Profilowanie pomocy dla bezrobotnych – dotychczasowe doświadczenia i nowe wyzwania z perspektywy praw człowieka

Author:

Kuba Magdalena1ORCID,Staszewska Ewa2ORCID

Affiliation:

1. Kozminski University, Warsaw, Poland; University of Łódź, Łódź, Poland

2. University of Łódź, Łódź, Poland

Abstract

Profiling help for the unemployed – past experiences and new challenges from a human rights perspective The dynamic development of modern information and communication technologies, enabling data collection on a much larger scale than before, has contributed to a change in the way services are provided also in the public sector. It is noticeable, among others, in the area of labor market policy, where tools based on profiling are used, understood as developing profiles of people on the basis of specific data and inferring on their basis the occurrence of certain characteristics or behaviors in people assigned to a given profile. Experiences in this area on the ground of Polish legal regulations show what consequences the use of profiling may have in the context of providing help to the unemployed. The aim of this article is to analyze the issue of profiling on the basis of regulations on personal data protection and labor market regulations as well as to identify threats related to the use of profiling in the area of providing help to the unemployed from the perspective of human rights.

Publisher

Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego

Reference52 articles.

1. 1. Bouckaert D. i in. (2017) VDAB op koers voor een datagedreven aanpak met big data, "Over Werk", nr 2.

2. 2. Chomiczewski W. (2016) Profilowanie w ogólnym rozporządzeniu o ochronie danych [w:] E. Bielak-Jomaa, D. Lubasz (red.), Polska i europejska reforma ochrony danych osobowych, Warszawa.

3. 3. Czerniawski M. (2018) [w:] E. Bielak-Jomaa, D. Lubasz (red.), RODO. Ogólne rozporządzenie o ochronie danych. Komentarz, Warszawa.

4. 4. Desiere S., Langenbucher K., Struyven L. (2019) Statistical Profiling in Public Employment Services: An International Comparison, OECD Social, Employment and Migration Working Papers, No. 224.

5. 5. Desiere S., Struyven L. (2021) Using Artificial Intelligence to Classiffy Jobseekers: The Accuracy-Equity Trade Off, "Journal of Social Policy", Vol. 50, Issue 2.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3