Abstract
We introduce causal agency models as a modeling technique
for representing and reasoning about ethical dilemmas. We
find that ethical dilemmas, although they look similar on the
surface, have very different causal structures. Based on their structural properties, as identified by the causal agency models, we cluster a set of dilemmas in Type 1 and Type 2 dilemmas. We observe that for Type 2 dilemmas but not for Type 1 dilemmas a utilitarian action dominates the possibility of refraining from action. Hence, we hypothesize, based on the model, that Type 2 dilemmas are perceived as less difficult than Type 1 dilemmas by human reasoners. A behavioral study where participants rated the difficulty of dilemmas supports the models’ predictions.
for representing and reasoning about ethical dilemmas. We
find that ethical dilemmas, although they look similar on the
surface, have very different causal structures. Based on their structural properties, as identified by the causal agency models, we cluster a set of dilemmas in Type 1 and Type 2 dilemmas. We observe that for Type 2 dilemmas but not for Type 1 dilemmas a utilitarian action dominates the possibility of refraining from action. Hence, we hypothesize, based on the model, that Type 2 dilemmas are perceived as less difficult than Type 1 dilemmas by human reasoners. A behavioral study where participants rated the difficulty of dilemmas supports the models’ predictions.
Original language | English |
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Title of host publication | Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci2017) |
Number of pages | 2494 |
Publisher | Cognitive Science Society |
Publication date | 2017 |
ISBN (Electronic) | 978-0-9911967-6-0 |
Publication status | Published - 2017 |
Event | 39th Annual Meeting of the Cognitive Science Society (COGSCI2017) - London, United Kingdom Duration: 26 Jul 2017 → 29 Jul 2017 http://www.cognitivesciencesociety.org/conference/cogsci2017/ |
Conference
Conference | 39th Annual Meeting of the Cognitive Science Society (COGSCI2017) |
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Country/Territory | United Kingdom |
City | London |
Period | 26/07/2017 → 29/07/2017 |
Internet address |