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#artificial intelligence Preprint Oct 2026

Designing the Future of User Feedback for Generative AI

Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and features. When implemented effectively, giving such feedback can increase users'engagement with and trust in GenAI systems. Government regulations and industry guidelines call...

A. Frik, Julia Bernd, Amitis Karami et al. · 0 citations
#human-computer interacti... Preprint Oct 2026

A Scale For Value Alignment In Human-AI Interaction

Value alignment is a central objective in AI and HCI research, yet no validated instrument measures how users perceive it. This gap hampers the comparison and accumulation of findings and limits the effectiveness of applications, where understanding users'viewpoints is critical. We construct and evaluate a 13-item psyc...

L. Hegemann, Steeven Villa, Hyemin Bang et al. · 0 citations
Open access Sep 2026

GOPAY USER EXPERIENCE: A BENCHMARK-BASED EVALUATION USING THE USER EXPERIENCE QUESTIONNAIRE

The growing adoption of digital wallets underscores the importance of systematically evaluating perceived user experience. This study assesses GoPay using the standardized User Experience Questionnaire (UEQ) benchmark framework to identify strengths and priorities for improvement across pragmatic and hedonic dimensions...

Florentina Yuni Arini, Muhammad Ramzy Basysyar, Lafifa Linta Qisisin Andayani et al. · 0 citations
Open access Sep 2026

PERANCANGAN UI/UX APLIKASI MOBILE KEDAI KOPI CEI BERBASIS DESIGN THINKING

This study presents the design of a mobile user interface and user experience (UI/UX) for Kedai Kopi Cei, a modern coffee shop, using the Design Thinking approach. The research addresses five key pain points identified during the Empathize stage: inefficient manual ordering, limited real-time menu and promotion informa...

Fierren Al - Hilal Saepul Bahri, Naufal Afaf Ekayana · 0 citations
Aug 2026

When AI service appearance backfires: form-based expectations and trust fragility

This research aims to explore why high-fidelity digital human avatars induce a stronger adverse response from customers than an artificial static robot interface condition following a service failure. A total of three studies were performed. Studies 1 and 2 (n = 322, n = 282) involved a between-subjects desi...

Abhinav Verma, Harshika Gabbad · 0 citations

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