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Pekka Abrahamsson, PhD

Professor of Information Systems and Software Engineering
University of Jyväskylä

Dr. Pekka Abrahamsson works as a full professor of information systems and software engineering at the University of Jyväskylä in Finland. He received his PhD in Software Engineering in 2002 from the University of Oulu. His research is in the area of emerging software technologies, empirical software engineering, software startups, and the ethics of artificial intelligence. Before his current position, he has served as a full professor at the University of Helsinki (Finland), Free University of Bolzano (Italy), Norwegian University of Science and Technology (Norway). He also worked at VTT Technical Research Centre of Finland as a research professor of software technologies. He is widely recognized for his academic achievements. He is a pioneer in the field of research on agile software engineering methods and processes. Abrahamsson is the most cited researcher in his field in Finland. He is the first Professor of Software Engineering to be invited to the Finnish Academy of Science and Letters. He has published broadly in his areas of expertise and received many awards and recognitions. Arnetminer named him among the 100 most influential software engineering scientists in the world in 2016. Abrahamsson was awarded the Nokia Foundation Award 2007. He is the Software Startup Research Network (SSRN) co-founder and a seasoned expert in leading large research projects.


From Principles to Action: A Method for Ethically Aligned AI Design and Implementation

There is a common agreement that ethical concerns are of high importance when it comes to systems equipped with Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI-based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. These guidelines do not seem to help the developers. To bridge this gap, we present a method for implementing AI Ethics in practice. The ECCOLA method has been developed in collaboration with researchers and practitioners in the field, and it is under proof-testing in several AI companies. The presentation outlines the method and its practical use cases.