En Salón de Actos de la EPS IV el día 30/01/2023 a las 11:00:00
Nombre | Towards Explainable AI | ||
---|---|---|---|
Autor | Universidad de Alicante | ||
Título | Towards Explainable AI | ||
Resumen | AI systems have become the de facto tools to solve complex problems in computer vision. Yet, it has been shown that these systems might not actually be safe to be deployed in the real world, as they too often tend to rely on dataset biases and other statistical shortcuts to achieve high performance. A growing body of research thus focuses on the development of explainability methods to better interpret these systems, to make them more trustworthy. In this talk, I will first give a general overview of the methods commonly used in eXplainable AI, before discussing the challenges that still need to be overcome by the community. | ||
Duración | 00:52:29.00 | ||
Keywords | artificial intelligence inteligencia artificial ellis | ||
Material incluido en las siguientes colecciones
|
|||
Usuario | malozanoua.es | ||
Tipo | DIRECTO | ||
Visitas | 203 | ||
Tamaño | 109.88MB |