Publikationen von Iyad Rahwan

Grasso, F., Rahwan, I., Reed, C., & Simari, G. R. (2011). Introducing Argument & Computation: Editorial. Argument & Computation (No. 1). https://doi.org/10.1080/19462161003734804

Pentland, A. P., & Rahwan, I. (2012). Method for promoting behavior change through social reward mediation. Google Patents.

Baumann, F., Halpern, D., Procaccia, A. D., Rahwan, I., Shapira, I., & Wuthrich, M. (2023). Optimal engagement-diversity tradeoffs in social media. arXiv, 2303.03549. https://doi.org/10.48550/arXiv.2303.03549

Dong, M., Conway, J. R., Bonnefon, J.-F., Shariff, A., & Rahwan, I. (2023). A psychological model predicts fears about artificial intelligence across 20 countries and 6 domains of application. PsyArXiv, October 12, 2023. https://doi.org/10.31234/osf.io/pjvqt

Köbis, N., Lorenz-Spreen, P., Ajaj, T., Bonnefon, J.-F., Hertwig, R., & Rahwan, I. (2023). Artificial intelligence can facilitate selfish decisions by altering the appearance of interaction partners. arXiv, 2306.04484 . https://doi.org/10.48550/arXiv.2306.04484

Althobaiti, S., Alabdulkareem, A., Hanwen Shen, J., Rahwan, I., Frank, M., Moro, E., & Rutherford, A. (2022). Longitudinal complex dynamics of labour markets reveal increasing polarisation. arXiv, 2204.07073. https://doi.org/10.48550/arXiv.2204.07073

Awad, E., Levine, S., Loreggia, A., Mattei, N., Rahwan, I., Rossi, F., Talamadupula, K., Tenenbaum, J., & Kleiman-Weiner, M. (2022). When is it acceptable to break the rules? Knowledge representation of moral judgement based on empirical data. arXiv, 2201.07763.

Fioravant, F., Rahwan, I., & Tohmé, F. A. (2022). Properties of aggregation operators relevant for ethical decision making in artificial intelligence. arXiv, 2206.05160. https://doi.org/10.48550/arXiv.2206.05160

Fioravanti, F., Rahwan, I., & Tohmé, F. A. (2022). Ethical decision making for artificial intelligence: A social choice approach. arXiv, 2206.05160. https://doi.org/10.48550/arXiv.2206.05160

von Schenk, A., Klockmann, V., Bonnefon, J.-F., Rahwan, I., & Köbis, N. (2022). Lie detection algorithms attract few users but vastly increase accusation rates. arXiv, December 8, 2022. https://doi.org/10.48550/arXiv.2212.04277