A bibliometric analysis of the explainable artificial intelligence research field. In Information Processing and Management of Uncertainty in Knowledge-Based Systems-Theory and Foundations ...Dec 4, 2021 · The stated goal of explainable artificial intelligence (XAI) was to create a suite of new or modified machine learning techniques that produce explainable models that, when combined with effective explanation techniques, enable end users to understand, appropriately trust, and effectively manage the emerging generation of AI systems. An Explainable Artificial Intelligence (XAI) has become one of the evolving technology due to the recent advancements in machine learning techniques. Researchers have developed many XAI tools that applicable for various domains and provide support for the understanding of AI-based black-box models. The Shapely … The World Conference on Explainable Artificial Intelligence is an annual event that aims to bring together researchers, academics, and professionals, promoting the sharing and discussing of knowledge, new perspectives, experiences, and innovations in eXplainable Artificial Intelligence (XAI). This event is multidisciplinary and ... Artificial Intelligence (AI) has emerged as a game-changer in various industries. One of the most significant applications of AI is in the development of intelligent apps. Artifici...Explainable Artificial Intelligence, or XAI, is a paradigm within the field of AI that focuses on creating systems capable of providing understandable explanations for …Artificial Intelligence (AI) has emerged as a game-changer in various industries. One of the most significant applications of AI is in the development of intelligent apps. Artifici...Oct 26, 2022 · With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essential in the development of cybersecurity solutions. However, sharing the same fundamental limitation with other DL application domains, such as computer vision (CV ... DARPA's explainable artificial intelligence (XAI) program endeavors to create AI systems whose learned models and decisions can be understood and appropriately trusted by end users. Realizing this goal requires methods for learning more explainable models, designing effective explanation interfaces, and understanding the …Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI). XAI can explain how AI obtained a particular …The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns regarding explainability. Recent studies have discussed the emerging demand for explainable AI (XAI); however, a systematic review of explainable artificial intelligence from an end user's perspective can provide a comprehensive understanding …Analysts at Credit Suisse have a price target of $275 on Nvidia, saying its hardware and software give it an edge over rivals in AI. Jump to When it comes to artificial intelligenc...XAI—Explainable artificial intelligence. Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications. Recent successes in machine learning (ML) have led to a new wave of artificial intelligence (AI) applications that offer extensive benefits to a diverse range of fields.Explainable artificial intelligence (XAI) refers to a collection of procedures and techniques that enable machine learning algorithms to produce output and results …Aug 10, 2023 · The field of explainable artificial intelligence (XAI) has witnessed the emergence of numerous methods and techniques aimed at comprehending the intricate workings of deep learning models. Currently, some survey papers have made efforts to summarize these methods and offer a fundamental understanding of the distinctions among various XAI ... Conclusion. This paper provides a novel finance data analysis approach based on explainable artificial intelligence applied to discovery the relationship between digital finance and consumption upgrading. Boosting trees was utilized as the machine learning model and Shapely value was adopted to interpret the model.Oct 22, 2019 · In the last years, Artificial Intelligence (AI) has achieved a notable momentum that may deliver the best of expectations over many application sectors across the field. For this to occur, the entire community stands in front of the barrier of explainability, an inherent problem of AI techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last ... Explainable Artificial Intelligence (xAI) is an established field with a vibrant community that has developed a variety of very successful approaches to explain and …The Explainable Artificial Intelligence (XAI) research area, as a developing branch of artificial intelligence (AI), is investigating various approaches that will allow the behavior of intelligent autonomous systems to be interpretable and understandable to humans. Human–machine interaction, on the bridge between Data Science and Social ...Explainable AI (explainable artificial intelligence (XAI)) is often considered a set of processes and methods that are used to describe deep learning models, by characterizing model accuracy, transparency, and outcomes in AI systems . XAI methods aim to provide human-readable explanations to help users comprehend and trust the …In today’s fast-paced digital landscape, businesses are