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Paper Type

ERF

Paper Number

1567

Description

Legal regulations such as European General Data Protection Regulation have put transparency as an essential characteristic of data-based information systems firmly into the focus of the system developers. Furthermore, enterprises increasingly consider challenging machine learning-based systems (MLS) to support particular business functions and hence require informed decisions based on explainable results of the MLS. This research in progress explores the information needs for the adaptation of predictive analytics MLS in a commercial setting. Using scenario-based survey and based on the technology acceptance model, insights into the transparency requirements from the users’ perspective are derived and future research directions are outlined. This empirical investigation provides suggestions for potential factors influencing the adaptation of MLS in business context and supports design decisions for MLS. Future directions for the exploration of the role of transparency requirements for the acceptance of machine learning-based information systems are outlined.

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Aug 10th, 12:00 AM

Transparency as a Potential Factor for Implementation of Machine Learning-based Systems

Legal regulations such as European General Data Protection Regulation have put transparency as an essential characteristic of data-based information systems firmly into the focus of the system developers. Furthermore, enterprises increasingly consider challenging machine learning-based systems (MLS) to support particular business functions and hence require informed decisions based on explainable results of the MLS. This research in progress explores the information needs for the adaptation of predictive analytics MLS in a commercial setting. Using scenario-based survey and based on the technology acceptance model, insights into the transparency requirements from the users’ perspective are derived and future research directions are outlined. This empirical investigation provides suggestions for potential factors influencing the adaptation of MLS in business context and supports design decisions for MLS. Future directions for the exploration of the role of transparency requirements for the acceptance of machine learning-based information systems are outlined.

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