Artificial intelligence is increasingly becoming part of decision-making processes in healthcare, manufacturing, transportation, public administration, and other areas that have a direct impact on society. This makes it essential for AI recommendations to be not only accurate, but also understandable, transparent, and trustworthy.<\/p>\n\n\n\n
Explainable Artificial Intelligence (XAI) enables users to better understand the factors behind an AI system\u2019s conclusions. This helps experts validate results, identify potential biases, and make informed decisions.<\/p>\n\n\n\n
In high-risk domains, accuracy alone is not enough. Trustworthy AI also requires transparency, robustness, fairness, accountability, and an appropriate level of human oversight.<\/p>\n\n\n\n
As part of the European TANGO project, the Institute for Artificial Intelligence Research and Development of Serbia contributes to the development of AI technologies that put transparency, human oversight, and trust at the forefront, connecting AI research with real-world needs.<\/p>\n\n\n\n
Why is explainability essential for developing trustworthy AI, and how is IVI contributing to this goal?<\/p>\n\n\n\n