Artificial intelligence (AI), which refers to both a research field and a set of technologies, is rapidly growing and has already spread to application areas ranging from policing to healthcare and transport. The increasing AI …
Purpose Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users. Design/methodology/approach …
Governing artificial intelligence (AI) requires cooperation, although the collaboration’s form remains unclear. Technological frames provide a theoretical perspective for understanding how actors interpret a technology and act upon its development, use, and governance. However, we …
Artificial intelligence (AI) governance and auditing promise to bridge the gap between AI ethics principles and the responsible use of AI systems, but they require assessment mechanisms and metrics. Effective AI governance is not only …
Artificial intelligence (AI) governance is required to reap the benefits and manage the risks brought by AI systems. This means that ethical principles, such as fairness, need to be translated into practicable AI governance processes. …
