and control between the utility and the results offered by mass surveillance systems based on artificial intelligence and robotics in the fight against COVID-19 on the one hand, and the protection of personal and collective fundamental rights and freedoms, on the other.
Keywords: Artificial Intelligence; AI; Anti-Discrimination; Big Data; COVID-19; COVID Long Haulers; Democratization of Healthcare Information; Digitalization; Healthcare; Human Rights; Massive Surveillance; Prevention; Tracking (search for similar items in EconPapers)
Pages: 9 pages
New Economics Papers: this item is included in nep-big, nep-cmp and nep-upt
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Published in Proceedings of the 24th International RAIS Conference on Social Sciences and Humanities, October 17-18, 2021, pages 1-9
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Persistent link: https://EconPapers.repec.org/RePEc:smo:lpaper:0115
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