Literatursammlung | FeKoM -Forschungsethik in der Kommunikations- und Medienwissenschaft

Kuenstliche Intelligenz

Wenn Sie die einzelnen Literatureinträge auswählen, bekommen Sie eine Zusammenfassung und weitere Informationen.

Brandenburg, S., Minge, M., Cymek, D. H., & Zeidler, L. (2017). Ethische Aspekte in der Forschung zu Mensch-Maschine-Systemen – Einblicke in die Arbeit einer Ethik-Kommission. Forschung, 3+4, 101–112.

Brown, S., Davidovic, J., & Hasan, A. (2021). The algorithm audit: Scoring the algorithms that score us. Big Data & Society, 8(1), 2053951720983865. https://doi.org/10.1177/2053951720983865

Engel, U., & Dahlhaus, L. (2021). Data quality and privacy concerns in digital trace data. In U. Engel, A. Quan-Haase, S. X. Liu, & L. Lyberg, Handbook of Computational Social Science, Volume 1 (pp. 343–362). Routledge. https://doi.org/10.4324/9781003024583-23

Gerdon, F., Bach, R. L., Kern, C., & Kreuter, F. (2022). Social impacts of algorithmic decision-making: A research agenda for the social sciences. Big Data & Society, 9(1). https://doi.org/10.1177/20539517221089305

Gilbert, J.-P., Ng, V., Niu, J., & Rees, E. E. (2020). A call for an ethical framework when using social media data for artificial intelligence applications in public health research. Canada Communicable Disease Report, 169–173. https://doi.org/10.14745/ccdr.v46i06a03

Hine, C. (2021). Evaluating the prospects for university-based ethical governance in artificial intelligence and data-driven innovation. 17(4), 464–479. https://doi.org/https://doi.org/10.1177/17470161211022790

Kieslich, K., Keller, B., & Starke, C. (2022). Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence. Big Data & Society, 9(1), 205395172210929. https://doi.org/10.1177/20539517221092956