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Published October 27, 2025 | Version v4
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Explainability Requirement Practices and Challenges from a Brazilian Industrial Research and Innovation Company

Authors/Creators

  • 1. ROR icon Instituto Federal Goiano
  • 2. ROR icon Universidade Federal de Goiás
  • 3. Universidade Federal do Maranhão
  • 4. Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
  • 5. Federal University of Goiás

Contributors

Contact person:

  • 1. Federal University of Goiás
  • 2. ROR icon Universidade Federal do Maranhão
  • 3. Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
  • 4. ROR icon Universidade Federal de Goiás
  • 5. ROR icon Instituto Federal Goiano

Description

We conducted a study to investigate how professionals leading machine learning (ML) projects perceive explainability and the challenges they face when addressing it as a software requirement. Semi-structured interviews were conducted with 13 professionals responsible for ML projects, following a hypothetico-deductive approach. The collected data were analyzed based on the principles of Grounded Theory, using open and axial coding to identify emerging themes and relationships.

Files

Interview Flow - Explainability in ML Projects.pdf

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Additional details

Related works

Documents
Publication: Semi-Structured Interview (Other)

Dates

Other
2025
Semi-Structured Interview Protocol Document

References

  • Requirements Engineering, Explainability, Machine Learning, Interview