Guiding the specification of sociotechnical Machine Learning systems

Addressing vulnerabilities and challenges in Machine Learning practice

Master thesis (2022)

Authors

A.E. Wolters Technology, Policy and Management

Contributors

M.F.W.H.A. Janssen (supervisor 2)
R.I.J. Dobbe (supervisor 1)
F.S. Gürses Organisation & Governance - TPM (supervisor 2)
Nick Jetten (supervisor 1)
Faculty
Technology, Policy and Management
Copyright: © 2022 Anouk Wolters
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Published Date

10-05-2022

Language

English

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Faculty

Technology, Policy and Management

Abstract

There is a need for a more comprehensive sociotechnical systems view on ML. Such a view looks at the development and use of an ML system in practice as being a sociotechnical ML system: "a system consisting of technical artefacts, human agents and institutions, in which a machine-based subsystem influences its real or virtual environment by automating, supporting or augmenting decision-making". This research takes on this view to design a sociotechnical guide for ML practice, centring the specication of sociotechnical ML systems. Taking on the guidelines contributes to a safe and effective development and use of ML systems.