Ethics of intelligence

Photo by Erhan Astam on Unsplash

Principal Investigators:

Ingo Schulz-Schaeffer
John-Dylan Haynes

Team members:

Dafna Burema (Postdoctoral researcher)
Mattis Jacobs
Rainer Mühlhoff

Ethical implications and debates on analytic and synthetic intelligence

Research Unit 4, SCIoI Project 19

SCIoI’s research will be confronted with an ongoing and extensive public debate, which results mainly from concerns about the growing ability of algorithms (in software and robotic systems) to become decision-makers and actors in all spheres of human life. Since SCIoI is basic research, most of its societal impacts will become apparent only in the (distant) future. Hence, every ethical reflection on societal impacts is subject to the Collingridge dilemma (Collingridge, 1980): In the early research process, predictions about the impacts of future technology are difficult. They only become more reliable when the technology has been extensively developed and is widely used. By then, however, any control or change is difficult, as the technology has already become entrenched.
In order to escape this dilemma, SCIoI implements ethical reflection as part of a responsible research and innovation (RRI) strategy. RRI itself is still in the process of developing its core concepts and methodology. So far, the focus of RRI has been primarily on applied research in key application areas such as information and communications technology (ICT), energy, nanotechnology, and synthetic biology. This project breaks new ground by transferring RRI to basic research, with a direct integration of ethics and technology-assessment (TA) experts into laboratory practices, and by exploring RRI within the area of robotics and intelligence research.
The aim is to take care of the future products of SCIoI’s research through a collective stewardship of analytic and synthetic researchers, ethicists and TA experts in order to make the overall research process more anticipatory, reflective, deliberative, and responsive (Owen et al., 2013). As a structural starting point, ethicists and TA experts are directly embedded in the laboratory teams to bring more reflective capacity into the practice of science and to kick-off a mutual learning process right from the beginning (Fisher et al., 2006; Van der Burg and Swierstra, 2013).




Related Publications

Mühlhoff, R. (2020). Automatisierte Ungleichheit: Ethik der Künstlichen Intelligenz in der biopolitische Wende des Digitalen Kapitalismus. Deutsche Zeitschrift Für Philosophie, 6(68).
Mühlhoff, R. (2020). Prädiktive Privatheit: Warum wir alle »etwas zu verbergen haben«. VerantwortungKI – Künstliche Intelligenz und gesellschaftliche Folgen, herausgegeben von Christoph Markschies und Isabella Hermann. Bd. 3/2020. Berlin-Brandenburgische Akademie der Wissenschaften.
Mühlhoff, R. (2021). Predictive Privacy: Towards an Applied Ethics of Data Analytics. Ethics and Information Technology.
Galbusera, L., Finn, M. T. M., Tschacher, W., & Kyselo, M. (2019). Interpersonal synchrony feels good but impedes self-regulation of affect. Scientific Reports, 9(1), 14691.
Burema, D., Jacobs, M., & Rozborski, F. (2023). Elusive technologies, elusive responsibilities: on the perceived responsibility of basic AI researchers. AI and Ethics.
Burema, D., Debowski-Weimann, N., Janowski, A. V., Grabowski, J., Maftei, M., Jacobs, M., Smagt, P. V. D., & Benbouzid, D. (2023). A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context. AAAI/ACM Conference on AI, Ethics, and Society (AIES ’23).