Incorporating literature and expert interviews the thesis demonstrates the oppressive nature of algorithmic systems within new technologies and places considerable emphasis on the dimension of gender. Furthermore, it addresses the question of how and to which extent potential social implications are incorporated in algorithmic development stages and explores social implications of gender bias in algorithms as well as probable technical methods for addressing social repercussions of algorithm systems. Moreover, the thesis explores how to face the identified issues beforehand and provides answers with the help of literature and expert interviews in the fields of development and implementation of new technologies, digital education as well as personal data protection. Key problems and possible solutions are identified as follows: greater interdisciplinary cooperation among planning teams, engagement of as many relevant experts in the planning stages as possible, increased transparency of planning stages, diversification of data sources and unbiased data gathering, greater accountability of planners by providing regulatory frameworks, appropriate and timely policies, adequate supervisory structures as well as awareness-raising and education.
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