Sebastian Krügel
Biographic Data
| ID | 4465827 |
|---|---|
| NAME | Sebastian Krügel |
| GIVEN NAMES | Sebastian |
| FAMILY NAME | Krügel |
| SIGNATURE | KRÜGEL S |
| AFFILIATIONS | Technische Hochschule Ingolstadt |
| ORCID | 0000-0003-1196-8220 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 5 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
The Folk Ethics of Commodification
Commodification is the process of transforming goods or services traditionally transferred without charge into commercially exchangeable commodities. Critics argue that this transformation often entails the loss of inherent value, rendering the resulting transactions morally problematic. In contrast, proponents of commodification contend that if it is morally acceptable to give something away for free, it should likewise be permissible to transfe…
Perceived responsibility in AI-supported medicine
In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, alt…
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
Algorithms as partners in crime
The human in the loop is often advocated as a panacea against concerns about AI-powered machines, which increasingly take decisions of consequence in all realms of life. However, can we rely on humans to prevent unethical decisions by machines? We run online experiments modeling both the case where the machine serves as a corrective to the human and where the human serves as a corrective to the machine. Our results suggest that, in the former cas…
The behavioral economics of dynamically inconsistent behavior
Preferences often change—even in short time intervals—due to either the mere passage of time (present-biased preferences) or changes in visceral or environmental conditions (state-dependent preferences). On the basis of empirical findings concerning state-dependent preferences, we critically discuss the “Aristotelian” view of unitary decision makers in economics. We illustrate that the conceptualization of preferences as “present-biased” as oppos…
Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions
Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants distrust. We conducted online experiments where the subjects took the role of decision-makers who received advice from an algorithm on how to deal with an ethical dilemma. We manipulated the information about the…
Automated vehicles and the morality of post-collision behavior
We address the considerations of the European Commission Expert Group on the ethics of connected and automated vehicles regarding data provision in the event of collisions. While human drivers’ appropriate post-collision behavior is clearly defined, regulations for automated driving do not provide for collision detection. We agree it is important to systematically incorporate citizens’ intuitions into the discourse on the ethics of automated vehi…
Judgmental overconfidence
Judgmental overconfidence
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
Judgmental overconfidence
Automated vehicles and the morality of post-collision behavior
We address the considerations of the European Commission Expert Group on the ethics of connected and automated vehicles regarding data provision in the event of collisions. While human drivers’ appropriate post-collision behavior is clearly defined, regulations for automated driving do not provide for collision detection. We agree it is important to systematically incorporate citizens’ intuitions into the discourse on the ethics of automated vehi…
Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions
Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants distrust. We conducted online experiments where the subjects took the role of decision-makers who received advice from an algorithm on how to deal with an ethical dilemma. We manipulated the information about the…
Algorithms as partners in crime
The human in the loop is often advocated as a panacea against concerns about AI-powered machines, which increasingly take decisions of consequence in all realms of life. However, can we rely on humans to prevent unethical decisions by machines? We run online experiments modeling both the case where the machine serves as a corrective to the human and where the human serves as a corrective to the machine. Our results suggest that, in the former cas…
The behavioral economics of dynamically inconsistent behavior
Preferences often change—even in short time intervals—due to either the mere passage of time (present-biased preferences) or changes in visceral or environmental conditions (state-dependent preferences). On the basis of empirical findings concerning state-dependent preferences, we critically discuss the “Aristotelian” view of unitary decision makers in economics. We illustrate that the conceptualization of preferences as “present-biased” as oppos…
An interdisciplinary perspective on AI-supported decision making in medicine
Artificial intelligence (AI)-supported medical diagnosis offers the potential to utilize the collaborative intelligence of context-sensitive humans and narrowly focused machines for patients’ benefit. The employment of machine-learning-based decision-support systems (MLDSS) in medicine, however, raises important multidisciplinary challenges that cannot be addressed in isolation. We discuss three disciplinary perspectives on the topic and their in…
Perceived responsibility in AI-supported medicine
In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, alt…
The Folk Ethics of Commodification
Commodification is the process of transforming goods or services traditionally transferred without charge into commercially exchangeable commodities. Critics argue that this transformation often entails the loss of inherent value, rendering the resulting transactions morally problematic. In contrast, proponents of commodification contend that if it is morally acceptable to give something away for free, it should likewise be permissible to transfe…
Computer Science (6 works) · Ethics and Social Impacts of AI (5 works) · Psychology (5 works) · Neuroethics, Human Enhancement, Biomedical Innovations (4 works) · Political science (4 works) · Artificial Intelligence (3 works) · Business (3 works) · Economics (3 works) · Law (3 works) · Psychology of Moral and Emotional Judgment (3 works)