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human-computer interaction

2,089 papers

#human-computer interacti... Preprint Sep 2026

Vulnerabilities in Personalization: Assessing Health Privacy Risks in ChatGPT Logs and Memory

A large-scale computational audit analyzing 179,057 conversations across India, Nigeria, Brazil, and Pakistan is presented to evaluate personal health disclosures and background memory synthesis in ChatGPT and concludes with sociotechnical design guidelines to restore user agency and consent-driven boundaries in statef...

S. M. Mehedi Zaman, Meeraz Hoque · 0 citations
#human-computer interacti... Preprint Sep 2026

The Arc of Artificial Romance: How Emerging Adults Experience Romantic Relationships with AI Companions

It was found that relationships with AI companions improved participants'sjective wellbeing, reduced symptoms of mental health disorders, and taught them new social skills, giving them the confidence to wait for someone who would treat them well.

Yixin Chen, Alexis Hiniker · 0 citations
#human-computer interacti... Preprint Sep 2026

Bring Buttons Back: Physical Interfaces for the Age of Automation

Physically Stateful Interfaces is introduced, a design concept that re-imagines traditional controls, such as buttons, switches, and knobs, as actuated, bidirectional interface elements that unify affordance, feedforward, and feedback into a single interaction point.

D. Goedicke, Donald Degraen, T. Igoe et al. · 0 citations

Understanding the Design Taxonomy of AI-Mediated Interpersonal Communication Experiences in HCI: A Scoping Analysis

A scoping analysis is conducted by performing an in-depth review of prior HCI literature published over the past decade by examining the types of AIMIC studied, AI integration approaches and human-AI interaction design, reported outcomes and benefits, and key challenges and future research opportunities.

Chen Chen, Ling-Yao Li, Ren-Kai Ma et al. · 0 citations
#human-computer interacti... Preprint Sep 2026

Show Me Your Prompts! How Writers Feel About Sharing Prompts in Collaborative Text Editors

This work shows that collaborative text editors should share more information among writers on when, how, and where AI is used, and suggests a strong preference for techniques that share more information about prompting activities for increased awareness.

Nikhita Joshi, Yen-Ting Yeh · 0 citations
#human-computer interacti... Preprint Sep 2026

ggaction: A Grammar of Graphical Actions

Through a series of evaluations, it is shown that ggaction is sufficiently expressive to capture common chart authoring intents and outperforms widely used visualization grammars, including Vega-Lite and ggplot2, in both human and machine interpretability.

Hyeon Jeon, Jinwook Seo · 0 citations
#human-computer interacti... Preprint Sep 2026

AnnoSketch: Evaluating and Collecting Human Sketches for MLLM-assisted Chart Annotation

This study examines when sketch input is useful for MLLM-generated chart annotations across variation in chart type and caption type, and presents AnnoSketch, a database of annotation sketches collected across 160 chart-caption pairs from the conditions in which sketch guidance proved most beneficial.

Yoon-Gu Oh, Seon Gyeom Kim, J. Choi et al. · 0 citations
#human-computer interacti... Preprint Open access Sep 2026

When Single-User-Oriented LLM-based Assistants Involve Others: A Scoping Review of Pathways, Risks, and Responses

LLM-based assistants are increasingly extending into multi-party contexts, while core operational processes for context management, personalization, identity attribution, authority attribution, and action execution often remain organized around a single user. Existing work examines particular multi-party settings, but...

Yulin Chen, Yang Zhan, Zhuoran Lu et al. · 0 citations

What Makes a Great Co-Worker in an AI-Native Workplace?

As knowledge work grows interdependent between humans and AI, we ask what makes a great co-worker in an AI-native workplace. To answer this, we conducted 22 interviews and a large-scale mixed-methods survey of 1,534 knowledge workers at a multinational technology company. We contribute BACI, a framework of 75 co-worker...

Rudrajit Choudhuri, M. Meijer, S. Lee et al. · 0 citations
#artificial intelligence Book Open access Sep 2026

"What Can I Do for You": How Should AI Companions Provide Assistance to Players in Virtual Reality Games

A VR puzzle game for Apple Vision Pro featuring an AI companion across four gameplay modes showed that AI assistance significantly reduced players’ workload, but autonomous agent play substantially diminished player experience by reducing challenge, autonomy, immersion, and enjoyment.

Tai-Yu Zhang, Xin-Nian Zhao, Adalberto L. Simeone · 0 citations

From tech blogs

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Microsoft Research Blog Nov 5, 2026

Formally verifying agent-written full-stack web apps with PDD Kit

AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

MIT News · Artificial Intelligence Oct 23, 2026

Reinforcing the value of human understanding at MIT

During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”

MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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