Related papers: A Context-based Trust Management Model for Pervasi…
The emerging need for qualitative approaches in context-aware information processing calls for proper modeling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of…
This empirical study proposes a novel methodology to measure users' perceived trust in an Explainable Artificial Intelligence (XAI) model. To do so, users' mental models are elicited using Fuzzy Cognitive Maps (FCMs). First, we exploit an…
Group Decision-Making (GDM) plays a crucial role in various real-life scenarios where individuals express their opinions in natural language rather than structured numerical values. Traditional GDM approaches often overlook the subjectivity…
This study explores the integration of contextual explanations into AI-powered loan decision systems to enhance trust and usability. While traditional AI systems rely heavily on algorithmic transparency and technical accuracy, they often…
Social participatory sensing is a newly proposed paradigm that tries to address the limitations of participatory sensing by leveraging online social networks as an infrastructure. A critical issue in the success of this paradigm is to…
This chapter will survey pervasive computing with a look at how its constraint for transparency affects issues of resource management and security. The goal of pervasive computing is to render computing transparent, such that computing…
Trust is an absolute necessity for digital communications; but is often viewed as an implicit singular entity. The use of the internet as the primary vehicle for information exchange has made accountability and verifiability of system code…
Trust is central to human social interactions, manifesting in actions that make one vulnerable to another. We argue that trust will thus depend on the decision-making processes that arise in neural systems. Building on advances in the…
To answer a question, language models often need to integrate prior knowledge learned during pretraining and new information presented in context. We hypothesize that models perform this integration in a predictable way across different…
Trust models are widely used in various computer science disciplines. The main purpose of a trust model is to continuously measure trustworthiness of a set of entities based on their behaviors. In this article, the novel notion of "rational…
Developments in pervasive computing introduced a new world of computing where networked processors embedded and distributed in everyday objects communicating with each other over wireless links. Computers in such environments work in the…
Ethics has become a major concern to the information management community, as both algorithms and data should satisfy ethical rules that guarantee not to generate dishonourable behaviours when they are used. However, these ethical rules may…
Pervasive social computing is a promising approach that promises to empower both the individual and the whole and thus candidates itself as a foundation to the "smarter" social organizations that our new turbulent and resource-scarce worlds…
In many large scale distributed systems and on the web, agents need to interact with other unknown agents to carry out some tasks or transactions. The ability to reason about and assess the potential risks in carrying out such transactions…
Causal inference, a critical tool for informing business decisions, traditionally relies heavily on structured data. However, in many real-world scenarios, such data can be incomplete or unavailable. This paper presents a framework that…
Recommender systems aim to help users find relevant items more quickly by providing personalized recommendations. Explanations in recommender systems help users understand why such recommendations have been generated, which in turn makes…
Handling trust is one of the core requirements for facilitating effective interaction between the human and the AI agent. Thus, any decision-making framework designed to work with humans must possess the ability to estimate and leverage…
Crowdsourcing refers to the arrangement in which contributions are solicited from a large group of unrelated people. Due to this nature, crowdsourcers (or task requesters) often face uncertainty about the workers' capabilities which, in…
This paper proposes a new fuzzy assessing procedure with application in management decision making. The proposed fuzzy approach build the membership functions for system characteristics of a standby repairable system. This method is used to…
In dealing with veracity of data analytics, fuzzy methods are more and more relying on probabilistic and statistical techniques to underpin their applicability. Conversely, standard statistical models usually disregard to take into account…