This page is still being polished. If you have thoughts, please share them via the feedback form.
Data on this page is preliminary and may change. Please do not share or cite these figures publicly.
Version control, prototyping, secure development practices, and engineering processes.
Also in Engineering & Development
In agile processes, ethical user stories [43, 93] can help the development team elicit ethical requirements for AI systems and implement AI ethics principles from the early stage of development. Ethical user stories are created to serve as items of the product backlog that is to be worked on by the development team in iterations (i.e., sprints). Card-based toolkits can be used to list questions related to AI ethics principles. The answers to those questions are integrated into ethical user stories to be included in sprint backlogs. The development team or users can write ethical user stories on cards or notes using a pre-defined template and assign them to different sprints based on priority
Ethical user stories make ethical requirements traceable both backward and forward, but they are difficult to scale for larger projects. The Guide for Artificial Intelligence Ethical Requirements Elicitation83 consists of 25 cards which are used by the development team to answer questions related to ethical principles. The answers are used to create ethical requirements in the form of ethical user stories which are included in sprint backlogs. ECCOLA [43] consists of 21 cards which are divided into eight themes and with questions to be answered by the development tea
Reasoning
Integrates ethical requirements into agile development workflows through structured sprint backlog practices.
Requirement Engineering
Governance Patterns
The governance for RAI systems can be defined as the structures and processes that are employed to ensure that the development and use of AI systems meet AI ethics principles. According to the structure of Shneiderman [104], governance can be built at three levels: industry level, organization level, and team level.
2.1 Oversight & AccountabilityGovernance Patterns > Industry-level governance patterns
3.1 Legal & RegulatoryGovernance Patterns > Organization-level governance patterns
2.1 Oversight & AccountabilityGovernance Patterns > Team-level governance patterns
2.1.2 Roles & AccountabilityProcess Patterns
The process patterns are reusable methods and best practices that can be used by the development team during the development process.
2.4.2 Design StandardsProcess Patterns > Requirement Engineering
2.4 Engineering & DevelopmentResponsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering
Lu, Qinghua; Zhu, Liming; Xu, Xiwei; Whittle, Jon; Zowghi, Didar; Jacquet, Aurelie (2024)
Responsible Artificial Intelligence (RAI) is widely considered as one of the greatest scientific challenges of our time and is key to increase the adoption of Artificial Intelligence (AI). Recently, a number of AI ethics principles frameworks have been published. However, without further guidance on best practices, practitioners are left with nothing much beyond truisms. In addition, significant efforts have been placed at algorithm level rather than system level, mainly focusing on a subset of mathematics-amenable ethical principles, such as fairness. Nevertheless, ethical issues can arise at any step of the development lifecycle, cutting across many AI and non-AI components of systems beyond AI algorithms and models. To operationalize RAI from a system perspective, in this article, we present an RAI Pattern Catalogue based on the results of a multivocal literature review. Rather than staying at the principle or algorithm level, we focus on patterns that AI system stakeholders can undertake in practice to ensure that the developed AI systems are responsible throughout the entire governance and engineering lifecycle. The RAI Pattern Catalogue classifies the patterns into three groups: multi-level governance patterns, trustworthy process patterns, and RAI-by-design product patterns. These patterns provide systematic and actionable guidance for stakeholders to implement RAI. © 2024 Copyright held by the owner/author(s).
Plan and Design
Designing the AI system, defining requirements, and planning development
Developer
Entity that creates, trains, or modifies the AI system
Map
Identifying and documenting AI risks, contexts, and impacts
Primary
6.5 Governance failure