SOCITM Digital Ethics Collection

Created By:  Magnus Smidak
Last updated: 15 May 2024

The Socitm Digital Ethics collection, provides comprehensive insights into the ethical considerations of deploying digital technologies in public service. These resources guide the ethical use, design, and governance of emerging technologies, highlighting the importance of transparency, fairness, and respect for privacy and human rights in digital initiatives.

The Socitm Digital Ethics collection encapsulates a broad spectrum of resources aimed at facilitating the ethical adoption of digital technologies in public services. The "Digital Ethics in Context" section provides a foundational understanding of digital ethics, emphasizing the role of moral principles in governing behaviour and decision-making in the digital realm. The "Glossary" serves as a helpful resource for understanding key terms in artificial intelligence (AI) and computer science, essential for navigating the complex landscape of digital ethics.

The "Emerging Tools" segment compiles a wide range of tools and frameworks designed to support the ethical design phase of using emerging technologies and data analytics. These tools are developed by various organizations, including governments, public sector bodies, universities, and industry, focusing on the ethical impacts of digital technology on society.

"Emerging Guidance" collects guidance resources developed to advise on the ethical use of emerging technologies and data, focusing on the design phase and operational level of service delivery. It addresses how emerging technologies and data analytics can be used ethically to deliver public services and solutions, aiming to ensure that technology benefits society while minimizing risks and negative impacts.

Lastly, the "Emerging Technical Standards" section highlights the ongoing efforts to establish technical standards for the ethical design and use of autonomous and intelligent systems. These standards, such as IEEE P7000™ series, aim to address ethical concerns, including transparency, data privacy, bias, and the wellbeing metrics of AI and autonomous systems, ensuring that technological advancements align with ethical principles and values.

Category: Characteristics » Use of data and intelligence Data maturity Data maturity » Leadership and strategy Data maturity » Skills and capability Data maturity » Governance and compliance