Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection

Fuente: arXiv
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Main Authors: Jung, Ji-Youn, Saxena, Devansh, Park, Minjung, Kim, Jini, Forlizzi, Jodi, Holstein, Kenneth, Zimmerman, John
Format: Preprint
Published: 2025
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_version_ 1866911018521722880
author Jung, Ji-Youn
Saxena, Devansh
Park, Minjung
Kim, Jini
Forlizzi, Jodi
Holstein, Kenneth
Zimmerman, John
author_facet Jung, Ji-Youn
Saxena, Devansh
Park, Minjung
Kim, Jini
Forlizzi, Jodi
Holstein, Kenneth
Zimmerman, John
contents AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with industry practitioners -- we explored methods for evaluating risks and benefits using multidisciplinary collaboration. Participants demonstrated strong receptivity to addressing RAI concerns early in the process and effectively identified low-risk, high-benefit AI concepts. Our findings highlight the potential of a design-led approach to embed ethical and service design thinking at the front end of AI innovation. By examining how practitioners reason about AI concepts, our study invites HCI and RAI communities to see early-stage innovation as a critical space for engaging ethical and commercial considerations together.
format Preprint
id arxiv_https___arxiv_org_abs_2506_17494
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Jung, Ji-Youn
Saxena, Devansh
Park, Minjung
Kim, Jini
Forlizzi, Jodi
Holstein, Kenneth
Zimmerman, John
Human-Computer Interaction
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with industry practitioners -- we explored methods for evaluating risks and benefits using multidisciplinary collaboration. Participants demonstrated strong receptivity to addressing RAI concerns early in the process and effectively identified low-risk, high-benefit AI concepts. Our findings highlight the potential of a design-led approach to embed ethical and service design thinking at the front end of AI innovation. By examining how practitioners reason about AI concepts, our study invites HCI and RAI communities to see early-stage innovation as a critical space for engaging ethical and commercial considerations together.
title Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
topic Human-Computer Interaction
url https://arxiv.org/abs/2506.17494