Kimon Kieslich
Orcid: 0000-0002-6305-2997
According to our database1,
Kimon Kieslich
authored at least 15 papers
between 2020 and 2024.
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Bibliography
2024
Ever Heard of Ethical AI? Investigating the Salience of Ethical AI Issues among the German Population.
Int. J. Hum. Comput. Interact., June, 2024
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 Soc., February, 2024
CoRR, 2024
CoRR, 2024
Regulating AI-Based Remote Biometric Identification. Investigating the Public Demand for Bans, Audits, and Public Database Registrations.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024
My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024
Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation.
Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) - Full Archival Papers, October 21-23, 2024, San Jose, California, USA, 2024
2023
Anticipating Impacts: Using Large-Scale Scenario Writing to Explore Diverse Implications of Generative AI in the News Environment.
CoRR, 2023
2022
Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence.
Big Data Soc., January, 2022
Commentary: Societal Reactions to Hopes and Threats of Autonomous Agent Actions: Reflections about Public Opinion and Technology Implementations.
Hum. Comput. Interact., 2022
2021
Using automated decision-making (ADM) to allocate Covid-19 vaccinations? Exploring the roles of trust and social group preference on the legitimacy of ADM vs. human decision-making.
CoRR, 2021
AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AI.
CoRR, 2021
2020
The Threats of Artificial Intelligence Scale (TAI). Development, Measurement and Test Over Three Application Domains.
CoRR, 2020
Implications of AI (un-)fairness in higher education admissions: the effects of perceived AI (un-)fairness on exit, voice and organizational reputation.
Proceedings of the FAT* '20: Conference on Fairness, 2020