title: Show Me the Work: Fact-Checkers' Requirements for Explainable Automated
    Fact-Checking
summary: The pervasiveness of large language models and generative AI in online media
  has amplified the need for effective automated fact-checking to assist
  fact-checkers in tackling the increasing volume and sophistication of
  misinformation. The complex nature of fact-checking demands that automated
  fact-checking systems provide explanations that enable fact-checkers to
  scrutinise their outputs. However, it is unclear how these explanations should
  align with the decision-making and reasoning processes of fact-checkers to be
  effectively integrated into their workflows. Through semi-structured interviews
  with fact-checking professionals, we bridge this gap by: (i) providing an
  account of how fact-checkers assess evidence, make decisions, and explain their
  processes; (ii) examining how fact-checkers use automated tools in practice;
  and (iii) identifying fact-checker explanation requirements for automated
  fact-checking tools. The findings show unmet explanation needs and identify
  important criteria for replicable fact-checking explanations that trace the
  model's reasoning path, reference specific evidence, and highlight uncertainty
  and information gaps.
paper_authors._id: 67b30726d4665a0448e6436d
paper_authors.name: Greta Warren
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-18T09:32:34.585Z
paper_authors._id: 6698cffdb2ebada9f4a7e7d7
paper_authors.avatarUrl: /avatars/e66d946c14595d3b008185f2be8d2f57.svg
paper_authors.fullname: Greta Warren
paper_authors.type: user
paper_authors.user: gretawarren
paper_authors._id: 67b30726d4665a0448e6436e
paper_authors.name: Irina Shklovski
paper_authors._id: 67b30726d4665a0448e6436f
paper_authors.name: Isabelle Augenstein
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-19T15:49:35.332Z
paper_authors._id: 608918b7df398c3b285ce960
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1621507769190-608918b7df398c3b285ce960.jpeg
paper_authors.fullname: Isabelle Augenstein
paper_authors.type: user
paper_authors.user: IAugenstein
paper_title: Show Me the Work: Fact-Checkers' Requirements for Explainable Automated
    Fact-Checking
paper_summary: The pervasiveness of large language models and generative AI in online media
  has amplified the need for effective automated fact-checking to assist
  fact-checkers in tackling the increasing volume and sophistication of
  misinformation. The complex nature of fact-checking demands that automated
  fact-checking systems provide explanations that enable fact-checkers to
  scrutinise their outputs. However, it is unclear how these explanations should
  align with the decision-making and reasoning processes of fact-checkers to be
  effectively integrated into their workflows. Through semi-structured interviews
  with fact-checking professionals, we bridge this gap by: (i) providing an
  account of how fact-checkers assess evidence, make decisions, and explain their
  processes; (ii) examining how fact-checkers use automated tools in practice;
  and (iii) identifying fact-checker explanation requirements for automated
  fact-checking tools. The findings show unmet explanation needs and identify
  important criteria for replicable fact-checking explanations that trace the
  model's reasoning path, reference specific evidence, and highlight uncertainty
  and information gaps.