Dr. K.H. (Kimon) Kieslich
Faculteit der Maatschappij- en Gedragswetenschappen
Communication, Organizations and Society
Expertisegebied: AI & Politics, AI Impact Assessment. Algorithmic Fairness, AI & Journalism, AI Ethics, Scenario-Writing, AI Regulation
Bezoekadres
- Nieuwe Achtergracht 166
Postadres
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Postbus 15791
1001 NG Amsterdam
Contactgegevens
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Profile
Kimon is a communication scientist studying the social and political implications of data-driven technologies, with a particular focus on AI ethics, public perceptions of algorithms, and the societal impacts of automated decision-making. His work examines how these technologies are designed, governed, and experienced in practice, especially in contexts shaped by inequality and global power relations.
He is currently a postdoctoral researcher in the research priority area (RPA) AI & Politics at the Communication, Organisations and Society department of the Amsterdam School of Communication Research (ASCoR), University of Amsterdam.
His research sits at the intersection of social sciences, computer science, law, and psychology, and he actively collaborates across these fields. His methodological expertise spans quantitative approaches such as surveys and content analysis, as well as qualitative approaches including scenario-writing and thematic analysis. He is co-developer of Scenario-Based Sociotechnical Envisioning, a method for exploring and evaluating possible futures of AI and other data-driven technologies.
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Research
Research methods
- Anticipatory metods (scenario-writing; future visioning)
- Surveys
- Conjoint analysis
- Content analysis
- Survey experiments
- Computational methods (in cooperation with computer scientists)
Research expertise
- AI and politics
- AI impact and risk assessment
- AI and journalism
- Political communication
- Trust
- Politicization
- Algorithmic fairness
- AI ethics
- AI resistance
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Publicaties
2026
- 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
- Kieslich, K. H., Helberger, N., & Diakopoulos, N. A. (2026). Scenario-based sociotechnical envisioning (SSE): an approach to enhance systemic risk assessments. AI and Ethics, 6. https://doi.org/10.1007/s43681-026-01084-5
- Mattis, N., Kieslich, K., & de Vreese, C. H. (2026). Feeling Iffy About Generative AI: Investigating Audiences’ Trustworthiness Perceptions of Task-Specific AI Disclosures. Digital Journalism. Advance online publication. https://doi.org/10.1080/21670811.2026.2703599
- Nishal, S., Sax, M., & Kieslich, K. (2026). Why AI Slop Matters, but Not Like That. ACM AI Letters, 1-6. https://doi.org/10.1145/3828758
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 [details]
2025
- Allaham, M., Kieslich, K., & Diakopoulos, N. (2025). Informing AI Risk Assessment with News Media: Analyzing National and Political Variation in the Coverage of AI Risks. In E. Burton, N. Mattei, & A. Páez (Eds.), Proceedings of the Eighth AAAI/ACM Conference on AI, Ethics, and Society: IE University Tower, Madrid, Spain : October 20-22, 2025 (Vol. 1, pp. 90-103). AAAI Press. https://doi.org/10.1609/aies.v8i1.36533
- 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 [details]
- Barnett, J., Kieslich, K., Sinchai, J., & Diakopoulos, N. (2025). Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society. In E. Burton, N. Mattei, & A. Páez (Eds.), Proceedings of the Eighth AAAI/ACM Conference on AI, Ethics, and Society: IE University Tower, Madrid, Spain : October 20-22, 2025 (Vol. 1, pp. 316-329). AAAI Press. https://doi.org/10.1609/aies.v8i1.36551
- 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 [details]
- Morosoli, S., Kieslich, K., Resendez, V., & van Drunen, M. (2025). AI governance in the spotlight: an empirical analysis of Dutch political parties’ strategies for the 2023 elections. Journal of Information Technology and Politics. Advance online publication. https://doi.org/10.1080/19331681.2025.2504519
- 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 [details]
