TY  - UNPD
A1  - Klockmann, Victor
A1  - Schenk, Alicia von
A1  - Villeval, Marie-Claire
T1  - Artificial intelligence, ethics, and intergenerational responsibility
T2  - SAFE working paper ; No. 335
N2  - In more and more situations, artificially intelligent algorithms have to model humans’ (social) preferences on whose behalf they increasingly make decisions. They can learn these preferences through the repeated observation of human behavior in social encounters. In such a context, do individuals adjust the selfishness or prosociality of their behavior when it is common knowledge that their actions produce various externalities through the training of an algorithm? In an online experiment, we let participants’ choices in dictator games train an algorithm. Thereby, they create an externality on future decision making of an intelligent system that affects future participants. We show that individuals who are aware of the consequences of their training on the pay- offs of a future generation behave more prosocially, but only when they bear the risk of being harmed themselves by future algorithmic choices. In that case, the externality of artificially intelligence training induces a significantly higher share of egalitarian decisions in the present.
T3  - SAFE working paper - 335 
KW  - Artificial Intelligence
KW  - Morality
KW  - Prosociality
KW  - Generations
KW  - Externalities
Y1  - 2021
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/63522
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-635224
UR  - https://ssrn.com/abstract=4002578
N1  - Financial research support from the Leibniz Institute for Financial Research SAFE, the Goethe University Frankfurt, and the LABEX CORTEX (ANR- 11-LABX-0042) of Universite de Lyon, within the program Investissements Avenir (ANR-11-IDEX-007) operated by the French National Research Agency (ANR) is gratefully acknowledged.
IS  - December 21, 2021
PB  - SAFE
CY  - Frankfurt am Main
ER  -