Navigating Privacy Issues in Gathering Training Data for AI: A Case Study of Google and Zoom
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14220%2F24%3A00138603" target="_blank" >RIV/00216224:14220/24:00138603 - isvavai.cz</a>
Result on the web
<a href="https://edpl.lexxion.eu/article/EDPL/2024/4/5" target="_blank" >https://edpl.lexxion.eu/article/EDPL/2024/4/5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21552/edpl/2024/4/5" target="_blank" >10.21552/edpl/2024/4/5</a>
Alternative languages
Result language
angličtina
Original language name
Navigating Privacy Issues in Gathering Training Data for AI: A Case Study of Google and Zoom
Original language description
This article focuses on the privacy concerns related to the use of personal data in training generative AI tools under EU law. It examines common techniques for acquiring personal data for training new AI systems by tech companies, mainly focusing on the legal basis for processing such personal data. The lawfulness of scraping data from the internet and using data generated by users of a service will be evaluated thanks to a specific case analysis of the practices employed by Google and Zoom. The unlawfulness and breach of GDPR by Google and the dubious response to customer backlash done by Zoom are put into perspective and the limits of privacy regulation dealing with big technological companies are briefly explored as well as the public responses to the privacy threatening techniques used by these companies.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50501 - Law
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Data Protection Law Review
ISSN
2364-2831
e-ISSN
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Volume of the periodical
10
Issue of the periodical within the volume
4
Country of publishing house
DE - GERMANY
Number of pages
13
Pages from-to
336-348
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85219032192