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Auflistung nach Schlagwort "Algorithmic Experience"

1 - 2 von 2
  • Workshopbeitrag
    Audit, Don’t Explain – Recommendations Based on a Socio-Technical Understanding of ML-Based Systems
    (Mensch und Computer 2021 - Workshopband, 2021) Heuer, Hendrik
    In this position paper, I provide a socio-technical perspective on machine learning-based systems. I also explain why systematic audits may be preferable to explainable AI systems. I make concrete recommendations for how institutions governed by public law akin to the German TÜV and Stiftung Wartentest can ensure that ML systems operate in the interest of the public.
  • Konferenzbeitrag
    Unpacking a model: An interactive visualization of a text similarity algorithm for legal documents
    (Mensch und Computer 2019 - Tagungsband, 2019) Soroko, Daria; Ndöge, Nina; Al-Shafeei, Ahmed; Heuer, Hendrik
    This paper presents a functional prototype for an interactive web-based interface i_sift developed to foreground the decision-making process of an algorithm that detects similarities in legal texts through word embeddings. Using this as a case study in Computational Social Science, our goal is, first, to highlight the importance of making computational tools and methods transparent to social scientists. Secondly, we suggest an approach that accomplishes this using methods and principles from Interactive Machine Learning and the Algorithmic Experience framework.