Journal Article (83)

2019
Journal Article
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A. S., Roberts, M. E., Shariff, A., Tenenbaum, J. B., & Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477–486. https://doi.org/10.1038/s41586-019-1138-y
Journal Article
Roy, K. C., Cebrian, M., & Hasan, S. (2019). Quantifying human mobility resilience to extreme events using geo-located social media data. EPJ Data Science, 8, Article 18. https://doi.org/10.1140/epjds/s13688-019-0196-6
Journal Article
Xu, W., Chen, H., Frias-Martinez, E., Cebrian, M., & Li, X. (2019). The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth. Royal Society Open Science, 6(11), Article 181640. https://doi.org/10.1098/rsos.181640

Book Chapter (1)

2020
Book Chapter
Bonnefon, J.-F., Shariff, A., & Rahwan, I. (2020). The moral psychology of AI and the ethical opt-out problem. In S. M. Liao (Ed.), Ethics of artificial intelligence (pp. 109–126). Oxford University Press.

Conference Paper (2)

2021
Conference Paper
Jung, C., Hong, I., Sáez-Trumper, D., Lee, D., Myung, J., Kim, D., Yun, J., Jung, W.-S., & Cha, M. (2021). Information flow on COVID-19 over Wikipedia: A case study of 11 languages. In WWW '21: Companion Proceedings of the Web Conference 2021. Ljubljana, Slovenia, April 19 - 23, 2021 (pp. 627–628). International World Wide Web Conferences Committee. https://doi.org/10.1145/3442442.3452352
2020
Conference Paper
Serna, I., Morales, A., Fierrez, J., Cebrian, M., Obradovich, N., & Rahwan, I. (2020). Algorithmic discrimination: Formulation and exploration in deep learning-based face biometrics. In H. Espinoza, J. Hernández-Orallo, X. C. Chen, S. S. ÓhÉigeartaigh, X. Huang, M. Castillo-Effen, R. Mallah, & J. McDermid (Eds.), H. Espinoza, J. Hernández-Orallo, X. C. Chen, S. S. ÓhÉigeartaigh, X. Huang, M. Castillo-Effen, R. Mallah, & J. McDermid (Eds.), Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020): Co-located with 34th AAAI Conference on Artificial Intelligence (AAAI 2020). New York, USA, Feb 7, 2020 (pp. 146–152). RWTH.

Working Paper (2)

2021
Working Paper
Köbis, N., Bonnefon, J.-F., & Rahwan, I. (2021). Bad machines corrupt good morals (TSE Working Papers No. 1212). Toulouse School of Economics.
Working Paper
Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2021). “How safe is safe enough? Psychological mechanisms underlying extreme safety demands for self-driving cars” (TSE Working Papers No. 1215). Toulouse School of Economics.

Editorial (1)

2022
Editorial
Obradovich, N., & Minor, K. (2022). Identifying and preparing for the mental health burden of climate change. JAMA Psychiatry (No. 79). https://doi.org/10.1001/jamapsychiatry.2021.4280

Preprint (20)

2022
Preprint
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
Preprint
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.
Preprint
Czaplicka, A., Charalambous, C., Toral, R., & Miguel, M. S. (2022). Biased-voter model: How persuasive a small group can be? ArXiv, 2203.05376. https://doi.org/10.48550/arXiv.2203.05376
Preprint
Feng, X., & Rutherford, A. (2022). The dynamic resilience of urban labour networks. arXiv, 2202.12856 . https://doi.org/10.48550/arXiv.2202.12856
Preprint
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
Preprint
Köbis, N., Dorrough, A., Irlenbusch, B., Shalvi, S., & Gloeckner, A. (2022). Bribery across nations. Research Square, 25 May 2022. https://doi.org/10.21203/rs.3.rs-1690288/v1
Preprint
Lange, J., Köbis, N., & Herrmann, C. (2022). A systematic literature review and integrative framework on the link between emotions and corruption. OSF Preprints, 15 June 2022. https://doi.org/10.31219/osf.io/8uzkf
Preprint
Müller, T. F., Brinkmann, L., Winters, J., & Pescetelli, N. (2022). Machine impostors avoid human detection by interrupting the formation of stable conventions: A minimal turing test. PsyArXiv, 28 April 2022. https://doi.org/10.31234/osf.io/x2yf7
Preprint
Yang, Q., Wei, W., Zhang, R., Pang, B., & Feng, X. (2022). Enhance ambiguous community structure via multi-strategy community related link prediction method with evolutionary process. arXiv, 2204.13301. https://doi.org/10.48550/arXiv.2204.13301
2021
Preprint
Köbis, N., Starke, C., & Rahwan, I. (2021). Artificial intelligence as an anti-corruption tool (AI-ACT): Potentials and pitfalls for top-down and bottom-up approaches. arXiv, 2102.11567.
Preprint
Kong, Q., Garcia-Herranz, M., Dotu, I., & Cebrian, M. (2021). Contact tracing: Computational bounds, limitations and implications. arXiv, 2102.13349.
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