Accepted Submissions

Papers & Disclosures

Nine position papers and one AI disclosure statement, presented at CHIWork 2026 on June 22 in Linz.

Track 1

Position Papers

Nine accepted position papers, each presented as a one-slide lightning talk at the workshop. Camera-ready PDFs are posted to arXiv as authors complete them; links appear below as they go up. Questions for authors live on the workshop Slack thread.

Visible Adoption, Untracked Contribution: GitHub Evidence of the Accountability Gap Across Three Cohorts of an HCI Prototyping Course

Maria Teresa Parreira, Pranav Prabhat Sinha, Hauke Sandhaus, Wendy Ju — Cornell University

arXiv:2606.14054 · presented by Pranav Prabhat Sinha
Designed by Journalists, but Is It for Readers? Rethinking AI Disclosures and Transparency in News

Pooja Prajod — CWI Amsterdam, Netherlands

arXiv:2606.11116
Steps toward Pluralistic AI

Michael Muller (Independent Researcher), Aminat Adebiye (IBM Research), Katelyn Morrison (Microsoft)

arXiv link coming
Verification as Psychological Necessity: Reframing GenAI Accountability Through Basic Psychological Needs

Prasil Adhikari — Johannes Kepler University · Pro2Future GmbH (Linz / Graz, Austria)

arXiv link coming
From Producing to Validating: How AI Is Deskilling Freelancers

Nakul Rajpal — Northeastern University

arXiv link coming
Adversarial Co-Thinking: Calibration and Triangulation Across Multiple GenAI Tools in HCI Writing

Pia Tukkinen — Aalto University

arXiv link coming
From Human-Centered Design to Human-AI Collaboration: Why the Future of HCI Still Starts With People

Issam Alzouby — UNC Charlotte

arXiv link coming
Generative AI as Support, Not Replacement, in Human-Centered Design

Amir Talakoob — UNC Charlotte

arXiv link coming
Human-Centered Design: The Disclosure of Generative AI for Emerging Professionals

Sydney Lee — UNC Charlotte

arXiv:2606.24136

Track 2

AI Disclosure Statement

One disclosure, presented in the opening framing of the workshop as a worked example of what an honest, reflexive AI use statement can look like.

AI Use Disclosure: Writing an LBW Paper with Claude Code

Hauke Sandhaus — Cornell Tech

A first-person account of writing a 6-page Late-Breaking Work paper with Claude Code, using a multi-agent strategy (parallel review-simulating agents, draft, optimization). Surfaces both AI catching real cross-file errors a human had missed, and AI fabricating an authoritative-sounding statistical claim (a Levene's test that was never run) — caught only by a human who knew the analysis well enough to be suspicious.

Disclosure notice on OSF

See also the website's own AI use statement — a second worked example documenting how this site was built with Claude Code under direction. Both are presented together in the workshop's opening framing.

After the workshop

What comes next

Following the workshop, we will invite interested participants to co-author a joint publication synthesizing collective strategies for accountable GenAI use in HCI practice. Workshop materials (the Code of Conduct draft, group syntheses, the casebook) will be posted here under CC BY shortly after the event.