What Predicts AI Usage? Investigating the Main Drivers of AI Use Intention over Different Contexts psyarxiv.com Artificial Intelligence (AI) based applications are an ever-expanding field, with an increasing number of sectors deploying this technology. While previous research has focused on … Continued
Study preregistration has become increasingly popular in psychology, but its effectiveness in restricting potentially biasing researcher degrees of freedom remains unclear. We used an extensive protocol to assess the strictness of preregistrations and the consistency between preregistration and publications of … Continued
Due to technological advancements such as text-to-speech software, reading while listening (audio-assisted reading) is widely available. However, the findings are mixed on the effectiveness of reading while listening as a tool to improve comprehension. The purpose of this study is … Continued
Technological advances in the context of digital transformation are the basis for rapid developments in the field of artificial intelligence (AI). Although AI is not a new topic in computer science (CS), recent developments are having an immense impact on … Continued
The causal capabilities of large language models (LLMs) is a matter of significant debate, with critical implications for the use of LLMs in societally impactful domains such as medicine, science, law, and policy. We further our understanding of LLMs and … Continued
The rationale of this work is based on the current user trust discourse of Artificial Intelligence (AI). We aim to produce novel HCI approaches that use trust as a facilitator for the uptake (or appropriation) of current technologies. We propose … Continued
The rapid development of AI-mediated communication technologies (AICTs), which are digital tools that use AI to augment interpersonal messages, has raised concerns about the future of interpersonal trust and prompted discussions about disclosure and uptake. This paper contributes to this … Continued
Abstract: Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system’s entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both from a technical … Continued
AI and ML models have already found many applications in critical domains, such as healthcare and criminal justice. However, fully automating such high-stakes applications can raise ethical or fairness concerns. Instead, in such cases, humans should be assisted by automated … Continued
The disruptive potential of AI systems roots in the emergence of big data. Yet, a significant portion is scattered and locked in data silos, leaving its potential untapped. Federated Machine Learning is a novel AI paradigm enabling the creation of … Continued