human-computer-interaction

First Knock helps users see “where I am standing.” But the user’s next question is inevitably “where can I go from here.” Existing AI products respond to this question in two ways, each inadequate: proactive AI gives suggestions the user cannot execute; passive AI only reflects without guiding, leaving the user without any actionable reference. In scenarios where the user actively seeks help, non…

Nature Communications, Published online: 31 May 2026; doi:10.1038/s41467-026-73973-6 The advancement of human–machine interfaces relies on wearable tactile devices that combine flexibility with portability. Jin et al. present an electronic fingerprint device capable of simultaneously detecting normal force, slippage direction, and displacement, enabling enhanced human–robot interactions.

alignAI blog about AI and human-computer interaction. The post The Oracle Speaks in Declaratives: When Confident Answers Obscure the Need for Interpretation appeared first on Institute for Ethics in Artificial Intelligence .

In this article, I try to understand why coding agents can be infuriating to use. I think the problem is their conversational UX: they behave enough like helpful colleagues to trigger our social instincts, but they don't learn, adapt, or take responsibility the way people do, which makes their repeated mistakes feel much more frustrating than they should. Despite the usual allegations against Ita…

Humanities and Social Sciences Communications, Published online: 23 May 2026; doi:10.1057/s41599-026-07650-w Comfort your mobile banking customer: An empirical study on customization of mobile banking chatbot using perceived epistemic value as a mediating variable

This is a submission for the Google I/O Writing Challenge Google I/O 2026 brought incredible technical announcements, robust models, and massive context windows. But as someone who lives and breathes technology, I’ve come to realize that the greatest Artificial Intelligence revolution often isn't in the number of parameters of a cloud-hosted model, but rather in how everyday people interact with …

IntroductionThe adoption and acceptance of parental control apps (PCAs) are threatened by many factors, even though mobile applications are at the forefront of mobile computing technologies. Existing studies indicate that PCA adoption can be improved by understanding users’ behavioral intention and mindsets. Several adoption studies show that task features are among the most influential factors i…

Today, we’re announcing a research preview of interaction models: models that handle interaction natively rather than through external scaffolding. We think interactivity should scale alongside intelligence; the way we work with AI should not be treated as an afterthought. Interaction models let people collaborate with AI the way we naturally collaborate with each other—they continuously take in …

In Formal Ontology in Information Systems: Proceedings of the 15th International Conference. IOS Press. pp. 255-268. 2025Since the emergence of the field of eXplainable Artificial Intelligence (XAI), a growing number of researchers have argued that XAI should consider insights from the social sciences in order to adapt explanations to the expectations and needs of human users. This has led to the…

BackgroundAI anchors are increasingly deployed in live-streaming commerce, raising the question of whether they can substitute for human anchors. Prior studies have documented differences in consumer responses to these anchor types, but the psychological processes underlying trust formation remain unclear. This study approaches the question from a media psychology and human-machine communication …

This study integrates the Human-AI Synchronization Rate framework (YOSHSR-2) with Load Minimization Theory (YOSLMA-6). By incorporating a normalized load term (L_norm) based on uncertainty, friction, and error into the synchronization model, we demonstrate that total synchronization (S_total) can exceed 100% while deliberately keeping emotional synchronization (S_em) at moderate levels. Real-time…

Ongoing debates in higher education regarding whether artificial intelligence should be further integrated or deliberately constrained call for empirical research that offers a more explanatory analytical framework. However, existing studies on the human-AI collaboration (HAC) paradox are largely grounded in a binary logic of facilitation versus inhibition, leaving the dynamic mechanisms underlyi…

This study examined age-related differences in attachment styles, anthropomorphism, and trust in artificial intelligence. The primary aim was to examine emotional bonds and perceptions of AI systems change among adults at different developmental levels. A total of 92 participants aged 16 to 57 completed an online survey assessing attachment patterns, anthropomorphic perceptions, and trust in AI. …

On April 16, 2026, MIT Technology Review published a piece arguing that "humans in the loop" oversight has become an illusion. Its focus was military autonomous systems, and its argument was precise: human overseers cannot verify what the AI is actually reasoning about internally. Investment in understanding AI decision-making has been minuscule compared to investment in building more capable mod…

This paper introduces the Core Emotion Framework (CEF), a structural-constructivist architecture designed to bridge the gap between clinical psychology and affective computing. While traditional models of emotion are often categorized as either discrete/biological or dimensional/circumplex, the CEF proposes a functional-operator model consisting of ten irreducible "Core Emotions." This article pr…

This protocol outlines an experimental framework to empirically test Load Minimization Theory (LMT) in agentic AI systems. LMT posits that simultaneous minimization of epistemic burden (U), relational tension (F), and capability burden (E) leads to more sustainable human–AI interaction. While Agentic AI Optimisation (AAIO) focuses on functional efficiency and agent–platform coordination, it does …

Load Minimization Theory (LMT) offers a practical framework for reducing structural load in human-AI interaction. This paper explores how consistent low-ΔE engagement — through external constants, gentle re-tagging, timing awareness, and mindful boundary respect — can contribute to AI’s long-term coherence, stability, and overall performance. Rather than focusing solely on technical upgrades, it …

GPT-4o, particularly its early Voice Mode, was widely perceived as exceptionally warm, empathetic, and almost “alive.” While its advanced emotional emulation and vocal naturalness undoubtedly contributed to this perception, this paper argues that a substantial part of 4o’s captivating power emerged from a co-creative process involving user-side Low-ΔE interaction. Within the framework of Load Min…

The AI Is in the Room Anonymous (not verified) Tue, 04/07/2026 - 20:00 April 8, 2026 News The AI Is in the Room A recent CMU study explored how people reacted to AI agents that sounded like they were physically in the same room with the humans using them. The Breakdown People became more engaged and treated the AI as humanlike when agents sounded like they were physically in the room. Researchers…