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Fundamentals article about Machine Learning & Deep Learning

Artificial intelligence technology has started to shape how decisions are being taken and how intelligent information systems are being implemented today. However, artificial intelligence should not be considered as an abstract system property, but researchers and practitioners must also understand its inner workings as it affects many socio-technical issues downstream.

In our Electronic Markets fundamentals article “Machine Learning and Deep Learning”, together with co-authors Christian Janiesch and Kai Heinrich, we distinguish approaches for shallow machine learning and deep learning and explain the process of analytical model building from a more technical information systems perspective. Further, we detail four overarching challenges that research and practice will have to manage going forward.

The article aims to be a terminological baseline, gentle introduction and pointer to relevant work, as well as a motivator to approach said challenges.

The article is open access and available at: https://link.springer.com/article/10.1007%2Fs12525-021-00475-2