The Pragmatic Turn in Explainable Artificial Intelligence (XAI) [PDF]
Minds and Machines, 2019 In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders.
Andrés Páez
core +8 more sources
eXplainable Artificial Intelligence (XAI) for improving organisational regility [PDF]
PLoS ONESince the pandemic started, organisations have been actively seeking ways to improve their organisational agility and resilience (regility) and turn to Artificial Intelligence (AI) to gain a deeper understanding and further enhance their agility and regility. Organisations are turning to AI as a critical enabler to achieve these goals.
Niusha Shafiabady +5 more
doaj +6 more sources
XAI—Explainable artificial intelligence [PDF]
Science Robotics, 2019 Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications.
David Gunning +5 more
openaire +6 more sources
Explainable Artificial Intelligence (XAI) in Insurance
Risks, 2022 Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry ...
Emer Owens +5 more
doaj +2 more sources
Editorial: Explainable Artificial Intelligence (XAI) in Systems Neuroscience. [PDF]
Front Syst Neurosci, 2021 In the last 10 years, we have experienced exceptional growth in the development of machine-learning-based (ML) algorithms for the analysis of different medical conditions and for developing clinical decision support systems. In particular, the availability of large datasets and the increasing complexity of both hardware and software systems have ...
Lombardi A, Tavares JMRS, Tangaro S.
europepmc +6 more sources
Regulating eXplainable Artificial Intelligence (XAI) May Harm Consumers [PDF]
Marketing Science, 2022 This work analyzes the impact of regulating explainable artificial intelligence.
Behnam Mohammadi +3 more
openalex +3 more sources
Towards explainable artificial intelligence (XAI)
, 2020 unknown ...
Tiia Haverinen
openalex +2 more sources
Histological Image Classification Between Follicular Lymphoma and Reactive Lymphoid Tissue Using Deep Learning and Explainable Artificial Intelligence (XAI). [PDF]
Cancers (Basel)Carreras J +9 more
europepmc +3 more sources
eXplainable Artificial Intelligence (XAI): A Systematic Review for Unveiling the Black Box Models and Their Relevance to Biomedical Imaging and Sensing. [PDF]
Sensors (Basel)Hettikankanamage N +5 more
europepmc +3 more sources
Exploring Explainable Artificial Intelligence for Transparent Decision Making [PDF]
E3S Web of Conferences, 2023 Artificial intelligence (AI) has become a potent tool in many fields, allowing complicated tasks to be completed with astounding effectiveness. However, as AI systems get more complex, worries about their interpretability and transparency have become ...
Praveenraj D. David Winster +6 more
doaj +1 more source