Advances in Information Systems (General Track)

Paper Type

Complete

Paper Number

1408

Description

Machine Learning (ML) is a rapidly-evolving branch of artificial intelligence. Responsible Machine Learning (RML) is the use of ethically-sound governance mechanisms, policies, controls and practices that prevent some ML errors and adverse events caused by ML, detect mistakes and adverse events that nevertheless occur, and minimize stakeholder harm by correcting ML mistakes and adjusting relevant systems, processes, controls and policies. This paper takes stock of relevant findings relevant in prior ML lit reviews and recent scholarly and practitioner papers published in premier IS journals, and offers suggestions for a program of research on RML.

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Aug 9th, 12:00 AM

Responsible Machine Learning Projects

Machine Learning (ML) is a rapidly-evolving branch of artificial intelligence. Responsible Machine Learning (RML) is the use of ethically-sound governance mechanisms, policies, controls and practices that prevent some ML errors and adverse events caused by ML, detect mistakes and adverse events that nevertheless occur, and minimize stakeholder harm by correcting ML mistakes and adjusting relevant systems, processes, controls and policies. This paper takes stock of relevant findings relevant in prior ML lit reviews and recent scholarly and practitioner papers published in premier IS journals, and offers suggestions for a program of research on RML.