👉 Disclosure computing, also known as computational transparency or explainable AI (XAI), refers to the process of making AI systems' decision-making processes understandable and interpretable to humans. It involves developing techniques and tools that allow users to comprehend how AI models arrive at their conclusions, often by visualizing the data they use, explaining the logic behind their predictions, or providing insights into the model's internal workings. This is crucial for building trust between AI systems and their users, ensuring accountability, and enabling the identification and correction of biases or errors. Disclosure computing is essential in domains where AI decisions have significant impacts, such as healthcare, finance, and criminal justice, ensuring that these systems are not only effective but also fair and transparent.
