Generative AI for Visualization: Opportunities and Challenges
Rahul C. Basole -
Timothy Major -
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DOI: 10.1109/MCG.2024.3362168
Room: Bayshore III
2024-10-17T17:00:00ZGMT-0600Change your timezone on the schedule page
2024-10-17T17:00:00Z
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Keywords
Generative AI, Art, Artificial Intelligence, Machine Learning, Visualization, Media, Augmented Reality, Machine Learning, Visual Representation, Professional Knowledge, Creative Process, Domain Experts, Generalization Capability, Development Of Artificial Intelligence, Artificial Intelligence Capabilities, Iterative Process, Natural Language, Commercial Software, Hallucinations, Team Sports, Design Requirements, Intelligence Agencies, Recommender Systems, User Requirements, Iterative Design, Use Of Artificial Intelligence, Visual Design, Phase Assemblage, Data Literacy
Abstract
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.