Is ChatGPT detrimental to innovation? A field experiment among university students

Purpose This paper investigates the potential collateral effects of A.I innovations, specifically ChatGPT, on three key variables: innovation, readiness to exert effort and risk behavior. Design/methodology/approach A field experiment was conducted involving nearly 100 senior university students at a public university in Egypt, at a time when ChatGPT had not yet been legally operational. Over a one-month period, participants submitted three graded essay assignments. The treatment group utilized ChatGPT to write the essays, while the control group completed the assignments without such assistance. After submission, both groups participated in a lab-based innovation game, a risk game and a real effort task to measure their respective innovation, risk aversion and effort exertion. Findings The results reveals that students who used ChatGPT demonstrated significantly lower levels of innovation (ChatGPT usage is associated with a decrease in innovation scores by approximately 0.6–0.72 standard deviation points, at the 95% confidence level) and risk aversion (individuals in the ChatGPT group are more likely to become risk lovers, at the 90% confidence level) compared to the Non-ChatGPT group. Although the reduction in effort exerted by the ChatGPT group was not statistically significant, the overall trends suggest a potential decrease in effort related to the use of A.I. applications. Research limitations/implications On avenues for future research, although field experiments will always have the advantage of high ecological validity, testing the effect of AITGs on behavior could also benefit from the controlled environment of lab experiments. In such designs, spill-over worries would be minimal and internal validity would be high. To address the issue of external validity however, new experimental designs could be thought of to test the generalizability of the findings; longitudinal studies that trace the effect of technology across time, expanding the participant pool across multiple institutions that vary in terms of type (public/private), age of students (schools/universities), academic background and majors … etc. Practical implications On practical and policy implications – and in line with economic theories on innovation and economic growth and development (Schumpeter, 1942; Romer, 1990; Acemoglu and Robinson, 2013) – our humble findings point to an urgent need to augment existing education with concrete, innovation-based practices. These could include embedding design thinking and problem-based learning modules directly into curricula, as well as choice architecture that alters people’s behavior without restricting options. In addition, designing student innovation competitions and startup incubators that reward novelty and impact would incentivize the value of innovation. Originality/value This study is among the first to empirically test the impact of ChatGPT on innovation, effort, and risk behavior in a real-world academic setting. It provides preliminary evidence of the potential negative effects of A.I. applications on these variables, offering valuable insights for further research into the broader implications of A.I. on human behavior.