Artificial intelligence (AI) governance refers to the processes, standards and guardrails that help ensure AI systems and tools are safe and ethical. AI governance frameworks direct AI research, development and application to help ensure safety, fairness and respect for human rights.
Effective AI governance includes oversight mechanisms that address risks such as bias, privacy infringement and misuse while fostering innovation and building trust. An ethical AI-centered approach to AI governance requires the involvement of a wide range of stakeholders, including AI developers, users, policymakers and ethicists, ensuring that AI-related systems are developed and used to align with society’s values.
AI governance addresses the inherent flaws arising from the human element in AI creation and maintenance. Because AI is a product of highly engineered code and machine learning (ML) created by people, it is susceptible to human biases and errors that can result in discrimination and other harm to individuals.
Governance provides a structured approach to mitigate these potential risks. Such an approach can include sound AI policy, regulation and data governance. These help ensure that machine learning algorithms are monitored, evaluated and updated to prevent flawed or harmful decisions, and that data sets are well trained and maintained.
Governance also aims to establish the necessary oversight to align AI behaviors with ethical standards and societal expectations so as to safeguard against potential adverse impacts.