Blind spots in AI ethics

A wrote a critical piece about my own field of research. It discusses the conservative nature of AI ethics’ main principles as well as the disregarding of negative externalities of AI technologies. The paper was recently published in AI and Ethics and can be accessed here.

Recent papers

Recently, three new papers have been published. Together with Kristof Meding, I conducted an empirical study on industry partners in AI research. The study is based on an analysis of nearly 11,000 publications from the most important AI conferences. The paper was published in “AI & Society” and can be read here.

A further paper appeared in “Minds and Machines” in which I argue for providing AI systems only those “environmental stimuli” for training that result in ethically desirable machine behavior. The idea is to overcome the Big Data principle of n=all in order to use new dimensions of data quality to better segregate which datafied behaviors are allowed to become training stimuli for machine learning applications in the first place. The paper can be viewed here.

Another paper I co-authored with my colleague Paula Helm critically addresses AI-based policing software. While predictive policing systems are often studied in this area, we explicitly looked at software used for criminal prosecution. An overview of these and other publications can be found here.