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Should explainers explain? [PDF]
Journal of Science Communication, 2005 One of the most common, and probably one of the crucial questions about science centers and interactive exhibitions is often phrased as “Ok, it’s fun, but do they learn anything?”. What follows is not an attempt to answer this question; we will just use it as a starting point for a discussion about the role of explainers in science centers.
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X-OODM: Explainable Object-Oriented Design Methodology
IEEE AccessIn software applications and decision-making systems, the explainability features can be instrumental for explicating internal working, accountability, understanding, fairness, and interpretation of decisions, processes, and data.
Abqa Javed +2 more
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Frontiers in Big Data, 2023 Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient services such as counseling and suggestive care. They are not used for patient diagnostic assistance because they cannot adhere to safety constraints and specialized ...
Kaushik Roy +5 more
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The role of explainability throughout the MLOps lifecycle: review and research agenda
Frontiers in Computer ScienceAs Machine Learning Operations (MLOps) adoption accelerates, systematic integration of explainability is imperative for reliability, transparency, and continuous quality assurance.
Sule Tekkesinoglu +2 more
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More Persuasive Explanation Method for End-to-End Driving Models
IEEE Access, 2023 With the rapid development of autonomous driving technology, a variety of high-performance end-to-end driving models (E2EDMs) are being proposed. In order to understand the computational methods of E2EDMs, pixel-level explanations methods are used to ...
Chenkai Zhang +3 more
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IEEE Access, 2022 There have existed many studies about the explainable artificial intelligence (XAI) that explains the logic behind the complex deep neural network called a black box.
Junhee Lee +4 more
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IEEE Access, 2023 Learning with graph-structured data, such as social, biological, and financial networks, requires effective low-dimensional representations to handle their large and complex interactions.
Hogun Park
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2020 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 2020 The Defense Advanced Research Projects Agency (DARPA) recently launched the Explainable Artificial Intelligence (XAI) program that aims to create a suite of new AI techniques that enable end users to understand, appropriately trust, and effectively manage the emerging generation of AI systems.
Luca Viganò 0001, Daniele Magazzeni
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EURASIP Journal on Image and Video ProcessingThe integration of Face Verification (FV) systems into multiple critical moments of daily life has become increasingly prevalent, raising concerns regarding the transparency and reliability of these systems.
Naima Bousnina +3 more
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BubblEX: An Explainable Deep Learning Framework for Point-Cloud Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Point-cloud data are nowadays one of the major data sources for describing our environment. Recently, deep architectures have been proposed as a key step in understanding and retrieving semantic information.
Francesca Matrone +4 more
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