Doom or Deliciousness: Challenges and Opportunities for Visualization in the Age of Generative Models

Schetinger, Victor; Bartolomeo, Soraya Di; El‐Assady, Mennatallah; McNutt, Andrew; Miller, Matthias; Passos, Joana Célia dos; Adams, Jane Lydia

doi:10.1111/cgf.14841

Cited by 18 publications

(2 citation statements)

References 71 publications

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“…Also, the creative power [14], practices, and risks of the co-creative artificial generative ecosystem have been analyzed [15]. Specific design areas also try to provide us with an understanding of the professional's perceived challenges and opportunities, like the visualization [16] or the communication [17] domain. Likewise, in web design, researchers try to understand how to integrate AI tools into the design process [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Generative Artificial Intelligence Image Tools among Future Designers: A Usability, User Experience, and Emotional Analysis

Casteleiro-Pitrez

2024

Digital

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Generative Artificial Intelligence (GenAI) image tools hold the promise of revolutionizing a designer’s creative process. The increasing supply of this type of tool leads us to consider whether they suit future design professionals. This study aims to unveil if three GenAI image tools—Midjourney 5.2, DreamStudio beta, and Adobe Firefly 2—meet future designers’ expectations. Do these tools have good Usability, show sufficient User Experience (UX), induce positive emotions, and provide satisfactory results? A literature review was performed, and a quantitative empirical study based on a multidimensional analysis was executed to answer the research questions. Sixty users used the GenAI image tools and then responded to a holistic evaluation framework. The results showed that while the GenAI image tools received favorable ratings for Usability, they fell short in achieving high scores, indicating room for improvement. None of the platforms received a positive evaluation in all UX scales, highlighting areas for enhancement. The benchmark comparison revealed that all platforms, except for Adobe Firefly’s Efficiency scale, require enhancements in pragmatic and hedonic qualities. Despite inducing neutral to above-average positive emotions and minimal negative emotions, the overall satisfaction was moderate, with Midjourney aligning more closely with user expectations. This study emphasizes the need for significant improvements in Usability, positive emotional resonance, and result satisfaction, even more so in UX, so that GenAI image tools can meet future designers’ expectations.

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Section: Literature Reviewmentioning

confidence: 99%

Generative Artificial Intelligence Image Tools among Future Designers: A Usability, User Experience, and Emotional Analysis

Casteleiro-Pitrez

2024

Digital

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“…The one major caveat to this conclusion is that, as we are now at the dawn of useful AI-powered coding tools [245], this usage may shift as programmers modify their languages and visualization systems [322] to accommodate a new occupant. Should specification of computational intent no longer be bound to our ability to manipulate text, the necessity of a given representation may fade-which would likely end the cycle of serialization-housed DSL reemergence.…”

Section: Are Json-based Dsls the Future?mentioning

confidence: 99%

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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Domain-specific languages represented in data serialization formats (such as Javascript Object Notation or JSON) are an increasingly common means to control numerous systems.These range from database queries to application configuration, narrative generation, Twitter bots, data visualization, and many other areas.These languages allow potentially unsophisticated human users to concisely specify their intent through logic and notation that is relevant to task domain.Further, they provide a means for computational agents to easily manipulate that form, allowing for powerful recommendation engines and systems of automated analyses.In this thesis, we consider how end-user agency might be enhanced and maintained through the design of tools that support these domain-specific languages, as well as through the study of the design of the languages themselves.In support of this goal, we conducted four interconnected projects which variously study how JSON-based DSLs are designed, how abstraction can be integrated into those languages, how interfaces can be designed to specifically facilitate their manipulation, as well as how those programs might be automatically validated.Through these projects, we demonstrate that giving primacy to these textual interfaces as design elements can be valuable for end users.We find that this style of interventions are useful for helping end users learn, use, and re-use programs written in these languages.We primarily consider languages focused on data visualization tasks, as there has been substantial work in the visualization research community on this form of interface—although the lessons learned could be applied to any relevant domain.

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Anonymizing eye-tracking stimuli with stable diffusion

Kurzhals

2024

Computers & Graphics

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Doom or Deliciousness: Challenges and Opportunities for Visualization in the Age of Generative Models

Abstract: Figure 1: Different types of data visualization (and the prompts used to create them) as imagined by text-to-image generative models. While these examples are delicious (in their graphical intrigue and exploration of style), they risk doom by potentially creating misplaced trust.

Cited by 18 publications

References 71 publications

Generative Artificial Intelligence Image Tools among Future Designers: A Usability, User Experience, and Emotional Analysis

Generative Artificial Intelligence Image Tools among Future Designers: A Usability, User Experience, and Emotional Analysis

Understanding and Enhancing JSON-based DSL Interfaces for Visualization

Anonymizing eye-tracking stimuli with stable diffusion

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