mlsanityData to 7 Oct 2026

Towards a Roadmap on Software Engineering for Responsible AI

arXiv 2203.08594 ↗First posted 9 Mar 2022cs.SE cs.AIcited by 9

Not on the map. Why?

Abstract (arXiv)

Although AI is transforming the world, there are serious concerns about its ability to behave and make decisions responsibly. Many ethical regulations, principles, and frameworks for responsible AI have been issued recently. However, they are high level and difficult to put into practice. On the other hand, most AI researchers focus on algorithmic solutions, while the responsible AI challenges actually crosscut the entire engineering lifecycle and components of AI systems. To close the gap in operationalizing responsible AI, this paper aims to develop a roadmap on software engineering for responsible AI. The roadmap focuses on (i) establishing multi-level governance for responsible AI systems, (ii) setting up the development processes incorporating process-oriented practices for responsible AI systems, and (iii) building responsible-AI-by-design into AI systems through system-level architectural style, patterns and techniques.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 24 of its 112 references that are in the map. First posted on arXiv 9 Mar 2022.

Builds on

24 of 112 references.

References · 24

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  3. 2020Questioning the AI: Informing Design Practices for Explainable AI User Experiencescited by 251
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12 more
  1. 2019Towards Traceability in Data Ecosystems using a Bill of Materials Modelcited by 12
  2. 2020Reflexive Design for Fairness and Other Human Values in Formal Modelscited by 11
  3. 2021AI and Ethics -- Operationalising Responsible AIcited by 11
  4. 2020Developing and Operating Artificial Intelligence Models in Trustworthy Autonomous Systemscited by 10
  5. 2021Software Engineering for Responsible AI: An Empirical Study and Operationalised Patternscited by 9
  6. 2019A Study on the Prevalence of Human Values in Software Engineering Publications, 2015-2018cited by 4
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  8. 2021More Reliable AI Solution: Breast Ultrasound Diagnosis Using Multi-AI Combinationcited by 3
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 1; 2025: 1; 2026: 3.

9 papers.

  1. 2022Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineeringcited by 20
  2. 2022Never trust, always verify : a roadmap for Trustworthy AI?cited by 4
  3. 2023Responsible Design Patterns for Machine Learning Pipelinescited by 4
  4. 2024Fairness Concerns in App Reviews: A Study on AI-based Mobile Appscited by 4
  5. 2023Developing Responsible Chatbots for Financial Services: A Pattern-Oriented Responsible AI Engineering Approachcited by 1
  6. 2026Trustworthy AI Posture (TAIP): A Framework for Continuous AI Assurance of Agentic Systems at Horizontal and Vertical scalecited by 1
  7. 2025A Gray Literature Study on Fairness Requirements in AI-enabled Software Engineeringcited by 0
  8. 2026Intersectional Fairness in Large Language Modelscited by 0
  9. 2026Value-Preserving Architectures for Agentic AI Systemscited by 0