Der Einfluss von Maschinen auf den Menschen
Leitfrage: Wie verändern Algorithmen den Einzelnen, Gruppen und ganze Gesellschaften?
Maschinen sind ein fester Bestandteil unseres täglichen Lebens. Da wir stark von unserer Umwelt geprägt sind, stellt sich die Frage, wie der Umgang mit Maschinen den Einzelnen, die Gruppe und ganze Gesellschaften verändern könnte. Die Forschungsgruppe untersucht, welche Auswirkungen unsere Beziehung zu Maschinen haben könnte.
Projektleiter*innen
Ausgewählte Literatur
Groh, M., Epstein, Z., Obradovich, N., Cebrian, M., and Rahwan, I. (forthcoming). Human detection of machine manipulated media. Communications of the ACM. (arXiv).
Obradovich, N.∗,Özack, Ö.∗, Martín, I.∗, Ortuño-Ortín, I., Awad, E., Cebrian, M.,Cuevas, R., Desmet, K., Rahwan, I., Cuevas, Á. (2020). Expanding the measurement of culture with a sample of two billion humans. (NBER). (∗ denotes equal contribution).
Bonnefon, J. F., & Rahwan, I. (2020). Machine Thinking, Fast and Slow. Trends in Cognitive Sciences. 24(12):1019–1027Rahwan, I., Crandall, J. W., & Bonnefon, J. F. (2020). Intelligent machines as social catalysts. Proceedings of the National Academy of Sciences, 117(14), 7555-7557.
Serna, I., Morales, A., Fierrez, J., Cebrian, M., Obradovich, N., and Rahwan, I. (2020). Algorithmic discrimination: Formulation and exploration in deep learning-based face biometrics. Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020).
Serna, I., Morales, A., Fierrez, J., Cebrian, M., Obradovich, N., and Rahwan, I. (2020). SensitiveLoss: Improving accuracy and fairness of face representations with discrimination-aware deep learning. (arXiv)
Mir, R., Felbo, B., Obradovich, N., and Rahwan, I. (2019). Evaluating style transfer for text. Annual Conference of the North American Chapter of the Association for Computational Linguistics.
Rahwan, I.∗, Cebrian, M.∗, Obradovich, N.∗ et al. Machine behaviour. Nature 568, 477–486 (2019). https://doi.org/10.1038/s41586-019-1138-y (∗ denotes equal contribution).
Ishowo-Oloko, F., Bonnefon, J., Soroye, Z. et al. Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation. Nat Mach Intell 1, 517–521 (2019). https://doi.org/10.1038/s42256-019-0113-5
Crandall, J.W., Oudah, M., Tennom et al. Cooperating with machines. Nat Commun 9, 233 (2018). https://doi.org/10.1038/s41467-017-02597-8
Garcia, D., Kassa, Y. M., Cuevas, A., Cebrian, M., Moro, E., Rahwan, I., & Cuevas, R. (2018). Analyzing gender inequality through large-scale Facebook advertising data. Proceedings of the National Academy of Sciences, 115(27), 6958-6963.
Epstein, Z., Payne, B.H., Shen, J.H., Hong, C.J., Dubey, A., Felbo, B., Groh, M., Obradovich, N., Cebrian, M., and Rahwan, I. (2018). TuringBox: An experimental platform for the evaluation of AI systems. International Joint Conference on Artificial Intelligence (IJCAI). Demo Track.
Epstein, Z., Payne, B.H., Shen, J.H., Dubey, A., Felbo, B., Groh, M., Obradovich, N.,Cebrian, M., and Rahwan, I. (2018). Closing the AI knowledge gap. (arXiv).