constantly striving to stay ahead of the competition. One of the most effective ways to achieve this is through the implemen...Explainable Artificial Intelligence in Education: A Comprehensive Review. Blerta Abazi Chaushi, Besnik Selimi, Agron Chaushi, Marika Apostolova; Pages 48-71. Contrastive Visual Explanations for Reinforcement Learning via Counterfactual Rewards. Xiaowei Liu, Kevin McAreavey, Weiru Liu;XAI: Explainable artificial intelligence. The search queries were. This article aims to demonstrate the potential of XAI, especially interpretable machine learning techniques, for analyzing agricultural datasets. After a brief introduction to the concept of interpretable machine learning, I show how interpretable machine …Introduction. Artificial Intelligence (AI), a research area initiated in the 1950ies (Mccarthy et al., Citation 2006), has received significant attention in science and practice.Global spending on AI systems is expected to more than double from 38 billion USD in 2019 to 98 billion USD by 2023 (Shirer & Daquila, Citation 2019).Emphasizing on …Explainable artificial intelligence (XAI) studies and designs approaches, algorithms and tools producing human-understandable explanations of AI-based systems information and decisions. This article presents a comprehensive survey of AI and XAI-based methods adopted in the Industry 4.0 scenario. First, …Conclusion. This paper provides a novel finance data analysis approach based on explainable artificial intelligence applied to discovery the relationship between digital finance and consumption upgrading. Boosting trees was utilized as the machine learning model and Shapely value was adopted to interpret the model.The literature on artificial intelligence (AI) or machine learning (ML) in mental health and psychiatry lacks consensus on what “explainability” means. In the more general XAI (eXplainable AI ...Abstract. Explainable artificial intelligence (AI) has drawn a lot of attention recently since AI systems are being employed more often across a variety of industries, including education. Building trust and increasing the efficacy of AI systems in educational settings requires the capacity to explain how they make decisions.Explainable artificial intelligence reveals the interactive effects of environmental variables in species distribution models. Abstract Seagrass is a globally vital marine resource that plays an essential global role in combating climate change, protecting coastlines, ensuring food security, and enriching biodiversity.While explainable artificial intelligence (XAI) has gained ground in diverse fields, including healthcare, numerous unexplored facets remain within the realm of medical imaging. To better understand the complexities of DL techniques, there is an urgent need for rapid advancement in the field of eXplainable DL (XDL) or eXplainable Artificial ...The literature on artificial intelligence (AI) or machine learning (ML) in mental health and psychiatry lacks consensus on what “explainability” means. In the more general XAI (eXplainable AI ...The potential for an intelligent transportation system (ITS) has been made possible by the growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration of IoT and ITS—known as the Internet of vehicles (IoV). To achieve the goal of automatic driving and efficient mobility, IoV is now combined with modern …XAI: Explainable artificial intelligence. The search queries were. This article aims to demonstrate the potential of XAI, especially interpretable machine learning techniques, for analyzing agricultural datasets. After a brief introduction to the concept of interpretable machine learning, I show how interpretable machine …Explainable AI is a set of tools and frameworks to help you understand and interpret predictions made by your machine learning models, natively integrated with a number of …eXplainable artificial intelligence (XAI) has emerged as a subfield of AI that aims to develop machine learning models capable of providing clear explanations for their decisions. By incorporating XAI principles into CRS, the algorithm seeks to enhance the transparency and interpretability of the recommendations provided to farmers. Research …Explainable Artificial Intelligence (XAI), a promising future technology in the field of healthcare, has attracted significant interest. Despite ongoing efforts in the …Explainable AI (XAI) is artificial intelligence that can document how specific outcomes were generated in such a way that ordinary humans can understand the process. The goal of XAI is to make sure that artificial intelligence programs are transparent regarding both the purpose they serve and how they …Jan 1, 2022 · There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent ... Explainable AI is an artificial intelligence method or technique in which the solution can be evaluated and understood by humans. It differs from standard ML techniques, in which researchers frequently fail to comprehend why the system has reached a particular conclusion.Explainable artificial intelligence. XAI refers to methods and techniques in the application of artificial intelligence (AI) such that the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where even