transparency and Explainability

transparency refers to providing disclosure on when an AI system is being used and the involvement of an AI system in decision making, what kind of data it uses, and its purpose.

In line with the principle of transparency, deployers have a responsibility to clearly disclose the implementation of an AI system to stakeholders and foster general awareness of the AI system being used.

An example of transparency in an AI enabled ecommerce platform is informing users that their purchase history is used by the platform’s recommendation algorithm to identify similar products and display them on the users’ feeds.

In cases where AI systems are procured directly from developers, deployers will have to work together with these developers to achieve transparency.

Organisations should be transparent about their data collection practices, including the types of data collected, how it is used, and who has access to it.