Interdisciplinary Perspective

Interdisciplinary research increasingly addresses complex challenges by integrating insights from diverse fields. Current efforts focus on applying this approach to understand and mitigate biases in AI systems, particularly large language models (LLMs), improve the design and regulation of AI, and enhance the analysis of complex data across various domains, including news media and scientific literature. This work leverages techniques from natural language processing, machine learning, and social sciences to develop more robust, ethical, and impactful technologies and analyses, ultimately aiming to improve both scientific understanding and societal well-being.