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Results: 11
Number of items: 11
  • Open Access
    Starke, C., Kieslich, K., Reichert, M., & Köbis, N. (2026). Designing algorithms against corruption: a conjoint study on communicative features to encourage intentions for collective action. Journal of Information Technology and Politics, 23(3), 237–25. https://doi.org/10.1080/19331681.2025.2465326
  • Open Access
    Barnett, J., Kieslich, K., Helberger, N., & Diakopoulos, N. (2026). Informing AI Policy Assessment using Large-Scale Simulation of Interventions. In ACM FAccT 2026: Proceedings of the 9th annual ACM Conference on Fairness, Accountability, and Transparency : June 25-28, 2026, Montréal, Canada (pp. 3942-3978). Association for Computing Machinery. https://doi.org/10.1145/3805689.3812334
  • Open Access
    Barnett, J., Kieslich, K., Helberger, N., & Diakopoulos, N. (2025). Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Making. In ACM FAccT '25: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency : June 23-26, 2025, Athens, Greece (pp. 1424-1449). Association for Computing Machinery. https://doi.org/10.1145/3715275.3732096
  • Open Access
    Resendez, V., Kieslich, K., Helberger, N., & de Vreese, C. (2025). More Than Justifications an Analysis of Information Needs in Explanations and Motivations to Disable Personalization. Journalism Studies, 26(11), 1304-1312. https://doi.org/10.1080/1461670X.2025.2505001
  • Open Access
    Kieslich, K., & Schmitt, J. B. (2025). “But what is the alternative?!” - The impact of generative AI on academic knowledge production in times of science under pressure. Web publication or website, Internet Policy Review. https://policyreview.info/articles/news/what-alternative-impact-generative-ai-academic-knowledge-production-times-science
  • Open Access
    Kieslich, K., Diakopoulos, N., & Helberger, N. (2025). Anticipating impacts: using large-scale scenario-writing to explore diverse implications of generative AI in the news environment. AI and Ethics, 5(5), 4555–4577. https://doi.org/10.1007/s43681-024-00497-4
  • Open Access
    Mattis, N. M., Kieslich, K., & de Vreese, C. (2025). Feeling iffy about generative AI: When journalists disclose AI use, trust in news is lower. (v1 ed.) Open Science Framework. https://doi.org/10.31219/osf.io/tmzq4_v1
  • Open Access
    Kieslich, K., & Lünich, M. (2024). Regulating AI-Based Remote Biometric Identification: Investigating the Public Demand for Bans, Audits, and Public Database Registrations. In ACM FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency : June 3rd-6th 2024, Rio de Janeiro, Brazil (pp. 173-185). The Association for Computing Machinery. https://doi.org/10.1145/3630106.3658548
  • Open Access
    Barnett, J., Kieslich, K., & Diakopoulos, N. (2024). Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation. In S. Das, B. P. Green, K. Varshney, M. Ganapini, & A. Renda (Eds.), Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society: AIES-24 (pp. 82-93). AAAI Press. https://doi.org/10.1609/aies.v7i1.31620
  • Open Access
    Kieslich, K., Helberger, N., & Diakopoulos, N. (2024). My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts. In ACM FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency : June 3rd-6th 2024, Rio de Janeiro, Brazil (pp. 2071-2085). The Association for Computing Machinery. https://doi.org/10.1145/3630106.3659026
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