Requirements engineering for artificial intelligence systems: A systematic mapping study
Context: In traditional software systems, Requirements Engineering (RE) activities are well-
established and researched. However, building Artificial Intelligence (AI) based software …
established and researched. However, building Artificial Intelligence (AI) based software …
Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges
When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
A manifesto on explainability for artificial intelligence in medicine
The rapid increase of interest in, and use of, artificial intelligence (AI) in computer
applications has raised a parallel concern about its ability (or lack thereof) to provide …
applications has raised a parallel concern about its ability (or lack thereof) to provide …
Ignore, trust, or negotiate: understanding clinician acceptance of AI-based treatment recommendations in health care
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …
clinician acceptance remains a critical barrier. We developed a novel decision support …
Explainable artificial intelligence: Evaluating the objective and subjective impacts of xai on human-agent interaction
Intelligent agents must be able to communicate intentions and explain their decision-making
processes to build trust, foster confidence, and improve human-agent team dynamics …
processes to build trust, foster confidence, and improve human-agent team dynamics …
An explainable artificial intelligence approach for financial distress prediction
Z Zhang, C Wu, S Qu, X Chen - Information Processing & Management, 2022 - Elsevier
External stakeholders require accurate and explainable financial distress prediction (FDP)
models. Complex machine learning algorithms offer high accuracy, but most of them lack …
models. Complex machine learning algorithms offer high accuracy, but most of them lack …
Xair: A framework of explainable ai in augmented reality
Explainable AI (XAI) has established itself as an important component of AI-driven
interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives …
interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives …
A situation awareness perspective on human-AI interaction: Tensions and opportunities
With the emergent focus on human-centered artificial intelligence (HCAI), research is
required to understand the humanistic aspects of AI design, identify the mechanisms through …
required to understand the humanistic aspects of AI design, identify the mechanisms through …
[HTML][HTML] Requirements practices and gaps when engineering human-centered Artificial Intelligence systems
Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …
many challenges, unknowns, and limited proven best practices. Big companies such as …
Who needs explanation and when? Juggling explainable AI and user epistemic uncertainty
In recent years, AI explainability (XAI) has received wide attention. Although XAI is expected
to play a positive role in decision-making and advice acceptance, various opposing effects …
to play a positive role in decision-making and advice acceptance, various opposing effects …