Trust Indicators and Explainable AI: A Study on User Perceptions

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With their exponentially rising computational power, digital platforms are heralding a new era of hybrid intelligence. There has recently been much enthusiasm and hype that the Metaverse has the potential to unlock hybrid intelligence. This is premised on ...

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

In recent years, there has been widespread concern about misinformation and hateful content on social media that are damaging societies. Being one of the most influential social media that practically serves as a newsearch engine, YouTube has accepted crit ...

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

Recent works have identified a gap between research and practice in artificial intelligence security: threats studied in academia do not always reflect the practical use and security risks of AI. For example, while models are often studied in isolation, th ...

Situated in the intersection of audiovisual archives, computational methods, and immersive interactions, this work probes the increasingly important accessibility issues from a two-fold approach. Firstly, the work proposes an ontological data model to hand ...

Defining a universal metric for Quality of Experience (QoE) is notoriously hard due to the complex relationship between low-level performance metrics and user satisfaction. The most common metric, the Mean Opinion Score (MOS), has well-known biases and inc ...

Harnessing the power of machine learning (ML) and other Artificial Intelligence (AI) techniques promises substantial improvements across forensic psychiatry, supposedly offering more objective evaluations and predictions. However, AI-based predictions abou ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

Understanding user’s perception of service variability is essential to discern their overall perception of any type of (transport) service. We study the perception of waiting time variability for ride-hailing services. We carried out a stated preference su ...

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

Trust Indicators and Explainable AI: A Study on User Perceptions

Chattez avec Graph Search

The Metaverse as a Virtual Model of Platform Urbanism: Its Converging AIoT, XReality, Neurotech, and Nanobiotech and Their Applications, Challenges, and Risks

Sensitivity to user mischaracterizations in electric vehicle charging

Referencing in YouTube Knowledge Communication Videos

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Towards more Practical Threat Models in Artificial Intelligence Security

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Learning a QoE Metric from Social Media and Gaming Footage

Out of their minds? Externalist challenges for using AI in forensic psychiatry

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability

Towards Novel Evaluation Methods for Social Dialog Systems