Data Science & AI #4 - Shifting Machine Learning Value Creation Mechanisms

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Talk
Shifting ML value creation mechanisms: A process model of ML value creation by Dr. Konstantin Hopf
In the search for an appropriate strategic response to advancements in artificial intelligence (AI), firms are currently engaging in a large variety of AI projects. However, many companies are falling short in creating tangible business value through AI. Through qualitative research, Dr. Hopf identifies necessary conditions for successfully leveraging machine learning and AI.

Dr. Hopf illustrates how organizations engage in (resource) orchestration by shifting between ML value creation mechanisms as their capabilities evolve and business conditions change. He develops a model which provides an alternative explanation for the current high failure rate of ML projects.

Konstantin Hopf is a researcher at the University of Bamberg. His research interests include the integration of data science, especially machine learning techniques, in organizational decision-making processes and the development of novel methods to exploit spatio-temporal data sources with machine learning algorithms.