Digital governance models are frameworks or systems that help organisations manage their digital resources, decisions, and responsibilities. These models set out clear rules for who makes decisions about technology and digital services, ensuring that everyone understands their roles. They help organisations stay efficient, secure, and compliant with regulations when using digital tools and platforms.
Category: AI Governance
Automated Compliance Monitoring
Automated compliance monitoring uses software tools to check if an organisation is following rules, laws, and internal policies. Instead of manual reviews, it relies on technology to scan records, activities, and systems for any signs of non-compliance. This approach helps organisations spot problems quickly and ensures they meet regulatory standards without needing constant human oversight.
AI-Driven Decision Systems
AI-driven decision systems are computer programmes that use artificial intelligence to help make choices or solve problems. They analyse data, spot patterns, and suggest or automate decisions that might otherwise need human judgement. These systems are used in areas like healthcare, finance, and logistics to support or speed up important decisions.
Synthetic Oversight Loop
A Synthetic Oversight Loop is a process where artificial intelligence or automated systems monitor, review, and adjust other automated processes or outputs. This creates a continuous feedback cycle aimed at improving accuracy, safety, or compliance. It is often used in situations where human oversight would be too slow or resource-intensive, allowing systems to self-correct and…
Proxy Alignment Drift
Proxy alignment drift refers to the gradual shift that occurs when a system or agent starts optimising for an indirect goal, known as a proxy, rather than the true intended objective. Over time, the system may become increasingly focused on the proxy, losing alignment with what was originally intended. This issue is common in automated…
Ethical AI
Ethical AI refers to the development and use of artificial intelligence systems in ways that are fair, responsible, and respectful of human rights. It involves creating AI that avoids causing harm, respects privacy, and treats all people equally. The goal is to ensure that the benefits of AI are shared fairly and that negative impacts…
AI Governance
AI governance is the set of rules, processes, and structures that guide how artificial intelligence systems are developed, used, and managed. It covers everything from who is responsible for AI decisions to how to keep AI safe, fair, and transparent. The goal is to make sure AI benefits society and does not cause harm, while…
Bias Mitigation
Bias mitigation refers to the methods and strategies used to reduce unfairness or prejudice within data, algorithms, or decision-making processes. It aims to ensure that outcomes are not skewed against particular groups or individuals. By identifying and addressing sources of bias, bias mitigation helps create more equitable and trustworthy systems.
Responsible AI
Responsible AI refers to the practice of designing, developing and using artificial intelligence systems in ways that are ethical, fair and safe. It means making sure AI respects people’s rights, avoids causing harm and works transparently. Responsible AI also involves considering the impact of AI decisions on individuals and society, including issues like bias, privacy…