The Principle of Transparency of Use of Artificial Intelligence

AI transparency is often placed at the forefront in discussions about digital technologies regulation. Extending the scope of access to information to understanding AI is at the heart of the concept of explainable AI. This concept provides a framework of possible explanations for how AI works. These include: causal explanations (based on the traditional legal logic of cause and effect), counterfactual explanations (revealing those factors in the AI-based decision-making process that need to be changed to arrive at a different outcome), and in-context explanations (allowing citizens to protect their rights in court). However, AI transparency in the public sector can be hindered by the fact that programs are often created in the private sector and protected by intellectual property rights or trade secrets. In order to take into account and overcome various risks in the use of AI in public administration, it is necessary to establish the principle of transparency in a normative way, extending it to the use of AI in public administration, including the implementation of the concept of explainable AI.