Anna-Lena Theus
ABSTRACT
The social sciences have a keen eye for the complex forces that shape our diverse experiences and excel in uncovering an issue's genesis by making sense of how the past has shaped the present. What is sometimes missing though is the practical application of this knowledge. Computer science disciplines and human-computer interaction on the other hand, are very skilled at identifying existing issues and at proposing practical solutions but sometimes miss to unpack and to scrutinize a problem's history and evolution. And while a lot of valuable domain specific knowledge exists, interdisciplinary socio-technical expertise is still scarce. This paper argues that a strong connection between these fields can counter the development of algorithmic systems that lead to inequitable consequences and instead support the design of algorithmic systems that result in more just outcomes and cultivate, what I call, affirmative algorithmic futures. To that end, this paper introduces a compendium of theoretical concepts and practical measures rooted in social science scholarship that foster socio-technical algorithmic system design practices and promote knowledge mobilization between disciplines.
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