What term describes the need for AI systems to clearly explain their decision-making processes?

The term that describes the need for AI systems to clearly explain their decision-making processes is transparency. Transparency in AI refers to the extent to which the workings of an AI system can be understood and scrutinized by users, stakeholders, or affected individuals. It is essential in fostering trust and confidence in AI technologies, especially given their increasingly critical role in various sectors such as healthcare, finance, and criminal justice.

When AI systems provide clear explanations of their decision-making processes, users can better understand how conclusions are drawn, which can help to identify biases, ensure fairness, and facilitate accountability. This is particularly important when decisions significantly impact individuals’ lives, as it enables users to question and, if necessary, contest those decisions based on the rationale provided.

Other terms, while related to the ethical use of AI, do not specifically address the clarity of decision-making processes in the same way as transparency does. Accountability pertains to the responsibility of organizations or individuals for the outcomes of AI systems. Consent is about user agreement to the use of their data. Security risks are related to the potential threats that can compromise the integrity or confidentiality of the data used by AI systems. Therefore, transparency is the most appropriate term to describe the need for explanations of AI decision-making.