PopBlends: Strategies for Conceptual Blending with Large Language Models

Wang, Sitong; Petridis, Savvas; Kwon, Taeahn; Ma, Xiaojuan; Chilton, Lydia B.

doi:10.1145/3544548.3580948

Cited by 22 publications

(7 citation statements)

References 54 publications

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“…While there is limited scholarly work specifically applying generative AI in the context of entrepreneurship, there is a rapidly growing body of tangentially-related scholarship which may be applicable for local entrepreneurs, such as using generative AI to increase productivity [62] and improved creative outcomes with ideation support [32], such as personalized brand material [92]. Alongside these empirical results, there are hundreds of accounts and videos of self-proclaimed entrepreneurs and influencers providing advice online for how to use AI for your business, often providing demos of ChatGPT [82], DALL-E 2 [97], Canva's Text-to-Image feature [96], Vidyo.ai [89].…”

Section: Prompt Engineeringmentioning

confidence: 99%

Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurs

Kotturi,

Anderson,

Ford

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Generative AI platforms and features are permeating many aspects of work. Entrepreneurs from lean economies in particular are well positioned to outsource tasks to generative AI given limited resources. In this paper, we work to address a growing disparity in use of these technologies by building on a four-year partnership with a local entrepreneurial hub dedicated to equity in tech and entrepreneurship. Together, we co-designed an interactive workshops series aimed to onboard local entrepreneurs to generative AI platforms. Alongside four community-driven and iterative workshops with entrepreneurs across five months, we conducted interviews with 15 local entrepreneurs and community providers. We detail the importance of communal and supportive exposure to generative AI tools for local entrepreneurs, scaffolding actionable use (and supporting non-use), demystifying generative AI technologies by emphasizing entrepreneurial power, while simultaneously deconstructing the veneer of simplicity to address the many operational skills needed for successful application. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; Empirical studies in HCI.

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Section: Prompt Engineeringmentioning

confidence: 99%

Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurs

Kotturi,

Anderson,

Ford

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…Prompt-based LLMs are increasingly used in the CHI community [20,56,76,110], primarily contributing to the development of applications like chatbots [46] and tools for co-writing [56], virtual simulations [108], story-telling [23], and visualization enhancement [96]. Such studies have primarily focused on using LLMs as production tools [56] rather than tools for analysis.…”

Section: Harnessing Large Language Models In Computational Social Sci...mentioning

confidence: 99%

Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language

Ding,

Carik,

Gunturi

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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We introduce a multi-step reasoning framework using promptbased LLMs to examine the relationship between social media language patterns and trends in national health outcomes. Grounded in fuzzy-trace theory, which emphasizes the importance of "gists" of causal coherence in effective health communication, we introduce Role-Based Incremental Coaching (RBIC), a prompt-based LLM framework, to identify gists at-scale. Using RBIC, we systematically extract gists from subreddit discussions opposing COVID-19 health measures (Study 1). We then track how these gists evolve across Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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“…For instance, Matejka et al proposed DreamLens, an interactive system for exploring and visualizing large-scale generative design datasets [43]. The most related generative design work to us includes those using AI models to support user's design [11,17,31,37,38,64,73]. Evirgen et al proposed GANzilla, a tool that allows users to discover image manipulation directions in Generative Adversarial Networks (GANs) [16].…”

Section: Interactive Support For Generative Designmentioning

confidence: 99%

PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinement

Wang,

Huang,

Song

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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PopBlends: Strategies for Conceptual Blending with Large Language Models

Cited by 22 publications

References 54 publications

Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurs

Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurs

Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language

PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinement

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