Mark Zachry

Pitch Sinlapanuntakul, Soyun Moon, Yuri Kawada et al.

Early-stage concept envisioning is a critical juncture in AI design, shaping how designers frame problems and the decisions that follow. Yet values and potential harms are often too abstract or addressed too late to meaningfully shape design. Using a Research-through-Design (RtD) approach, we developed the AI Concept Envisioning Toolkit, comprising an AI Capability Library, 24 Value--Harm Cards, and a Value--Tension Map, to support reasoning by juxtaposing values and harms within AI technical capabilities. Through a survey with 30 designers and in-depth interviews with 12 designers, we find that the toolkit is clear and perceived as valuable, and that it encourages value reflection, helps anticipate potential harms, and makes ethical considerations more transparent in early-stage design. We reflect on our design process and discuss design approaches for tools that promote reflection on values and potential harms, surface and navigate value tensions, and introduce productive friction throughout design workflows.

Pitch Sinlapanuntakul, Aayushi Dangol, Xiaoyi Xue et al.

As AI integrates into design practice, designers increasingly use generative AI tools to envision AI-enabled solutions, positioning AI as both design tool and design material. This dual role creates recursive value tensions distinct from traditional design work. We engaged 18 designers in a concept envisioning activity and interviews to understand how they navigate values and recognize potential harms in this context. Our analysis reveals that (i) designers engage in reciprocal reflection-in-action with AI; (ii) this process surfaces multi-level value tensions across tool, designer, and concept; (iii) designers demonstrate greater attunement to harm recognition as a primary design signal than to articulating positive value fulfillment; and (iv) designers exercise anticipatory judgment through meta-design reasoning about how tool assumptions risk propagating into designed concepts and future use contexts. We extend Schon's reflection-in-action framework and discuss implications for redesigning AI-mediated design tools, supporting harm-centered reasoning, and positioning design as foundational to AI development.

Julie A. Vera, Mark Zachry, David W. McDonald

This paper examines collaborative sensemaking during severe weather events through the emerging phenomenon of "weatherfluencers" or content creators who livestream meteorological interpretation on platforms like YouTube. Drawing from sensemaking theory, crisis informatics, and platform studies, we analyze how these creators navigate the sociotechnical dynamics of interpreting severe weather in real time with distributed audiences. Through critical incident analysis of 13 Particularly Dangerous Situation (PDS) storm warnings across three prominent weatherfluencers, we identify three key practices: multi-source information triangulation, temporal bridging techniques, and platform-specific adaptations that transform entertainment interfaces into safety-critical communication channels. Our analysis shows how these practices challenge existing models of crisis communication by integrating distributed expertise, collapsing temporal frames, and reconfiguring platform affordances. This research contributes to understanding how informal emergency communicators mediate between institutional alerting systems and public needs, and how visual, multimodal crisis communication differs from text-centered approaches.