FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines

Matthew Barker, Emma Kallina, Dhananjay Ashok, Katherine M. Collins, Ashley Casovan +4 more
7/28/2023
cs.HCcs.AIcs.LG

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Abstract

Even though machine learning (ML) pipelines affect an increasing array of stakeholders, there is little work on how input from stakeholders is recorded and incorporated. We propose FeedbackLogs, addenda to existing documentation of ML pipelines, to track the input of multiple stakeholders. Each log records important details about the feedback collection process, the feedback itself, and how the feedback is used to update the ML pipeline. In this paper, we introduce and formalise a process for collecting a FeedbackLog. We also provide concrete use cases where FeedbackLogs can be employed as evidence for algorithmic auditing and as a tool to record updates based on stakeholder feedback.

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Cite this paper

@article{barker2023feedbacklogs,
  title  = {FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines},
  author = {Matthew Barker and Emma Kallina and Dhananjay Ashok and Katherine M. Collins and Ashley Casovan and Adrian Weller and Ameet Talwalkar and Valerie Chen and Umang Bhatt},
  year   = {2023},
  eprint = {2307.15475},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.15475v1}
}

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