Answering end user security questions is challenging. While large language models (LLMs) like GPT, LLAMA, and Gemini are far from error-free, they have shown promise in answering a variety of questions outside of security. We studied LLM performance in the area of end user security by qualitatively evaluating 3 popular LLMs on 900 systematically collected end user security questions. While LLMs demonstrate broad generalist ``knowledge'' of end user security information, there are patterns of errors and limitations across LLMs consisting of stale and inaccurate answers, and indirect or unresponsive communication styles, all of which impacts the quality of information received. Based on these patterns, we suggest directions for model improvement and recommend user strategies for interacting with LLMs when seeking assistance with security.
This article explores the potential of large language models (LLMs) to shift computing away from application-centric models towards a more dynamic, relational, and human-centered paradigm. It argues that LLMs can unlock the computer's full capabilities by mediating human intent and enabling a conversational style of interaction.
Daniel M. Russell's talk will review the successes and failures of past UX research approaches, drawing on decades of experience at the intersection of human experience and intelligent systems, to explore how AI will shape future knowledge practices.
This paper explores 'TeleAbsence,' a concept extending telepresence to address emotional distance from lost loved ones through poetic encounters with their digital and physical traces, inspired by the Portuguese concept of 'Saudade.' It outlines five design principles – presence of absence, illusory communication, materiality of memory, traces of reflection, and remote time – and explores applications using mediums like poetry, phone, piano, and pen.
Proceedings from the Thirty-Ninth AAAI Conference on Artificial Intelligence, including papers from AAAI-25, IAAI-25, and EAAI-25. The conference covered topics like machine learning, natural language processing, game theory, and human-AI interaction, with a focus on bridging different areas of AI and related disciplines.
Elizabeth Churchill, a professor at Mohamed bin Zayed University of Artificial Intelligence, emphasizes human-centered design in AI to ensure technology serves people's needs positively. Her career and research focus on understanding the interaction between people and technology, aiming to design tools and experiences that enhance human potential.
An interdisciplinary research project exploring the history and ideas behind the influential ELIZA chatbot, created in the 1960s. The project aims to contextualize ELIZA, analyze its code, and examine its cultural impact on human-computer interaction.
This issue of ACM Interactions explores the crucial role of User Experience (UX) in ensuring responsible AI (RAI) design and use. Articles discuss the importance of UX in shaping meaningful and trustworthy AI systems, the potential of 'reuser experience' for sustainable design practices, and emerging trends in AI interaction design.
