AI in the Cosmos
It tackles the problem of AI reliability and ethics in astrophysics research, which is incremental as it builds on existing AI methods with a focus on human integration.
This review addresses the application of AI in astrophysics for tasks like source classification and data modeling, highlighting challenges such as biases and interpretability, and proposes Human-Guided AI (HG-AI) to enhance robustness and ethics.
Artificial intelligence (AI) is revolutionizing research by enabling the efficient analysis of large datasets and the discovery of hidden patterns. In astrophysics, AI has become essential, transforming the classification of celestial sources, data modeling, and the interpretation of observations. In this review, I highlight examples of AI applications in astrophysics, including source classification, spectral energy distribution modeling, and discuss the advancements achievable through generative AI. However, the use of AI introduces challenges, including biases, errors, and the "black box" nature of AI models, which must be resolved before their application. These issues can be addressed through the concept of Human-Guided AI (HG-AI), which integrates human expertise and domain-specific knowledge into AI applications. This approach aims to ensure that AI is applied in a robust, interpretable, and ethical manner, leading to deeper insights and fostering scientific excellence.