Generative AI for Visualization: Opportunities and Challenges

• Published in: IEEE computer graphics and applications Vol. 44; no. 2; pp. 55 - 64
• Main Authors: Basole, Rahul C., Major, Timothy, Ferrise, Francesco
• Format: Magazine Article
• Language: English
• Published: United States IEEE 01.03.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Augmented reality; Generative AI; Generative artificial intelligence; Machine learning; Media; Visualization
• ISSN: 0272-1716; 1558-1756; 1558-1756
• DOI: 10.1109/MCG.2024.3362168

Recent developments in artificial intelligence (AI) and machine learning (ML) have led to the creation of powerful generative AI methods and tools capable of producing text, code, images, and other media in response to user prompts. Significant interest in the technology has led to speculation about what fields, including visualization, can be augmented or replaced by such approaches. However, there remains a lack of understanding about which visualization activities may be particularly suitable for the application of generative AI. Drawing on examples from the field, we map current and emerging capabilities of generative AI across the different phases of the visualization lifecycle and describe salient opportunities and challenges.