What does explainable AI (XAI) aim to achieve?

Explainable AI (XAI) aims to make AI systems transparent and understandable. This is crucial because as AI systems become increasingly integrated into various sectors, stakeholders want to comprehend how these systems arrive at their decisions. Transparency fosters trust and accountability, allowing users to see not only the outcomes produced by AI but also the reasoning behind those outcomes. This understanding helps in verifying the reliability and fairness of AI predictions, making it easier to identify potential biases and errors. Furthermore, when users can interpret AI decision-making, they are better equipped to incorporate these insights into their own decision processes, ensuring that AI acts as a support tool rather than a black box.

The focus of XAI is not on increasing complexity, speeding up algorithms, or abstracting decision-making processes. In fact, the goal is to simplify and clarify these processes so that they can be scrutinized and understood, which is essential for ethical AI deployment in society.