Module Contents
Introduction to this Module
This workbook aims to provide resources and training which help you and your team to ethically steward the data you access and utilise by proactively initiating and facilitating responsible data practices. You will learn how to use these tools and how they may be relevant at different stages of the project lifecycle. The tools, approaches, and policies introduced should be discussed with your core team and your stakeholders, and should be clearly documented.
Data is essential in developing AI models and systems, forming the core information on which they are trained, and, as such, shaping their knowledge base and epistemic (knowledge-contributing) capacity. For this reason, responsible data stewardship is crucial for developing ethical and responsible AI.
KEY CONCEPTS
This section provides content for workshop participants and facilitators to engage with prior to attending each workshop. This section demystifies AI and ML by discussing foundational components that make up AI systems, providing definitions of key terms, an overview of the stages for building AI models, and a brief introduction to AI ethics.
It provides an overview of the frameworks that will be explored in more detail in subsequent modules.
ACTIVITIES
This section provides a set of group-based activities that can be used in a workshop to explore the core ideas of this module. Each activity corresponds to a specific section in the Key Concepts. Instructions are provided for both facilitators and participants.
Case studies within the AI Ethics and Governance in Practice workbook series are grounded in public sector use cases, but do not reference specific AI projects.
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