Operationalizing Human Values in Software Engineering: A Survey
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Abstract (arXiv)
Human values (e.g., pleasure, privacy, and social justice) are what a person or a society considers important. The inability to address them in software-intensive systems can result in numerous undesired consequences (e.g., financial losses) for individuals and communities. Various solutions (e.g., methodologies, techniques) are developed to help "operationalize values in software". The ultimate goal is to ensure building software (better) reflects and respects human values. In this survey, "operationalizing values" is referred to as the process of identifying human values and translating them to accessible and concrete concepts so that they can be implemented, validated, verified, and measured in software. This paper provides a deep understanding of the research landscape on operationalizing values in software engineering, covering 51 primary studies. It also presents an analysis and taxonomy of 51 solutions for operationalizing values in software engineering. Our survey reveals that most solutions attempt to help operationalize values in the early phases (requirements and design) of the software development life cycle. However, the later phases (implementation and testing) and other aspects of software development (e.g., "team organization") still need adequate consideration. We outline implications for research and practice and identify open issues and future research directions to advance this area.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Aug 2021.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 3; 2026: 2.
6 papers.
- 2022Towards a multi-stakeholder value-based assessment framework for algorithmic systemscited by 12
- 2025Learning the Value Systems of Societies from Preferencescited by 2
- 2026Learning the Value Systems of Agents with Preference-based and Inverse Reinforcement Learningcited by 1
- 2025RobEthiChor: Automated Context-aware Ethics-based Negotiation for Autonomous Robotscited by 0
- 2025Advancing Automated Ethical Profiling in SE: a Zero-Shot Evaluation of LLM Reasoningcited by 0
- 2026Value-Preserving Architectures for Agentic AI Systemscited by 0
- 2026Value-Preserving Architectures for Agentic AI Systems3 Sep 2026
- 2026Learning the Value Systems of Agents with Preference-based and Inverse Reinforcement Learning4 Feb 2026
- 2025Advancing Automated Ethical Profiling in SE: a Zero-Shot Evaluation of LLM Reasoning1 Oct 2025
- 2025RobEthiChor: Automated Context-aware Ethics-based Negotiation for Autonomous Robots30 Jul 2025
- 2025Learning the Value Systems of Societies from Preferences28 Jul 2025
- 2022Towards a multi-stakeholder value-based assessment framework for algorithmic systems9 May 2022