Algorithms play a crucial role in many technological systems that control or affect various aspects of our lives. As a result, providing explanations for their decisions to address the needs of users and organisations is increasingly expected by laws, regulations, codes of conduct, and the public. However, as laws and regulations do not prescribe how to meet such expectations, organisations are often left to devise their own approaches to explainability, inevitably increasing the cost of compliance and good governance. Hence, we envision Explainability-by-Design, a holistic methodology characterised by proactive measures to include explanation capability in the design of decision-making systems. The methodology consists of three phases: (A) Explanation Requirement Analysis, (B) Explanation Technical Design, and (C) Explanation Validation. This paper describes phase (B), a technical workflow to implement explanation capability from requirements elicited by domain experts for a specific application context. Outputs of this phase are a set of configurations, allowing a reusable explanation service to exploit logs provided by the target application to create provenance traces of the application's decisions. The provenance then can be queried to extract relevant data points, which can be used in explanation plans to construct explanations personalised to their consumers. Following the workflow, organisations can design their decision-making systems to produce explanations that meet the specified requirements. To facilitate the process, we present a software architecture with reusable components to incorporate the resulting explanation capability into an application. Finally, we applied the workflow to two application scenarios and measured the associated development costs. It was shown that the approach is tractable in terms of development time, which can be as low as two hours per sentence.

翻译：算法在许多控制或影响我们生活方方面面的技术系统中扮演着关键角色。因此，为满足用户和组织需求而对其决策提供解释，日益受到法律法规、行为准则及公众的期待。然而，由于法律法规并未规定如何满足此类期待，组织往往需要自行设计可解释性方案，这不可避免地增加了合规与善治的成本。为此，我们提出“可解释性内建”这一整体方法论，其特点在于采取主动措施，将解释能力纳入决策系统的设计之中。该方法论包含三个阶段：(A) 解释需求分析、(B) 解释技术设计与(C) 解释验证。本文描述阶段(B)，即根据领域专家针对特定应用场景所获取的需求，实现解释能力的技术工作流。该阶段的输出是一组配置，使得可重用的解释服务能够利用目标应用提供的日志，为应用的决策创建溯源轨迹。随后，可查询溯源信息以提取相关数据点，这些数据点可用于解释计划，从而构建面向不同消费者的个性化解释。遵循此工作流，组织可设计其决策系统，以生成满足特定需求的解释。为便利该过程，我们提出一种包含可重用组件的软件架构，用于将最终的解释能力集成至应用之中。最后，我们将该工作流应用于两个应用场景，并测量了相关的开发成本。结果表明，该方法在开发时间方面具有可行性，最低可达每句两小时。