Ethical and social concerns are a key obstacle to the adoption of artificial intelligence (AI) in the life sciences and beyond. The discussion of these issues has intensified in recent years and led to a number of approaches, tools and initiatives. Key amongst them is the idea of ex-ante impact assessments that aim to identify issues at the early stages of development. One prominent example of such ex-ante impact assessment is the European Union's (EU) Assessment list for Trustworthy AI (ALTAI). This article uses the findings of a large-scale application of the ALTAI to a large neuro-informatics project as an exemplar to demonstrate the effectiveness and limitations of the ALTAI in practice. The article shows that ex-ante impact assessment has the potential to help identify and address ethical and social issues. However, they need to be understood as part of a broader socio-technical ecosystem of AI. For ALTAI and related approaches to be useful in bio-medical research, they should be interpreted from a systems theory perspective which allows for their integration into the rich set of tools, legislation and approaches. The paper argues that ex-ante impact assessments have the best chance of being successful if seen applied in conjunction with other approaches in the context of the overall AI ecosystem.
Stahl, B. C., & Leach, T. (2022). Assessing the ethical and social concerns of artificial intelligence in neuroinformatics research: an empirical test of the European Union Assessment List for Trustworthy AI (ALTAI). AI and Ethics, https://doi.org/10.1007/s43681-022-00201-4