About SAIL

Artificial Intelligence is ubiquitous in our society and a key driver of economic growth. This comes with societal and technological challenges, as the increasing proliferation of current AI in society can reduce the autonomy of humans instead of supporting it. AI might impact individual human behavior as well as societal norms and structures in yet unprecedented ways. These challenges have led to the demand for a new wave of sustainable AI; AI that is transparent, allows for human agency, and is safe, robust, and resource-saving.

Our Network of Four Universities

Achieving these goals requires novel approaches that intertwine expertise in AI with attention to societal and environmental impacts. Sustainable AI can thus only be reached through cross-disciplinary research, which combines expertise in computer science and engineering with expertise in psychology, linguistics, and sociology, as well as strong relations to industry to deliver innovations to the market. With SAIL, we bring these disciplines and relations to industry together, bilding on our strong and successful research tradition of Bielefeld University, Paderborn University, Bielefeld University of Applied Sciences, and OWL University of Applied Sciences and Arts in jointly developing intelligent technical systems.

New Requirements for Intelligent Technical Systems

Intelligent technical systems (ITS) have AI technology at their core and are deployed in complex environments where they facilitate intelligent human-machine interaction and support intelligent process automation. Yet, current ITS are far from fulfilling the requirements which arise with the new wave of sustainable AI: Current research targets the introduction phase rather than the whole life-cycle of ITS in terms of the growth, maintenance, deprecation, and long-term societal, technological, and ecological impact of ITS’ AI models; current ITS focus on technological requirements, which are prominent in the introduction phase, rather than societal and human needs, which become apparent only within the long-term operation of ITS. As a consequence, current models may be biased, reflect distortions in training data, and lead to undesirable social consequences. In addition, current methods may be brittle or even dangerous if humans behave unexpectedly or the environment changes. Moreover, current AI technologies require massive data and compute resources, resulting in an unfavorable environmental footprint. To enable humans to remain in control of AI technology development, we require a fundamentally new perspective on how AI is embedded in the social process of building and using ITS. This new perspective is reflected in the research program of SAIL.


The Diversity Working Group (Diversity WG) within the SAIL project advocates for openness, equal opportunities, and diversity in the research community. We follow a holistic approach to promote diverse perspectives in research on intelligent socio-technical systems, as well as to mitigate bias and discrimination. We approach diversity from a multifaceted perspective, including features like gender, ethnicity, nationality, academic cultures, and languages. Our work aligns with a concept of diversity as a pluralistic perspective and situational interaction.

Long-Term Goal

The long-term goal of our network is to herald ITS of the next wave of AI by addressing societal, cognitive, and technological demands and by taking into account the whole life-cycle of AI. SAIL aims to perform high-impact fundamental research to develop crucial components of human-centered sustainable ITS; implement a strong transfer chain towards ITS applications of particular societal and industrial relevance; further strengthen the network’s structure into an internationally unique lighthouse in NRW for ITS.