its designers cannot explain why an AI arrived at a specific decision.What used to be just a pipe dream in the realms of science fiction, artificial intelligence (AI) is now mainstream technology in our everyday lives with applications in image and v...Explainable artificial intelligence (XAI) is a research direction that was already put under scrutiny, in particular in the AI&Law community. Whilst there were notable developments in the area of (general, not necessarily legal) XAI, user experience studies regarding such methods, as well as more general studies pertaining to the concept of explainability …Argumentation and eXplainable Artificial Intelligence (XAI) are closely related, as in the recent years, Argumentation has been used for providing Explainability to AI. Argumentation can show step by step how an AI System reaches a decision; it can provide reasoning over uncertainty and can find solutions when conflicting …In this study, we propose the application of an explainable artificial intelligence (XAI) model that incorporates the Shapley additive explanation (SHAP) model to interpret the outcomes of convolutional neural network (CNN) deep learning models, and analyze the impact of variables on flood susceptibility mapping. This …Feb 12, 2024 ... Artificial intelligence (AI) and machine learning (ML) impact our lives in many ways. From mundane tasks to critical decision-making ...Jan 17, 2022 · Explainable artificial intelligence (XAI) is a powerful tool in answering critical How? and Why? questions about AI systems and can be used to address rising ethical and legal concerns. As a result, AI researchers have identified XAI as a necessary feature of trustworthy AI, and explainability has experienced a recent surge in attention. Figure 1. Photo by Arseny Togulev on Unsplash. T his might be the first time you hear about Explainable Artificial Intelligence, but it is certainly something you should have an opinion about. Explainable AI (XAI) refers to the techniques and methods to build AI applications that humans can understand …Explainable AI is an artificial intelligence method or technique in which the solution can be evaluated and understood by humans. It differs from standard ML techniques, in which researchers frequently fail to comprehend why the system has reached a particular conclusion.Artificial intelligence involves complex studies in many areas of math, computer science and other hard sciences. Experts outfit computers and machines with specialized parts, help...Dec 18, 2019 · Abstract. Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications. Recent successes in machine learning (ML) have led to a new wave of artificial intelligence (AI) applications that offer extensive benefits to a diverse range of fields. However, many of these systems are ... Argumentation and eXplainable Artificial Intelligence (XAI) are closely related, as in the recent years, Argumentation has been used for providing Explainability to AI. Argumentation can show step by step how an AI System reaches a decision; it can provide reasoning over uncertainty and can find solutions when conflicting …Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead …Explainable Artificial Intelligence (xAI) is an established field with a vibrant community that has developed a variety of very successful approaches to explain and …Recently, explainable artificial intelligence has emerged as an area of research that goes beyond pure prediction improvement by extracting knowledge from deep learning methodologies through the interpretation of their results. We investigate such explanations to explore the genetic architectures of phenotypes in genome-wide …Genomics. Artificial intelligence (AI) models based on deep learning now represent the state of the art for making functional predictions in genomics research. However, the underlying basis on which predictive models make such predictions is often unknown. For genomics researchers, this missing explanatory in ….DARPA's explainable artificial intelligence (XAI) program endeavors to create AI systems whose learned models and decisions can be understood and appropriately trusted by end users. Realizing this goal requires methods for learning more explainable models, designing effective explanation interfaces, and understanding the …One of the tools for improving that is explainability which boosts trust and understanding of decisions between humans and machines. This research offers an update on the current …PMID: 37527200. DOI: 10.1097/ICU.0000000000000983. We summarize an overview of the key concepts, and categorize some examples of commonly employed XAI methods. Specific to ophthalmology, we explore XAI from a clinical perspective, in enhancing end-user trust, assisting clinical management, and uncovering new insights.The recent approaches from the explainable artificial intelligence (XAI) research domain pursue the objective of tackling these issues by facilitating a healthy collaboration between the human users and artificial intelligent systems. Generating relevant explanations tailored to the mental models, technical and …Dec 8, 2020 ... While there is no corresponding programmed knowledge in machine learning models, AI explanations