World Conference on eXplainable Artificial Intelligence’s Post

🔎 𝗫𝗔𝗜 𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝟮𝟬𝟮𝟱 - 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗧𝗿𝗮𝗰𝗸 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁: 🖥️ Generative AI meets explainable AI ✏️ 𝗔𝘂𝘁𝗵𝗼𝗿𝘀: Przemyslaw Biecek Christin Seifert Sebastian Lapuschkin Sonia Laguna Cillero Chirag Agarwal Hubert Baniecki Bartłomiej Sobieski 🔗 𝗟𝗲𝗮𝗿𝗻 𝗠𝗼𝗿𝗲 𝗛𝗲𝗿𝗲: https://lnkd.in/dFnd_4dp 𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁: Generative Artificial Intelligence (GenAI) is revolutionizing machine learning research and rapidly pushing the boundaries of computer vision, natural language processing, and multi-modal learning. This phenomenon has already raised significant concerns regarding the extreme complexity of machine learning systems. The effective and safe implementation of GenAI solutions must align with a deeper understanding of their decision-making processes. Historically focused on purely predictive models, the eXplainable Artificial Intelligence (XAI) domain has tackled the challenge of understandability for years. However, current XAI methods often constrain human creativity when debugging machine learning systems. The field of XAI is now at a pivotal point where the focus is shifting from simply understanding AI model outputs and inner logic to a new paradigm. In this paradigm, explainability becomes a tool for verifying, mining, and exploring information, including outputs from AI and other automated decision-making systems. This special track emphasizes the critical role generative AI can play in enhancing explainability, enabling constructive verification of both AI model outputs and human decisions/intuitions. With this in mind, we distinguish between two key themes: i)How GenAI can advance the frontier of XAI (GenAI for XAI). ii) How the XAI experience can address critical challenges in GenAI (XAI for GenAI). The goal of this track is to bridge the two domains and integrate their development, fostering innovation and collaboration. #general #artificialintelligence #deeplearning #interpretability #generativeAI #explainability #enhancement #innovation #explanations #GenXAI