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

Chen, H. C., Li, X., Frank, M., Qin, X., Xu, W., 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

Czaplicka, A., Charalambous, C., Toral, R., & Miguel, M. S. (2022). Biased-voter model: How persuasive a small group can be? Chaos, Solitons, & Fractals, 161, Article 112363. https://doi.org/10.1016/j.chaos.2022.112363

Dong, M., van Prooijen, J.-W., & van Lange, P. A. M. (2022). Strategic exploitation by higher-status people incurs harsher third-party punishment. Social Psychology, 53(4), 209–220. https://doi.org/10.1027/1864-9335/a000493

Dong, M., van Prooijen, J.-W., Wu, S., & van Lange, P. A. M. (2022). Culture, status, and hypocrisy: High-status people who don't practice what they preach are viewed as worse in the United States than China. Social Psychological and Personality Science, 13(1), 60–69. https://doi.org/10.1177/1948550621990451

Klockmann, V., von Schenk, A., & Villeval, M. C. (2022). Artificial intelligence, ethics, and intergenerational responsibility. Journal of Economic Behavior & Organization, 203, 284–317. https://doi.org/10.1016/j.jebo.2022.09.010

Köbis, N., Starke, C., & 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

Liu, C., Xie, Y., Hao, Y., Zhang, W., Yang, L., Bu, J., Wei, Z., Wu, H., Pescetelli, N., & Zhang, X. (2022). Using multisession tDCS stimulation as an early intervention on memory bias processing in subthreshold depression. Psychophysiology, 60(1), Article e14148. https://doi.org/10.1111/psyp.14148

Minor, K., Bjerre-Nielsen, A., Jonasdottir, S. S., Lehmann, S., & Obradovich, N. (2022). Rising temperatures erode human sleep globally. One Earth, 5(5), 534–549. https://doi.org/10.1016/j.oneear.2022.04.008

Morin, O., Müller, T. F., Morisseau, T., & Winters, J. (2022). Cultural evolution of precise and agreed-upon semantic conventions in a multiplayer gaming app. Cognitive Science, 46(2), Article e13113. https://doi.org/10.1111/cogs.13113

Nussberger, A.-M., Luo, L., Celis, L. E., & Crockett, M. J. (2022). Public attitudes value interpretability but prioritize accuracy in artificial intelligence. Nature Communications, 13, Article 5821. https://doi.org/10.1038/s41467-022-33417-3

Obradovich, N., Özak, Ö., Martín, I., Ortuño-Ortín, I., Awad, E., Cebrián, M., Cuevas, R., Desmet, K., Rahwan, I., & Cuevas, Á. (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

Pescetelli, N., Barkoczi, D., & Cebrian, M. (2022). Bots influence opinion dynamics without direct human-bot interaction: The mediating role of recommender systems. Applied Network Science, 7, Article 46. https://doi.org/10.1007/s41109-022-00488-6

Pescetelli, N., Reichert, P., & Rutherford, A. (2022). A variational-autoencoder approach to solve the hidden profile task in hybrid human-machine teams. PLoS ONE, 17(8), Article e0272168. https://doi.org/10.1371/journal.pone.0272168

Romanello, M., Di Napoli, C., Drummond, P., Green, C., Kennard, H., Lampard, P., Scamman, D., Arnell, N., Ayeb-Karlsson, S., Berrang Ford, L., Belesova, K., Bowen, K., Cai, W., Callaghan, M., Campbell-Lendrum, D., Chambers, J., van Daalen, K. R., Dalin, C., Dasandi, N., Dasgupta, S., Davies, M., Dominguez-Salas, P., Dubrow, R., Ebi, K. L., Eckelman, M., Ekins, P., Escobar, L. E., Georgeson, L., Graham, H., Gunther, S. H., Hamilton, I., Hang, Y., Hänninen, R., Hartinger, S., He, K., Hess, J. J., Hsu, S.-C., Jankin, S., Jamart, L., Jay, O., Kelman, I., Kiesewetter, G., Kinney, P., Kjellstrom, T., Kniveton, D., Lee, J. K. W., Lemke, B., Liu, Y., Liu, Z., Lott, M., Lotto Batista, M., Lowe, R., MacGuire, F., Odhiambo Sewe, M., Martinez-Urtaza, J., Maslin, M., McAllister, L., McGushin, A., McMichael, C., Mi, Z., Milner, J., Minor, K., Minx, J. C., Mohajeri, N., Moradi-Lakeh, M., Morrissey, K., Munzert, S., Murray, K. A., Neville, T., Nilsson, M., Obradovich, N., O’Hare, M. B., Oreszczyn, T., Otto, M., Owfi, F., Pearman, O., Rabbaniha, M., Robinson, E. J. Z., Rocklöv, J., Salas, R. N., Semenza, J. C., Sherman, J. D., Shi, L., Shumake-Guillemot, J., Silbert, G., Sofiev, M., Springmann, M., Stowell, J., Tabatabaei, M., Taylor, J., Triñanes, J., Wagner, F., Wilkinson, P., Winning, M., Yglesias-González, M., Zhang, S., Gong, P., Montgomery, H., & Costello, A. (2022). The 2022 report of the Lancet Countdown on health and climate change: Health at the mercy of fossil fuels. The Lancet, 400(10363), 1619–1654. https://doi.org/10.1016/S0140-6736(22)01540-9

Serna, I., Morales, A., Fierrez, J., & Obradovich, N. (2022). Sensitive loss: Improving accuracy and fairness of face representations with discrimination-aware deep learning. Artificial Intelligence, 305, Article 103682. https://doi.org/10.1016/j.artint.2022.103682

Wang, J., Fan, Y., Palacios, J., Chai, Y., Guetta-Jeanrenaud, N., Obradovich, N., Zhou, C., & Zheng, S. (2022). Global evidence of expressed sentiment alterations during the COVID-19 pandemic. Nature Human Behaviour, 6, 349–358. https://doi.org/10.1038/s41562-022-01312-y

Waniek, M., Holme, P., Farrahi, K., Emonet, R., Cebrian, M., & Rahwan, T. (2022). Trading contact tracing efficiency for finding patient zero. Scientific Reports, 12, Article 22582. https://doi.org/10.1038/s41598-022-26892-7

Yu, H., Zhou, Y., & Nussberger, A.-M. (2022). Gratitude is morally sensitive. Personality and Social Psychology Bulletin. Advance online publication. https://doi.org/10.1177/01461672221092273

Alfonseca, M., Cebrian, M., Anta, A. F., Coviello, L., Abeliuk, A., & Rahwan, I. (2021). Superintelligence cannot be contained: Lessons from computability theory. Journal of Artificial Intelligence Research, 70, 65–76. https://doi.org/10.1613/jair.1.12202