could be used, for instance, to discover ... Keywords: Explainable artificial intelligence, method classification, survey, systematic literature review 1. Introduction The number of scientific articles, conferences and symposia around the world in eXplainable Artificial Intelligence (XAI) has significantly increased over the last decade [1, 2]. This has led Sep 29, 2021 · Four Principles of Explainable Artificial Intelligence. Published. September 29, 2021. Author(s) In recent years, there has been a significant surge in the adoption of industrial automation across various sectors. This rise can be attributed to the advancements in artificial i...Explainable artificial intelligence (AI) has drawn a lot of attention recently since AI systems are being employed more often across a variety of industries, including education. Building trust and increasing the efficacy of AI systems in educational settings requires the capacity to explain how they make decisions. This article provides a ...Explainable AI refers to methods and techniques in the application of artificial intelligence technology (AI) such that the results of the solution can be understood by human experts. It contrasts with the concept of the “black box” in machine learning where even their designers cannot explain why the AI arrived at …Apr 6, 2020 · NIST held a virtual workshop on Explainable Artificial Intelligence (AI) on January 26-28, 2021. Explainable AI is a key element of trustworthy AI and there is significant interest in explainable AI from stakeholders, communities, and areas across this multidisciplinary field. As part of NIST’s efforts to provide foundational tools, guidance ... XAI, or explainable artificial intelligence, is gaining importance for GPTs (Generative Pretrained Transformers) as these models become more sophisticated and capable. GPTs are notorious for their lack of interpretability and transparency, despite achieving remarkable results in several applications. This makes it difficult to …There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that …Explainable AI (XAI) techniques aim to provide additional information about a model's decision thereby improving trust in model's decisions, as shown in Fig. 1 “An explainable model is one which provides explanations for its predictions at the human level for a specific task. An interpretable model is one for which some …Nov 16, 2023 ... Explainability considered a critical component of trustworthy artificial intelligence (AI) systems, has been proposed to address AI systems' ...The potential for an intelligent transportation system (ITS) has been made possible by the growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration of IoT and ITS—known as the Internet of vehicles (IoV). To achieve the goal of automatic driving and efficient mobility, IoV is now combined with modern …Feb 27, 2021 ... It is a field dedicated to studying methods. Artificial Intelligence applications produce solutions that can be explained, acting as a ...Jan 1, 2023 · The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns regarding explainability. Recent studies have discussed the emerging demand for explainable AI (XAI); however, a systematic review of explainable artificial intelligence from an end user's perspective can provide a comprehensive understanding of the current situation and help close the research gap. Abstract. The last decade has witnessed the rise of a black box society where obscure classification models are adopted by Artificial Intelligence systems (AI). The lack of explanations of how AI systems make decisions is a key ethical issue to their adoption in socially sensitive and safety-critical contexts.May 17, 2022 ... Explainable AI Explained As the field of artificial intelligence (AI) has matured, increasingly complex opaque models have been developed ...Explainable AI is a set of tools and frameworks to help you understand and interpret predictions made by your machine learning models, natively integrated with a number of …May 17, 2022 ... The emerging field of explainable AI (or XAI) can help banks navigate issues of transparency and trust, and provide greater clarity on their AI ...Introduction. Artificial Intelligence (AI), a research area initiated in the 1950ies (Mccarthy et al., Citation 2006), has received significant attention in science and practice.Global spending on AI systems is expected to more than double from 38 billion USD in 2019 to 98 billion USD by 2023 (Shirer & Daquila, Citation 2019).Emphasizing on …Explainable Artificial Intelligence (XAI) is a new set of techniques that attempts to provide such an understanding, here we report on some of these practical approaches. We discuss the potential value of XAI to the field of neurostimulation for both basic scientific inquiry and therapeutic purposes, as well …Jul 12, 2021 · 1 INTRODUCTION. Artificial intelligence (AI) and machine learning (ML) have demonstrated their potential to revolutionize industries, public services, and society, achieving or even surpassing human levels of performance in terms of accuracy for a range of problems, such as image and speech recognition (Mnih et al., 2015) and language translation (Young et al., 2018). Explainable