Iyad Rahwan - Publications
Journal Article (5)
2022
Journal Article
Rahwan, I., & (2022). Polarized citizen preferences for the ethical allocation of scarce medical resources in 20 countries. MDM Policy & Practice, 7(2). https://doi.org/10.1177/23814683221113573
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Journal Article
Brinkmann, L., Gezerli, D., Kleist, K. V., Müller, T. F., Rahwan, I., & Pescetelli, N. (2022). Hybrid social learning in human-algorithm cultural transmission. Philosophical Transactions of the Royal Society of London: A, Mathematical, Physical and Engineering Sciences, 380(2227), Article 20200426. https://doi.org/10.1098/rsta.2020.0426
Journal Article
Cebrian, M., & Rahwan, I. (2022). Automation impacts on China’s polarized job market. Journal of Computational Social Science, 5, 517–535. https://doi.org/10.1007/s42001-021-00134-8
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Journal Article
Köbis, N., , & Rahwan, I. (2022). The promise and perils of using artificial intelligence to fight corruption. Nature Machine Intelligence, 4, 418–424. https://doi.org/10.1038/s42256-022-00489-1
Journal Article
Obradovich, N., , , , , Cebrián, M., , , Rahwan, I., & (2022). Expanding the measurement of culture with a sample of two billion humans. Journal of the Royal Society Interface, 19(190), Article 20220085. https://doi.org/10.1098/rsif.2022.0085
Preprint (5)
2022
Preprint
Rahwan, I., , , & Rutherford, A. (2022). Longitudinal complex dynamics of labour markets reveal increasing polarisation. arXiv, 2204.07073. https://doi.org/10.48550/arXiv.2204.07073
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Preprint
Rahwan, I., , , , & (2022). When is it acceptable to break the rules? Knowledge representation of moral judgement based on empirical data. arXiv, 2201.07763.
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Preprint
Rahwan, I., & (2022). Properties of aggregation operators relevant for ethical decision making in artificial intelligence. arXiv, 2206.05160. https://doi.org/10.48550/arXiv.2206.05160
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Preprint
Rahwan, I., & (2022). Ethical decision making for artificial intelligence: A social choice approach. arXiv, 2206.05160. https://doi.org/10.48550/arXiv.2206.05160
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Preprint
von Schenk, A., Klockmann, V., , 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