Governing Algorithmic Systems in the Social Domain

Providing a socio-technical description of algorithmic systems in the SUWI-domain using Systems Safety and Actor Analyses

Master thesis (2024)

Authors

W.W.C. Segeren Technology, Policy and Management

Contributors

H.G. van der Voort Organisation & Governance - TPM (graduation committee member)
R.I.J. Dobbe (mentor)
G. Hopster (graduation committee member)
S. Kulk (graduation committee member)
Faculty
Technology, Policy and Management
More Info
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Published Date

01-07-2024

Language

English

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Faculty

Technology, Policy and Management

Abstract

This research looked into Algorithmic Systems used in the execution of the SUWI-law by executing agencies. It analysed the use and governance of these systems and their possible harms to citizens and society by means of an Actor Analysis and System-Theoretical Process Analysis (STPA), supported by semi-structured interviews.

It aimed to answer the following research question:
How can a systems safety perspective combined with an actor perspective be used to provide a sociotechnical description of algorithmic systems, their governance and possible hazards at agencies executing the SUWI-law?

By means of the Actor Analysis, this research was able to describe the actor field and implications of it on the problem situation. The main insight from the actor field was the presence of ‘double binds’, several value conflicts that trouble use of AS. STPA, a method that focusses on safety of a system as a whole rather than individual components, provided the ability to map algorithmic systems within their sociotechnical context. It focussed on three hazards, which are system states that lead to accidents. These three hazards were the use of flawed logic in algorithmic systems, the use of flawed information in algorithmic system, and the flawed understanding citizens have of the role of the systems. They were explored through a Safety Control Structure, which displays controlled processes and those controlling them, and the construction of causal scenarios.
Semi-structured interviews focussed on the governance of algorithmic systems, and possible improvements. They provided empirical input for STPA.
The main contributions of this research are the proposal it makes for a sociotechnical description of algorithmic systems and their harms, using concepts derived from STPA. Such descriptions can be used to build shared understanding of algorithmic systems and their harms. It showed how such a description can be constructed using an Actor Analysis, interviews, and STPA, describing how these methods work together.