Centre for Applied Research of the Faculty of Digital Media & Creative Industries
S. Horsman (Sophie)
Lecturer ResearcherSophie Horsman is lecturer-researcher 'Responsible AI' at the Hogeschool van Amsterdam. She is a researcher within the Responsible IT lectorate. In addition, Sophie teaches the course 'Philosophy and Ethics' at the master Applied AI.
Education
Sophie completed an interdisciplinary bachelor's degree in Liberal Arts & Sciences at Utrecht University. She then completed two masters cum laude: a one-year master's in philosophy at Radboud University and a research master's in Artificial Intelligence at Utrecht University.
Research
During her master, Sophie did a graduate internship at TNO where she participated in several projects as an ethically trained researcher. In these, she studied how ethical decision-making takes place in AI projects. During her studies, she also did internships at the Rathenau Institute and the Digital Society School. Currently, Sophie is doing several research projects within the Responsible IT lectureship in the field of AI Ethics. Within the DRAMA project, for example, she worked on a study of bias in speech recognition that investigated the extent to which automatic speech recognition works well for everyone.
Motivation
With her interdisciplinary background, Sophie finds it interesting to study complex and social problems. She likes to look at problems from different lenses and methodologies. She enjoys doing practice-oriented research where the research results have a positive impact on society and individuals.
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Workshop on Responsible Applied Artificial InTelligence
van Dierendonck, R., Fuckner, M., Harbers, M., Horsman, S., van der Horst, T., Kok, F., Leijnen, S., Peters, M., Robben, S. M. B., & Wiggers, P. (2024). Workshop on Responsible Applied Artificial InTelligence. In Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI 2024) (Vol. 3825, pp. 180). CEUR-WS.
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Uncovering bias in ASR systems
Fuckner, M., Horsman, S., Janssen, I., & Wiggers, P. (2024). Uncovering bias in ASR systems: Evaluating the performance of Wav2vec2 and Whisper for Dutch speakers. Poster session presented at 2nd Dutch Speech Tech Day , Hilversum, Netherlands.
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Moralis machina
Veerman, M., Horsman, S., Silvis, J., Westplat, Y., & Jones, P. (2023). Moralis machina: Kaartspel voor overheidsorganisaties om hun ideale AI-gebruik te bepalen. Artefact, Hogeschool van Amsterdam.
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DRAMA – Op weg naar inclusieve spraakherkenning
Horsman, S., Fuckner, M., & Wiggers, P. (2023). DRAMA – Op weg naar inclusieve spraakherkenning. Web publication or website, RAAIT. https://raait.nl/kennisbank/inclusieve-spraakherkenning/
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Uncovering Bias in ASR Systems
Fuckner, M., Horsman, S., Wiggers, P., & Janssen, I. (2023). Uncovering Bias in ASR Systems: Evaluating Wav2vec2 and Whisper for Dutch speakers. Paper presented at 2023 International Conference on Speech Technology and Human-Computer Dialogue (SpeD), Bucharest, Romania. https://ieeexplore.ieee.org/document/10314895