Artificial Intelligence, Surveillance, and Big Data
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Autor/Autorin: | Karpa, David Klarl, Torben Rochlitz, Michael |
Herausgeber: | Diginomics Research Group | Zusammenfassung: | The most important resource to improve technologies in the field of artificial intelligence is data. Two types of policies are crucial in this respect: privacy and data-sharing regulations, and the use of surveillance technologies for policing. Both types of policies vary substantially across countries and political regimes. This chapter examines how authoritarian and democratic political institutions can influence the quality of research in artificial intelligence, and the availability of large-scale datasets to improve and train deep learning algorithms. We focus mainly on the case of China, and find that – ceteris paribus – authoritarian political institutions continue to have a negative effect on innovation. They can, however, have a positive effect on research in deep learning, via the availability of large-scale datasets that have been obtained through government surveillance. We propose a research agenda to study which of the two effects might dominate in a race for leadership in artificial intelligence between countries with different political institutions, such as the United States and China. |
Schlagwort: | artificial intelligence; surveillance; big data | Veröffentlichungsdatum: | 30-Mai-2022 | Serie: | Diginomics Working Paper | Band: | 0016 | Dokumenttyp: | Bericht, Report | ISSN: | 2701-6307 | Zweitveröffentlichung: | no | DOI: | 10.26092/elib/1570 | URN: | urn:nbn:de:gbv:46-elib59650 | Institution: | Universität Bremen | Fachbereich: | Fachbereich 07: Wirtschaftswissenschaft (FB 07) | Institut: | Diginomics Research Group |
Enthalten in den Sammlungen: | Forschungsdokumente |
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