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    Do regulatory efforts in Europe regarding algorithmic discrimination caused by private actors offer emancipation for women and other marginalized groups?
    (İstanbul Bilgi Üniversitesi, 2022) Erden, Deniz; Keser Berber, Leyla
    ABSTRACT: Discovery of automated extraction and processing of personal data as a massively profitable economic activity led to the new online public spheres to be intermediated by a few large corporations making use of advanced technologies to collect, manage and analyse vast amounts of data in providing real-time services. This enables significant decisions about individuals made by private companies such as access to employment and credit to be automated. Machine learning algorithms used in these ADM processes have notoriously found to be discriminating against WMG. Some argue that it is easier to fix these systems to overcome bias that is an inherent property in humans, while others argue that they are more likely to perpetuate and cement power relations in the society without regulatory intervention. Europe has become a global trendsetter on tech regulation as well as being at the forefront of democracy and human rights protection. This thesis aims at evaluating the main legislations in the EU that would apply in erecruitment context which falls under similarly significant category in Article 22 GDPR and likely to result in a high risk for the rights and freedoms of individuals, arguing that transparency and accountability obligations under GDPR could be interpreted in a manner to enhance both ex ante and ex post protection against risks of algorithmic discrimination and its human rights implications in a democratic society in combination with the EU antidiscrimination law. On the other hand, several remaining loopholes are identified, by critically questioning the role of power relations in shaping underlying values and methods of the applicable law, technologies and business models by taking an intersectional feminist stance.