skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Creating Design Resources to Scaffold the Ideation of AI Concepts
Advances in artificial intelligence have enabled unprecedented technical capabilities, yet making these advances useful in the real world remains challenging. We engaged in a Research through Design process to improve the ideation of AI products and services. We developed a design resource capturing AI capabilities based on 40 AI features commonly used across various domains. To probe its usefulness, we created a set of slides illustrating AI capabilities and asked designers to ideate AI-enabled user experiences. We also incorporated capabilities into our own design process to brainstorm concepts with domain experts and data scientists. Our research revealed that designers should focus on innovations where moderate AI performance creates value. We reflect on our process and discuss research implications for creating and assessing resources to systematically explore AI’s problem-solution space.  more » « less
Award ID(s):
2007501
PAR ID:
10447189
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
DIS '23: Proceedings of the 2023 ACM Designing Interactive Systems Conference
Page Range / eLocation ID:
2326 to 2346
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, ACM)
    Mueller, Florian Floyd; Kyburz, Penny; Williamson, Julie R; Sas, Corina; Wilson, Max L; Dugas, Phoebe Toups; Shklovski, Irina (Ed.)
    Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovations users do not want, while domain experts think of innovations that cannot be built. A lack of effective ideation seems to be a breakdown point. How might multidisciplinary teams identify buildable and desirable use cases? This paper presents a first hand account of ideating AI concepts to improve critical care medicine. As a team of data scientists, clinicians, and HCI researchers, we conducted a series of design workshops to explore more effective approaches to AI concept ideation and problem formulation. We detail our process, the challenges we encountered, and practices and artifacts that proved effective. We discuss the research implications for improved collaboration and stakeholder engagement, and discuss the role HCI might play in reducing the high failure rate experienced in AI innovation. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, CHI '22: CHI Conference on Human Factors in Computing Systems)
    HCI research has explored AI as a design material, suggesting that designers can envision AI’s design opportunities to improve UX. Recent research claimed that enterprise applications offer an opportunity for AI innovation at the user experience level. We conducted design workshops to explore the practices of experienced designers who work on cross-functional AI teams in the enterprise. We discussed how designers successfully work with and struggle with AI. Our findings revealed that designers can innovate at the system and service levels. We also discovered that making a case for an AI feature’s return on investment is a barrier for designers when they propose AI concepts and ideas. Our discussions produced novel insights on designers’ role on AI teams, and the boundary objects they used for collaborating with data scientists. We discuss the implications of these findings as opportunities for future research aiming to empower designers in working with data and AI. 
    more » « less
  3. ; ; (, ACM)
    We ideate a future design workflow that involves AI technology. Drawing from activity and communication theory, we attempt to isolate the new value that large AI models can provide design compared to past technologies. We arrive at three affordances—dynamic grounding, constructive negotiation, and sustainable motivation—that summarize latent qualities of natural language-enabled foundation models that, if explicitly designed for, can support the process of design. Through design fiction, we then imagine a future interface as a diegetic prototype, the story of Squirrel Game, that demonstrates each of our three affordances in a realistic usage scenario. Our design process, terminology, and diagrams aim to contribute to future discussions about the relative affordances of AI technology with regard to collaborating with human designers. 
    more » « less
  4. ; ; (, Design Studies)
    Throughout the design process, designers encounter diverse stimuli that influence their work. This influence is particularly notable during idea generation processes that are augmented by novel design support tools that assist in inspiration discovery. However, fundamental questions remain regarding why and how interactions afforded by these tools impact design behaviors. This work explores how designers search for inspirational stimuli using an AI-enabled multi-modal search platform, which supports queries by text and non-text-based inputs. Student and professional designers completed a think-aloud design exploration task using this platform to search for stimuli to inspire idea generation. We identify expertise and search modality as factors influencing design exploration, including the frequency and framing of searches, and the evaluation and utility of search results. 
    more » « less
  5. ; ; ; (, Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference)
    null (Ed.)
    Abstract Additive manufacturing (AM) processes present designers with unique capabilities while imposing several process limitations. Designers must leverage the capabilities of AM — through opportunistic design for AM (DfAM) — and accommodate AM limitations — through restrictive DfAM — to successfully employ AM in engineering design. These opportunistic and restrictive DfAM techniques starkly contrast the traditional, limitation-based design for manufacturing techniques — the current standard for design for manufacturing (DfM). Therefore, designers must transition from a restrictive DfM mindset towards a ‘dual’ design mindset — using opportunistic and restrictive DfAM concepts. Designers’ prior experience, especially with a partial set of DfM and DfAM techniques could inhibit their ability to transition towards a dual DfAM approach. On the other hand, experienced designers’ auxiliary skills (e.g., with computer-aided design) could help them successfully use DfAM in their solutions. Researchers have investigated the influence of prior experience on designers’ use of DfAM tools in design; however, a majority of this work focuses on early-stage ideation. Little research has studied the influence of prior experience on designers’ DfAM use in the later design stages, especially in formal DfAM educational interventions, and we aim to explore this research gap. From our results, we see that experienced designers report higher baseline self-efficacy with restrictive DfAM but not with opportunistic DfAM. We also see that experienced designers demonstrate a greater use of certain DfAM concepts (e.g., part and assembly complexity) in their designs. These findings suggest that introducing designers to opportunistic DfAM early could help develop a dual design mindset; however, having more engineering experience might be necessary for them to implement this knowledge into their designs. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email