2024
- 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 [details]
- 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 [details]
- 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 [details]
2023
- Kieslich, K., Lünich, M., & Došenović, P. (2023). Ever Heard of Ethical AI? Investigating the Salience of Ethical AI Issues among the German Population. International Journal of Human-Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2023.2178612
2022
- Kieslich, K., Keller, B., & Starke, C. (2022). Artificial intelligence ethics by design: Evaluating public perception on the importance of ethical design principles of artificial intelligence. Big Data & Society, 9(1). https://doi.org/10.1177/20539517221092956 [details]
- Lünich, M., & Kieslich, K. (2022). Exploring the roles of trust and social group preference on the legitimacy of algorithmic decision-making vs. human decision-making for allocating COVID-19 vaccinations. AI and Society. Advance online publication. https://doi.org/10.1007/s00146-022-01412-3
2021
- Kieslich, K., Lünich, M., & Marcinkowski, F. (2021). The Threats of Artificial Intelligence Scale (TAI): Development, Measurement and Test Over Three Application Domains. International journal of social robotics, 13(7), 1563-1577. https://doi.org/10.1007/s12369-020-00734-w
- Lünich, M., Marcinkowski, F., & Kieslich, K. (2021). It's now or never! future discounting in the application of the online privacy calculus. Cyberpsychology, 15(3), Article 11. https://doi.org/10.5817/CP2021-3-11
2020
- Hase, V., Engelke, K. M., & Kieslich, K. (2020). The Things We Fear. Combining Automated and Manual Content Analysis to Uncover Themes, Topics and Threats in Fear-Related News. Journalism Studies, 21(10), 1384-1402. https://doi.org/10.1080/1461670X.2020.1753092
- Kieslich, K., & Marcinkowski, F. (2020). Serving the populist agenda: How German public media broadcasters inadvertently facilitate populist movements by evoking fear and anger. Studies in Communication and Media, 9(4), 482-515. https://doi.org/10.5771/2192-4007-2020-4-482
- Marcinkowski, F., Kieslich, K., Starke, C., & Lünich, M. (2020). Implications of AI (un-)fairness in higher education admissions: The effects of perceived AI (un-)fairness on exit, voice and organizational reputation. In FAT* '20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 122–130). ACM. https://doi.org/10.1145/3351095.3372867
2025
- Kieslich, K. H., & Schmitt, J. B. (2025). “But what is the alternative?!” - The impact of generative AI on academic knowledge production in times of science under pressure. Internet Policy Review. https://policyreview.info/articles/news/what-alternative-impact-generative-ai-academic-knowledge-production-times-science
- 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 [details]
2022
- Kieslich, K. (2022). Commentary: Societal Reactions to Hopes and Threats of Autonomous Agent Actions: Reflections about Public Opinion and Technology Implementations. Human-Computer Interaction, 37(3), 259-262. https://doi.org/10.1080/07370024.2021.1976642
Mediaoptreden
- van Drunen, M., Kieslich, K., Morosoli, S. & Resendez Gómez, V. (18-11-2023). Partijen hebben het punt van de toeslagenaffaire gemist: AI’s risico’s zijn breder [Web] Stuk Rood Vlees. AI in Dutch party manifestos and the child benefit scandal. https://stukroodvlees.nl/partijen-hebben-het-punt-van-de-toeslagenaffaire-gemist-ais-risicos-zijn-breder/
Spreker
- Kieslich, K. (speaker), Helberger, N. (speaker) & Diakopoulos, N. (speaker) (10-4-2025). Using scenario-based sociotechnical envisioning for value-driven risk assessment, The Future of Public Values in the Algorithmic Society, Amsterdam. https://algosoc.org/uploads/AlgoSoc-Conference-2025_spreads_DIGI.pdf
2024
- Kieslich, K. (2024). The role of public opinion on ethical AI principles and its implication for a common good-oriented implementation. [Thesis, fully external, University of Hohenheim]. https://doi.org/10.60848/10892
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Nevenwerkzaamheden
Geen nevenwerkzaamheden
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.