An Intergenerational Common Pool Resource Experiment

intergenerational common pool resources;growth and altruism;free-riding intentions

The corruptive force of AI-generated advice

Artificial Intelligence (AI) is increasingly becoming a trusted advisor in people's lives. A new concern arises if AI persuades people to break ethical rules for profit. Employing a large-scale behavioural experiment (N = 1,572), we test whether AI-generated advice can corrupt people. We further test whether transparency about AI presence, a commonly proposed policy, mitigates potential harm of AI-generated advice. Using the Natural Language Processing algorithm, GPT-2, we generated honesty-promoting and dishonesty-promoting advice. Participants read one type of advice before engaging in a task in which they could lie for profit. Testing human behaviour in interaction with actual AI outputs, we provide first behavioural insights into the role of AI as an advisor. Results reveal that AI-generated advice corrupts people, even when they know the source of the advice. In fact, AI's corrupting force is as strong as humans'.Comment: Leib & K\"obis share first authorshi

How private is private information?:The ability to spot deception in an economic game

First Online: 22 February 2016We provide experimental evidence on the ability to detect deceit in a buyer–seller game with asymmetric information. Sellers have private information about the value of a good and sometimes have incentives to mislead buyers. We examine if buyers can spot deception in face-to-face encounters. We vary whether buyers can interrogate the seller and the contextual richness. The buyers’ prediction accuracy is above chance, and is substantial for confident buyers. There is no evidence that the option to interrogate is important and only weak support that contextual richness matters. These results show that the information asymmetry is partly eliminated by people’s ability to spot deception

Competition and Prosociality: A Field Experiment in Ghana

Competitive bonuses are commonly used to promote higher productivity in the workplace. Yet, these types of incentives could have negative spillovers on coworkers' prosocial behavior in subsequent tasks. To investigate this question, we conduct a lab-in-the-eld experiment in Ghana. In a between-subjects design, participants complete a real-eort task under a competitive, threshold, or random payment while holding payment dierentials constant across treatments. Before and after, we measure prosociality through a public goods and a social value orientation game. Competition reduces prosociality when the dispersion of payments is high. However, when there is less at stake, competition does not aect prosociality