artificial intelligence (XAI) refers to methods and techniques that produce accurate, explainable models of why and how an AI algorithm arrives at a specific …Apr 15, 2020 ... Explainable AI is one of the hottest topics in the field of Machine Learning. Machine Learning models are often thought of as black boxes ...Background: The International Prognostic Index (IPI) is applied to predict the outcome of chronic lymphocytic leukemia (CLL) with five prognostic factors, including genetic analysis. We investigated whether multiparameter flow cytometry (MPFC) data of CLL samples could predict the outcome by methods of …The purpose of this study was to create an explainable artificial intelligence framework combining data preprocessing methods, machine learning methods, and model interpretability methods to identify people at high risk of COPD in the smoking population and to provide a reasonable interpretation of model predictions. The data comprised ...To facilitate greater human acceptability of these systems, explainable artificial intelligence (XAI) has experienced significant growth over the last couple of years with the development of highly accurate models but with a paucity of explainability and interpretability. The literature shows evidence from numerous studies on the philosophy …Artificial Intelligence (AI) is a rapidly growing field of technology that has already made a significant impact on many industries. AI is the development of computer systems that ...There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that …Genomics. Artificial intelligence (AI) models based on deep learning now represent the state of the art for making functional predictions in genomics research. However, the underlying basis on which predictive models make such predictions is often unknown. For genomics researchers, this missing explanatory in ….Apr 15, 2020 ... Explainable AI is one of the hottest topics in the field of Machine Learning. Machine Learning models are often thought of as black boxes ...
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The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this …Explainable AI is one of the hottest topics in the field of Machine Learning. Machine Learning models are often thought of as black boxes that are imposible to …To foster user understanding and appropriate trust in such systems, we assessed the effects of explainable artificial intelligence (XAI) methods and an educational intervention on AI-assisted decision-making behavior in a 2 × 2 between subjects online experiment with N = 410 participants. We developed a novel use …Explainable artificial intelligence. XAI refers to methods and techniques in the application of artificial intelligence (AI) such that the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where even its designers cannot explain why an AI arrived at a specific decision.The World Conference on Explainable Artificial Intelligence is an annual event that aims to bring together researchers, academics, and professionals, promoting the sharing and discussing of knowledge, new perspectives, experiences, and innovations in eXplainable Artificial Intelligence (XAI). This event is multidisciplinary and ...Aug 17, 2020 · 152. We present four fundamental principles for explainable AI systems. These principles are. 153. heavily influenced by considering the AI system’s interaction with the human recipient of. 154. the information. The requirements of the given situation, the task at hand, and the consumer. How does machine learning work? Learn more about how artificial intelligence makes its decisions in this HowStuffWorks Now article. Advertisement If you want to sort through vast n...Microsoft Corp. March 21 (Reuters) - The United Nations General Assembly on Thursday unanimously adopted the first global resolution on artificial intelligence that …Abstract. This study focuses on explainable artificial intelligence (XAI) in finance. We collected 2,733 articles published between 2013 and 2023 from the Web of Science Core Collection and analyzed trends in literature development and future prospects using an integrated CiteSpace and Natural Language Processing (NLP) bibliometric …Model accuracy was reported and analyzed using explainable artificial intelligence (XAI), to justify the trustworthiness, ability, and reliability of the AI-based solutions in IDS. XAI [ 6 ] is a method that allows humans to understand the results of a model, as models are too difficult to understand and explain due to their black-box …Mar 4, 2021 ... Visual explanations. Visual explainable methods produce pictures or plots in order to provide information about the model's decision. Most ...Feb 26, 2024 · What users obtain from explainable artificial intelligence is the precondition for trust, rather than novel knowledge. This trust necessitates satisfaction via a comprehensive RDF, implying that ... WASHINGTON – Today, Secretary of Homeland Security Alejandro N. Mayorkas and Chief Information Officer and Chief Artificial Intelligence Officer Eric …Artificial intelligence (AI) is a rapidly growing field of technology that has the potential to revolutionize the way we live and work. AI is defined as the ability of a computer o....