RAI User Story

Summary: RAI requirements can be elicited and incorporated into the product backlog in the form of RAI user stories.

Type of pattern: Process pattern

Type of objective: Trustworthiness

Target users: Product managers, business analysts, AI users, AI consumers

Impacted stakeholders: Developers, data scientists, testers, operators

Lifecycle stages: Requirements

Relevant AI ethics principles: Human, societal and environmental wellbeing, human-centered values, fairness, privacy protection and security, reliability and safety, transparency and explainability, contestability, accountability

Mapping to AI regulations/standards: ISO/IEC 42001:2023 Standard.

Context: Considering AI ethics from the early stages of AI system development is crucial. However, it can be challenging because AI ethics principles are often high-level and abstract, providing limited guidance to the development team. Additionally, RAI requirements are often overlooked or only briefly described as project objectives. It is necessary to use specific requirements elicitation methods to collect detailed RAI requirements from relevant stakeholders.

Problem: How can RAI requirements be elicited?

Solution: In an agile development process, RAI user stories are created and added to the product backlog. These RAI user stories can be tackled by the development team during sprints. One way to facilitate the creation of RAI user stories is by using card-based toolkits, which list questions related to AI ethics principles. The answers to these questions then can be integrated into RAI user stores and included in sprint backlogs. The development team or users can write RAI user stories on cards or notes using predefined templates and assign them to different sprints based on the priority.


  • Increased traceability: RAI user stories make RAI requirements traceable both backward and forward.
  • RAI requirements elicitation: RAI user stories can help the development team elicit RAI requirements for AI systems and implement AI ethics principles from the early stage of development.
  • Ethical awareness: RAI user stories can help to increase the RAI awareness of the development team.


  • Lack of scalability: RAI user stories are difficult to scale for larger projects.
  • Bias: The process of writing RAI user stories maybe influenced by the personal biases of the stakeholders involved.
  • Inability to anticipate all RAI concerns: It is possible to miss some RAI concerns when identifying the RAI requirements.

Related patterns:

  • Verifiable RAI requirement: Acceptance criteria should be included in the RAI user stories to make the RAI requirements verifiable.
  • RAI acceptance testing: In the agile process, the customer can write the acceptance tests before the development team implements the RAI user story.

Known uses: