@article{47293, author = {{Dunlap, Trevor and Acar, Yasemin and Cucker, Michel and Enck, William and Kapravelos, Alexandros and Kästner, Christian and Williams, Laurie A.}}, journal = {{CoRR}}, title = {{{S3C2 Summit 2023-02: Industry Secure Supply Chain Summit}}}, doi = {{10.48550/arXiv.2307.16557}}, volume = {{abs/2307.16557}}, year = {{2023}}, } @article{47292, author = {{Enck, William and Acar, Yasemin and Cukier, Michel and Kapravelos, Alexandros and Kästner, Christian and Williams, Laurie A.}}, journal = {{CoRR}}, title = {{{S3C2 Summit 2023-06: Government Secure Supply Chain Summit}}}, doi = {{10.48550/arXiv.2308.06850}}, volume = {{abs/2308.06850}}, year = {{2023}}, } @inproceedings{47298, author = {{Mink, Jaron and Kaur, Harjot and Schmüser, Juliane and Fahl, Sascha and Acar, Yasemin}}, booktitle = {{32nd USENIX Security Symposium, USENIX Security 2023, Anaheim, CA, USA, August 9-11, 2023}}, editor = {{Calandrino, Joseph A. and Troncoso, Carmela}}, publisher = {{USENIX Association}}, title = {{{"Security is not my field, I’m a stats guy": A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry}}}, year = {{2023}}, } @article{47295, author = {{Amft, Sabrina and Höltervennhoff, Sandra and Huaman, Nicolas and Krause, Alexander and Simko, Lucy and Acar, Yasemin and Fahl, Sascha}}, journal = {{CoRR}}, title = {{{Lost and not Found: An Investigation of Recovery Methods for Multi-Factor Authentication}}}, doi = {{10.48550/arXiv.2306.09708}}, volume = {{abs/2306.09708}}, year = {{2023}}, } @inproceedings{48355, abstract = {{Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal. In this contribution, we take a closer look at the embedding vector representing the slowly varying signal components, commonly named the speaker embedding vector. We ask, which properties of a speaker's voice are captured and investigate to which extent do individual embedding vector components sign responsible for them, using the concept of Shapley values. Our findings show that certain speaker-specific acoustic-phonetic properties can be fairly well predicted from the speaker embedding, while the investigated more abstract voice quality features cannot.}}, author = {{Rautenberg, Frederik and Kuhlmann, Michael and Wiechmann, Jana and Seebauer, Fritz and Wagner, Petra and Haeb-Umbach, Reinhold}}, booktitle = {{ITG Conference on Speech Communication}}, location = {{Aachen}}, title = {{{On Feature Importance and Interpretability of Speaker Representations}}}, year = {{2023}}, } @inproceedings{48410, author = {{Wiechmann, Jana and Rautenberg, Frederik and Wagner, Petra and Haeb-Umbach, Reinhold}}, booktitle = {{20th International Congress of the Phonetic Sciences (ICPhS) }}, title = {{{Explaining voice characteristics to novice voice practitioners-How successful is it?}}}, year = {{2023}}, } @article{46139, author = {{Schneider, Martin and Radermacher, Katharina}}, issn = {{0032-3446}}, journal = {{Wie Arbeitgeber strategisch gegen den Arbeitskräftemangel vorgehen.}}, number = {{580}}, publisher = {{Die politische Meinung}}, title = {{{Wie Arbeitgeber strategisch gegen den Arbeitskräftemangel vorgehen.}}}, year = {{2023}}, } @inproceedings{48285, author = {{Lebedeva, Anastasia and Kornowicz, Jaroslaw and Lammert, Olesja and Papenkordt, Jörg}}, booktitle = {{Artificial Intelligence in HCI}}, title = {{{The Role of Response Time for Algorithm Aversion in Fast and Slow Thinking Tasks}}}, doi = {{10.1007/978-3-031-35891-3_9}}, year = {{2023}}, } @inproceedings{47976, author = {{Papenkordt, Jörg and Ngonga-Ngomo, Axel-Cyrille and Thommes, Kirsten}}, booktitle = {{Academy of Management Proceedings}}, title = {{{Are Numbers or Words the Key to User Reliance on AI?}}}, doi = {{10.5465/AMPROC.2023.12946}}, year = {{2023}}, } @article{49157, abstract = {{ Service frontline encounters between customers and service providers have been subject to fundamental changes in recent years. As two major change agents, technology infusion and data privacy regulations are inextricably linked and constitute a critical ethical and societal issue. Specifically, service frontlines—as represented by human or technological agents, or some hybrid form—rely on customer data for service provision, which subjects them to privacy regulations governing the collection, submission, access, and use of any customer data thus captured. However, scant research outlines the significant implications of evolving data privacy regulations for service frontline encounters. To advance knowledge in this domain, this research distills six key dimensions of global data privacy regulations (fairness, data limits, transparency, control, consent, and recourse). Employing an intelligences theoretical lens, the authors theorize how these dimensions might become differentially manifest across three service frontline interface types (human-based, technology-based, and hybrid). Carefully intersecting the need for varying intelligences across data privacy regulatory dimensions with the abilities of service frontline interfaces to harness each intelligence type, this study offers a novel conceptual framework that advances research and practice. Theoretical, managerial, and policy implications unfold from the proposed framework, which also can inform a future research agenda. }}, author = {{Steinhoff, Lena and Martin, Kelly D.}}, issn = {{1094-6705}}, journal = {{Journal of Service Research}}, keywords = {{Organizational Behavior and Human Resource Management, Sociology and Political Science, Information Systems}}, number = {{3}}, pages = {{330--350}}, publisher = {{SAGE Publications}}, title = {{{Putting Data Privacy Regulation into Action: The Differential Capabilities of Service Frontline Interfaces}}}, doi = {{10.1177/10946705221141925}}, volume = {{26}}, year = {{2023}}, }