Laura Schelenz

Schelenz, Laura (forthcoming): Diversity and Social Justice in Technology Design: Reflections on Diversity-aware Technology. In: International Journal of Critical Diversity Studies.

Helm, Paula; Loizos, Michael, Schelenz, Laura (2022): Diversity by Design? Balancing the Inclusion and Protection of Users in an Online Social Platform. In: AIES '22: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, https://doi.org/10.1145/3514094.3534149

Martinez Demarco, Sol; Schelenz, Laura (2022): Diversity and Technology. A Zine. Internationales Zentrum für Ethik in den Wissenschaften. Materialien zur Ethik in den Wissenschaften; 21. ISBN: 978-3-935933-20-9.

Schelenz, Laura (2022): Diversity Concepts in Computer Science and Technology Development: A Critique. In Science, Technology, & Human Values. DOI: https://doi.org/10.1177/01622439221122549

Schelenz, Laura (2022): Artificial Intelligence Between Oppression and Resistance: Black Feminist Perspectives on Emerging Technologies. In Ariane Hanemaayer (Ed.): Artificial Intelligence and Its Discontents. Cham: Springer International Publishing (Social and Cultural Studies of Robots and AI), pp. 225–249.

Schelenz, Laura; Vondermaßen, Marcel (2022): Diversity, Identity, Oppression: The Construction of “Blackness” in Dear White People. In Open Philosophy 5 (1), pp. 44–56. DOI: 10.1515/opphil-2020-0171.

Schelenz, Laura; Bison, Ivano; Busso, Matteo; de Götzen, Amalia; Gatica-Perez, Daniel; Giunchiglia, Fausto; Meegahapola, Lakmal; Ruiz-Correa, Salvador (2021): The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations. In: AIES '21: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. https://doi.org/10.1145/3461702.3462595

Schelenz, Laura (2021): Diversity-aware Recommendations for Social Justice? Exploring User Diversity and Fairness in Recommender Systems. In Judith Masthoff, Eelco Herder, Nava Tintarev, Marko Tkalčič (Eds.): Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization. UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization. Utrecht Netherlands, 21 06 2021 25 06 2021. New York, NY, USA: ACM, pp. 404–410.

Schelenz, Laura; Pawelec, Maria (2021): Information and Communication Technologies for Development (ICT4D) critique. In Information Technology for Development, pp. 1–24. DOI: 10.1080/02681102.2021.1937473.

Schelenz, Laura; Segal, Avi; Gal, Kobi (2020): Best Practices for Transparency in Machine Generated Personalization. In Tsvi Kuflik, Ilaria Torre, Robin Burke, Cristina Gena (Eds.): Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization. UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization. Genoa Italy, 14 July 2020 - 17 July 2020. New York, NY, USA: ACM, pp. 23–28.

“Diversity by Design: Balancing Protection and Inclusion in Social Networks.” AITHICS 2021 workshop at the German Conference on Artificial Intelligence (KI2021), 27 September 2021.

“Diversity-aware Recommendations for Social Justice? Exploring User Diversity and Fairness in Recommender Systems.” Fair UMAP Workshop @ ACM UMAP 2021, 25 June 2021.

“Diversity-aware Technology: a Concept and Method for Social Justice-Oriented Design.” Lecture, Aalborg University, Copenhagen, Denmark, 21 April 2021.

“Diversity-aware Technology: a Concept and Method for Increased Social Justice in Computer Systems.” Know-Dive Seminar at the University of Trento, Italy, 4 November 2020.

“Applying Transparency in Artificial Intelligence based Personalization Systems.” With Avi Segal. Presentation at the Virtual Human-AI Interaction Workshop (HAIW), European Conference on Artificial Intelligence (ECAI). 8 September 2020.

 “Best Practices for Transparency in Machine-Generated Personalization.” With Avi Segal. Presentation at the Virtual ACM Conference on User Modelling and Adaptive Technologies. 16 July 2020.

“Diversity and Discrimination in Social Networking: Diversity Aware Technology from a Black Feminist Perspective” (2019-2023)

In her dissertation, Laura explores and discusses how Black feminist theory can be harnessed to design and develop “diversity-aware technology.” A growing field in the computer sciences sees technology as a solution to societal challenges and wants to leverage ethical AI for social good. At the same time, scholarly communities in the computer sciences warn of algorithmic discrimination and the reinforcement of societal challenges in and through technology. “Diversity-aware technology” sits in between the two movements and may present an alternative to the status quo. Diversity-aware technology takes into account the diversity of users but at the same time has a normative component that demands inclusion of diverse user groups. While this seems innovative, there are challenges. Diversity-aware technology builds on categories of difference that “sort” users into groups and imply expectations towards their behavior. How can we theorize diversity-aware technology so that it does not reinforce biased conceptualizations of diverse users? How can diversity-aware technology promote social justice? The dissertation draws on a Black feminist framework to answer these questions and explore the opportunities and limitations of diversity-aware technology.

Supervisors: Prof. Dr. Astrid Franke, American Studies Department at University of Tübingen; Prof. Dr. Daniel Gatica-Perez, Social Computing Group at IDIAP, EPFL in Switzerland