We contrast three perspectives on engagement from three projects on the design of Digital Behavior Change Interventions (DBCIs), all conducted as part of the PhD thesis of the second author. We provide a reflection on this work with respect to engagement, discussing the motivation, the assumed effects of engagement, the measures of engagements and key insights of each project, as the well as the strategies employed to increase engagement.
As spatial computing and multimodal LLMs mature, AR is tending to become an intuitive "thinking tool," embedding semantic and context-aware intelligence directly into everyday environments. This paper explores how always-on AR can seamlessly bridge digital cognition and physical affordances, enabling proactive, context-sensitive interactions that enhance human task performance and understanding.
Mendelian randomization (MR) is an epidemiological framework using genetic variants as instrumental variables (IVs) to examine the causal effect of exposures on outcomes. Statistical methods based on unidirectional MR (UMR) are widely used to estimate the causal effects of exposures on outcomes in observational studies. To estimate the bidirectional causal effects between two phenotypes, investigators have naively applied UMR methods separately in each direction. However, bidirectional causal effects between two phenotypes create a feedback loop that biases the estimation when UMR methods are naively applied. To overcome this limitation, we proposed two novel approaches to estimate bidirectional causal effects using MR: BiRatio and BiLIML, which are extensions of the standard ratio, and limited information maximum likelihood (LIML) methods, respectively. We compared the performance of the two proposed methods with the naive application of UMR methods through extensive simulations of several scenarios involving varying numbers of strong and weak IVs. Our simulation results showed that when multiple strong IVs are used, the proposed methods provided accurate bidirectional causal effect estimation in terms of median absolute bias and relative median absolute bias. Furthermore, compared to the BiRatio method, the BiLIML method provided a more accurate estimation of causal effects when weak IVs were used. Therefore, based on our simulations, we concluded that the BiLIML should be used for bidirectional causal effect estimation. We applied the proposed methods to investigate the potential bidirectional relationship between obesity and diabetes using the data from the Multi-Ethnic Study of Atherosclerosis cohort. We used body mass index (BMI) and fasting glucose (FG) as measures of obesity and type 2 diabetes, respectively. Our results from the BiLIML method revealed the bidirectional causal relationship between BMI and FG in across all racial populations. Specifically, in the White/Caucasian population, a 1 kg/m2 increase in BMI increased FG by 0.70 mg/dL (95% confidence interval [CI]: 0.3517–1.0489; p = 8.43×10−5), and 1 mg/dL increase in FG increased BMI by 0.10 kg/m2 (95% CI: 0.0441–0.1640; p = 6.79×10−4). Our study provides novel findings and quantifies the effect sizes of the bidirectional causal relationship between BMI and FG. However, further studies are needed to understand the biological and functional mechanisms underlying the bidirectional pathway.
We propose to review the main stages in the computer history of virtual actors, with a view to the exploration of virtual reality and discussion on different approaches to human simulation. The notion of autonomy emerges as a key issue for the virtual entities. We then explore one way of building elements of autonomy and conclude with an example of avatar stage direction leading to a simulacrum of autonomy in a live performance.
Using some results coming from human and social sciences, we are working on the still important problem of tailorability inside CSCW systems. Our proposition aims at favouring the dynamic integration of groupware systems in a global and integrated environment that creates a context for their use. This work leads us to define the problem of the inter-activities management. This study helps us to propose a technical solution to this problem and that is realized in the CooLDA platform.
The development of a desktop Braille printing machine aims to create an affordable, user-friendly device for visually impaired users. This document outlines the entire process, from research and requirement analysis to distribution and support, leveraging the content and guidelines from the GitHub repository,https://github.com/fablabnepal1/Desktop-Braille-Printing-Machine.
What if a clock could do more than tell time - what if it could look around? This project explores the conceptualization, design, and construction of a timepiece with visual perception capabilities, featuring three types of human-time interactions. Informal observations during a demonstration highlight its unique user experiences. https://www.zhuoyuelyu.com/clook
An explainable AI (XAI) model aims to provide transparency (in the form of justification, explanation, etc) for its predictions or actions made by it. Recently, there has been a lot of focus on building XAI models, especially to provide explanations for understanding and interpreting the predictions made by deep learning models. At UCLA, we propose a generic framework to interact with an XAI model in natural language.
This paper describes an innovative solution that enables the enterprises to bring their associates (or employees) back to physical workspaces for critical operations in a safe manner in the wake of current COVID-19 pandemic.
Designing human-centered AI-driven applications require deep understandings of how people develop mental models of AI. Currently, we have little knowledge of this process and limited tools to study it. This paper presents the position that AI-based games, particularly the player-AI interaction component, offer an ideal domain to study the process in which mental models evolve. We present a case study to illustrate the benefits of our approach for explainable AI.
Nicola Orio, Norbert Schnell, Marcelo M. Wanderley
This paper reviews the existing literature on input device evaluation and design in human-computer interaction (HCI) and discusses possible applications of this knowledge to the design and evaluation of new interfaces for musical expression. Specifically, a set of musical tasks is suggested to allow the evaluation of different existing controllers.
This paper describes a series of projects that explore the possibilities of musical expression through the combination of pre-composed, interlocking, modular components. In particular, this paper presents a modular soundtrack recently composed by the author for "Currents of Creativity," a permanent interactive video wall installation at the Pope John Paul II Cultural Center which is slated to open Easter 2001 in Washington, DC.
Chatbots are emerging as a promising platform for accessing and delivering healthcare services. The evidence is in the growing number of publicly available chatbots aiming at taking an active role in the provision of prevention, diagnosis, and treatment services. This article takes a closer look at how these emerging chatbots address design aspects relevant to healthcare service provision, emphasizing the Human-AI interaction aspects and the transparency in AI automation and decision making.
In this article, we are going to review a brief history of the field of Virtual Reality (VR), VR systems, and applications and discuss how they evolved. After that, we will familiarize ourselves with the essential components of VR experiences and common VR terminology. Finally, we discuss the evolution of ubiquitous VR as a subfield of VR and its current trends.
In this extended abstract, we propose an intelligent system that can be used as a Personalized Virtual Teaching Assistant (PVTA) to improve the students learning experience both for online and on-site courses. We show the architecture of such system, which is composed of an instance of IBM Watson Assistant and a server, and present an initial implementation, consisting in a chatbot that can be questioned about the content and the organization of the RecSys course, an introductory course on recommender systems.