<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>This article examines what kind of personal data disclosure may make it difficult to get employed and what kind of excessive (unlawful) data is collected when selecting candidates in Lithuania. The analysis reveals that there have been a number of justified complaints regarding the selection of employees via recruitment platforms and the provided application forms that specifically requested an excessive amount of information, or situations in which the conditions indicated in job listings were adapted to a specific circle of people, thus eliminating other potential candidates, such as persons of pre-retirement age, young families, persons with children, persons of a particular gender and similar groups of people. The purpose of this article is to identify methods of unlawful collection of personal data, as well as the types of requested personal data, the origin of which may lead to discrimination during the recruitment process in Lithuania. The article analyses the legality of documents requested from candidates, data collected from them by filling out application forms and providing preliminary or additional information during job interviews, or information gathered from former employers or social networks.</p>
</abstract>

This article examines what kind of personal data disclosure may make it difficult to get employed and what kind of excessive (unlawful) data is collected when selecting candidates in Lithuania. The analysis reveals that there have been a number of justified complaints regarding the selection of employees via recruitment platforms and the provided application forms that specifically requested an excessive amount of information, or situations in which the conditions indicated in job listings were adapted to a specific circle of people, thus eliminating other potential candidates, such as persons of pre-retirement age, young families, persons with children, persons of a particular gender and similar groups of people. The purpose of this article is to identify methods of unlawful collection of personal data, as well as the types of requested personal data, the origin of which may lead to discrimination during the recruitment process in Lithuania. The article analyses the legality of documents requested from candidates, data collected from them by filling out application forms and providing preliminary or additional information during job interviews, or information gathered from former employers or social networks.

Discrimination on the Basis of Personal Data in Employment: The Case Study of Lithuania

Baltic Journal of Law & Politics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This article examines what kind of personal data disclosure may make it difficult to get employed and what kind of excessive (unlawful) data is collected when...

Discrimination on the Basis of Personal Data in Employment: The Case Study of Lithuania

Online veröffentlicht: 26. Okt. 2023

Seitenbereich: 24 - 41

Eingereicht: 23. Nov. 2022

Akzeptiert: 06. März 2023

DOI: https://doi.org/10.2478/bjlp-2023-0002

Schlüsselwörter
Personal data, discrimination, digital platforms, selection of candidates, equal opportunities, artificial intelligence (AI).

© 2023 Ingrida Mačernytė-Panomariovienė, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Discrimination on the Basis of Personal Data in Employment: The Case Study of Lithuania

Online veröffentlicht: 26. Okt. 2023

Seitenbereich: 24 - 41

Eingereicht: 23. Nov. 2022

Akzeptiert: 06. März 2023

DOI: https://doi.org/10.2478/bjlp-2023-0002

SchlüsselwörterPersonal data, discrimination, digital platforms, selection of candidates, equal opportunities, artificial intelligence (AI).

© 2023 Ingrida Mačernytė-Panomariovienė, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Personal data, discrimination, digital platforms, selection of candidates, equal opportunities, artificial intelligence (AI).