Research Interests
Primary: Gender and Gender in Language, Economics of Artificial Intelligence and Robotics
Secondary: Behavioral Economics, Experimental Methodology, Networks, Contest
Publications
How Strength Asymmetries Shape Multi-Sided Conflicts, joint with Sebastiàn Cortes-Corrales, Economic Theory, 2024
Our older working paper version, including a proof showing that there exist no closed-form solutions to the model for non-trivial graphs, can be found here: Generalising Conflict Networks
Reproducibility in Management Science, by Fišar, M., Greiner, B., Huber, C., Katok, E., Ozkes, A., and the Management Science Reproducibility Collaboration, Management Science, 70(3), pp. 1343-2022, 2024, Note: Contributed as a Member of the Management Science Reproducibility Collaboration.
Prosocial behavior among human workers in robot-augmented production teams—A field-in-the-lab experiment, joint with Benedikt Renner and Louis Schäfer, Frontiers in Behavioral Economics (Section Culture and Ethics), 2, 1220563, 2023, preregistration
Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs, joint with Christoph Huber, Anna Dreber, Jürgen Huber, Magnus Johannesson, Michael Kirchler, Utz Weitzel, Felix Holzmeister and others, Proceedings of the National Academy of Science (PNAS), 120(23), e2215572120, 2023
Working Papers
Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight joint with Eva Groos and Christina Strobel (soon to be submitted)
Regulators of artificial intelligence (AI) emphasize the importance of human autonomy and oversight in AI-assisted decision-making (European Commission, Directorate General for Communications Networks, Content and Technology, 2021; 117th Congress, 2022). Predictions are the foundation of all AI tools; thus, if AI can predict our decisions, how might these predictions influence our ultimate choices? We examine how salient, personalized AI predictions affect decision outcomes and investigate the role of reactance, i.e., an adverse reaction to a perceived reduction in individual freedom. We trained an AI tool on previous dictator game decisions to generate personalized predictions of dictators’ choices. In our AI treatment, dictators received this prediction before deciding. In a treatment involving human oversight, the decision of whether participants in our experiment were provided with the AI prediction was made by a previous participant (a ‘human overseer’). In the baseline, participants did not receive the prediction. We find that participants sent less to the recipient when they received a personalized prediction but the strongest reduction occurred when the AI’s prediction was intentionally not shared by the human overseer. Our findings underscore the importance of considering human reactions to AI predictions in assessing the accuracy and impact of these tools as well as the potential adverse effects of human oversight.
Gendered Language, Economic Behavior, and Norm Compliance joint with Petra Nieken and Karoline Ströhlein (currently under review)
We conducted a controlled experiment to examine how the gender frame of instructions—male, female, or gender-inclusive—along with the presence or absence of a prescriptive norm (norm salience) influences norm compliance. Participants played three standard two-player economic games focusing on sharing, cooperation, and honesty. Whereas we find no clear ordering in norm compliance across our male, gender-inclusive, and female gender frames, we do find a statistically significant negative effect of the gender-inclusive frame on norm compliance for almost all participants and a statistically significant negative effect of the male gender frame on men's norm compliance. Additionally, norm salience does not appear to increase norm compliance. These findings contribute to the debate on gender-inclusive language by highlighting its unintended behavioral effects.
Previously, this project circulated as two separate papers, The Effects of Gendered Language on Norm Compliance and He, She, They? The Impact of Gendered Language on Economic Behavior.
Don't fear the Robots: Automatability and Job Satisfaction joint with Ritchie C. Woodard (new draft in preparation)
We analyse the correlation between job satisfaction and automatability - the degree to which an occupation can be or is at risk of being replaced by computerised equipment. Using multiple survey datasets matched with various measures of automatability from the literature, we find a negative and statistically significant correlation that is robust to controlling for worker and job characteristics. Depending on the dataset, a one standard deviation increase in automatability leads to a drop in job satisfaction of about 0.64% to 2.61% for the average worker. Unlike other studies, we provide evidence that it is not the fear of losing the job that mainly drives this result, but the fact that monotonicity and low perceived meaning of the job drive both automatability and low job satisfaction.
Conference Proceedings (peer-reviewed)
Seeing Is Feeling: Emotional Cues in Others’ Heart Rate Visualizations joint with Anke Greif-Winzrieth, Verena Dorner, Fabian Wuest, and Christof Weinhardt
Learning Factory Labs as Field-in-the-Lab Environment – An Experimental Concept for Human-Centred Production Research joint with Magnus Kandler, Louis Schäfer, Gisela Lanza, Petra Nieken, and Karoline Ströhlein
Decision Experiments in the Learning Factory: A Proof of Concept joint with Karoline Ströhlein, Magnus Kandler, Petra Nieken, Louis Schäfer, and Gisela Lanza
Human-Oriented Design of Andon-Boards 4.0 – Promoting Decentralized Decisions on the Shopfloor and Acceptance by Employees joint with Magnus Kandler, Karoline Ströhlein, Sebastian Riedinger, Petra Nieken, and Gisela Lanza
Work in Progress
Do Personalized AI Predictions Change Subsequent Decision-Outcomes? Artificial versus Swarm Intelligence, joint with Christina Strobel (data gathering)
Feedback in the Factory—A Novel Field in-the-Lab Experiment, joint with Magnus Kandler, Gisela Lanza, Petra Nieken, and Karoline Ströhlein (draft in preparation)
The Role of Adaptivity in Human-Robot Collaboration: A Field-in-the-Lab Experiment, joint with Louis Schäfer (draft in preparation)
The Gender of Opportunity: How Gendered Job Titles Affect Job Seeker Attraction, joint with Petra Nieken and Martin Trenkle (additional data gathering)
Predict, Advise, or Perform?—The Role of Automated Systems in Human Interaction, joint with Emike Nasamu and Mengjie Wang (data gathering)
Assessing the Human Premium: Task Allocation Preferences in a Hybrid Workforce, joint with Aleksandr Alekseev and Mikhail Anufriev
Exploring Distributional Biases in Responses of Generative AI, joint with Petra Nieken, Abdolkarim Sadrieh, and Frederic Sadrieh
Social Preferences and Cost Considerations in Contests
Audience Effects in the Overconfidence Gender Gap