Engi Amin

ChatGPT represents a momentous technological breakthrough whose implications – along with other AI innovations – are yet to fully materialize. This paper is among the first attempts to experimentally test the effect of AI applications (in the form of ChatGPT) on three dependent variables usually assumed to be AI-collaterals: innovation, readiness to exert effort, and risk behaviour. We took advantage of the delayed introduction of ChatGPT in Egypt and conducted a pre-registered field experiment with nearly 100 senior university students at a public university. Over one month during term time, participants were asked to submit three graded essay assignments. In the treatment group, students were asked to write the essays using ChatGPT whereas in the control group, such option was neither mentioned nor allowed (the experiment was fielded before ChatGPT was legally operable in Egypt). One week after all assignments were submitted, the two groups were invited to the lab to play an innovation game (deploying multiple strategies to increase the sales of a hypothetical lemonade stand), a risk game (bomb risk elicitation task), and do a real effort task. The ChatGPT group was significantly less innovative, significantly less risk averse, and exerted less effort (however not statistically significant). Our results point to possible negative effects of AI applications but need further testing and larger samples to be confirmed.Competing Interest StatementThe authors have declared no competing interest.

Voluntary cooperation contributes significantly to development and prosperity. Settings where the social norm is free-riding, however, offer a particular challenge for public goods contribution. In this paper we ask two questions: how could high contributors to public goods in such contexts be encouraged to sustain their contributions against a defecting crowd? Second, how can low contributors – who are abundant in such milieus – be lured to increase their contributions without expensive institutional interventions or major structural transformations? To answer these questions, we conducted three public good experiments with 456 subjects in Egypt. In the first experiment, we find that priming high cooperators with a message that makes them take pride in being among the minority of cooperators increases contributions, albeit with a lag. In the second and third experiments, we test how far three possible appeal messages – emphasizing religious, patriotic, or social harm– could drive low cooperators to increase their contributions. We show that using such messages does increase contributions significantly.

This paper examines the role of heterogeneous agents in the study of voluntary contributions to public goods. A human-subject experiment was conducted to classify agent types and determine their effects on contribution levels. Data from the experiment was used to build and calibrate an agent-based simulation model. The simulations display how different compositions of agent preference types affect the contribution levels. Findings indicate that the heterogeneity of cooperative preferences is an important determinant of a population’s contribution pattern.