arXiv:2606. 14306v1 Announce Type: cross Abstract: Current Generative AI (GenAI) interfaces remain largely constrained to chatbox interaction, which can impose high cognitive demands on users and create substantial barriers for people with intellectual disabilities (ID), including prompt formulation difficulties, response overload, and limited mechanisms to assess information reliability.
By Virginia Francisco, Daniel Guasch, Raquel Herv\'as
The ideation phase of participatory AI risk assessment often starts with a blank slate or a limited list of predefined risks, making it difficult to surface indirect or systemic harms. To address this...
The paper introduces AI4CDS, a five‑phase framework that guides how AI can participate in computational design science while keeping researchers responsible for domain grounding, verification, and scientific judgment. It emphasizes principles such as graduated trust, reversibility, auditability, and differentiated reproducibility. The authors demonstrate the framework with ChildRiskGuard, an interpretable system that detects child‑inappropriate short‑form videos, achieving an F1 score of 0.769 and outperforming generic content‑safety models.
By Wenli Zhang, Jiaheng Xie, Zhihe Pan, Yidong Chai, Xiao Fang, Sudha Ram
PersonaTeaming introduces a workflow that incorporates personas into adversarial prompt generation for generative AI, achieving higher attack success rates than the state‑of‑the‑art RainbowPlus while preserving prompt diversity. The system is extended into a user‑facing playground that lets red‑teamers create their own personas and collaborate with AI to refine prompts, fostering diverse strategies. A user study with 11 industry practitioners found the playground produced useful outputs and encouraged out‑of‑the‑box thinking, even when suggestions were not strictly followed.
By Wesley Hanwen Deng, Mingxi Yan, Sunnie S. Y. Kim, Akshita Jha, Lauren Wilcox, Kenneth Holstein, Motahhare Eslami, Leon A. Gatys
arXiv:2609.24859v1 Announce Type: cross
Abstract: The ideation phase of participatory AI risk assessment often starts with a blank slate or a limited list of predefined risks, making it difficult to...
By Ke Zhou, Edyta Bogucka, Daniele Quercia
arXiv:2606. 11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research.
By Zhiqing Wang, Steven Dow
arXiv:2410. 22526v2 Announce Type: replace Abstract: To effectively address potential harms from Artificial Intelligence (AI) systems, it is essential to identify and mitigate system-level hazards.
By Shalaleh Rismani, Roel Dobbe, AJung Moon
arXiv:2607. 28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI into system administration may involve deeper shifts in professional practice that are not yet fully understood.
By Rana Abou Khamis, Hala Assal, Ashraf Matrawy
arXiv:2606. 13196v2 Announce Type: replace Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
arXiv:2608. 07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks.
By Afreen Alam, Evgenija Popchanovska, Ana Gjorgjevikj, Maryan Rizinski, Lubomir T. Chitkushev, Irena Vodenska, Dimitar Trajanov
arXiv:2607. 23126v2 Announce Type: replace-cross Abstract: The rapid adoption of generative AI tools has created new literacy demands for designers who must verbalize tacit knowledge through natural language prompts.
By Daisaku Sato
arXiv:2606. 13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng