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This chapter provides guidance for how to think about the role that humans play in conducting analyses that include ML as part of the workflow. It introduces a stance towards ML as “intelligence augmentation” rather than “artificial intelligence” and articulates four key questions for an analyst to consider when setting up analysis. It also introduces computational grounded theory as an alternative to automation-focused applications of ML.

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Human-Machine Interactions in Machine Learning Modeling: The Role of Theory

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Christina Krist,
  • Marcus Kubsch,
  • Peter Wulff

摘要

This chapter provides guidance for how to think about the role that humans play in conducting analyses that include ML as part of the workflow. It introduces a stance towards ML as “intelligence augmentation” rather than “artificial intelligence” and articulates four key questions for an analyst to consider when setting up analysis. It also introduces computational grounded theory as an alternative to automation-focused applications of ML.