• Conference
    • About
    • Topics
    • Organisation & Committees
    • Awards
    • Grants & support
  • Calls
    • Call for papers
    • Call for workshops/special tracks
    • Call for doctoral consortium proposals
    • Call for late-breaking works & demos
  • Submissions
    • Important dates
    • Submit an article
    • Submit a Doctoral proposal
    • Review process
    • Registration
    • Publication & indexing
  • Programme
    • Invited speakers
    • Full programme
    • Accepted special tracks
      • Special track: Model-agnostic explanations
      • Special Track: Explainable AI in Finance
      • Special Track: Neuro-symbolic xAI
      • Special Track: xAI in biomedicine
      • Special Track: xAI in the Public Sector
      • Special Track: visual representations & analytics for xAI
      • Special Track: Actionable eXplainable AI
      • Special Track: xAI for Trustworthy & Responsible AI
      • Special Track: Interdisciplinary Perspectives on XAI
      • Special Track: Trustworthy Surveillance Systems via Computer Vision xAI
      • Special Track: eXplainable AI in Cybersecurity
      • Special Track: eXplainable AI in Education
      • Special Track: Explainable & Interpretable AI with Argumentation
      • Special track: XAI for decision-making & human-AI collaboration
      • Special Track: Human-centered explanations for XAI
      • Special Track: Explanations for Advice-Giving Systems
      • Special track: XAI in health-care
      • Special track: Causality & Explainable AI
      • Special Track: xAI for Machine Learning on Graphs with Ontologies & Graph Neural Networks
      • Special track: xAI for time series
      • Special track: XAI in Automotive & Industrial Applications
    • Panel discussion
    • Conference banquet
    • Code of conduct
  • Sponsors
    • Become a sponsor
    • Sponsors / Partners
  • Location
    • Conference venue
    • Travel
    • Accomodation
    • Practical info
REGISTER NOW
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The World Conference on eXplainable Artificial Intelligence

The World Conference on eXplainable Artificial Intelligence

(xAI 2023)

  • Conference
    • About
    • Topics
    • Organisation & Committees
    • Awards
    • Grants & support
  • Calls
    • Call for papers
    • Call for workshops/special tracks
    • Call for doctoral consortium proposals
    • Call for late-breaking works & demos
  • Submissions
    • Important dates
    • Submit an article
    • Submit a Doctoral proposal
    • Review process
    • Registration
    • Publication & indexing
  • Programme
    • Invited speakers
    • Full programme
    • Accepted special tracks
      • Special track: Model-agnostic explanations
      • Special Track: Explainable AI in Finance
      • Special Track: Neuro-symbolic xAI
      • Special Track: xAI in biomedicine
      • Special Track: xAI in the Public Sector
      • Special Track: visual representations & analytics for xAI
      • Special Track: Actionable eXplainable AI
      • Special Track: xAI for Trustworthy & Responsible AI
      • Special Track: Interdisciplinary Perspectives on XAI
      • Special Track: Trustworthy Surveillance Systems via Computer Vision xAI
      • Special Track: eXplainable AI in Cybersecurity
      • Special Track: eXplainable AI in Education
      • Special Track: Explainable & Interpretable AI with Argumentation
      • Special track: XAI for decision-making & human-AI collaboration
      • Special Track: Human-centered explanations for XAI
      • Special Track: Explanations for Advice-Giving Systems
      • Special track: XAI in health-care
      • Special track: Causality & Explainable AI
      • Special Track: xAI for Machine Learning on Graphs with Ontologies & Graph Neural Networks
      • Special track: xAI for time series
      • Special track: XAI in Automotive & Industrial Applications
    • Panel discussion
    • Conference banquet
    • Code of conduct
  • Sponsors
    • Become a sponsor
    • Sponsors / Partners
  • Location
    • Conference venue
    • Travel
    • Accomodation
    • Practical info
REGISTER NOW

The 1st World Conference on eXplainable Artificial Intelligence (xAI 2023)

July 26-28, 2023 - Lisboa, Portugal

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eXplainable Artificial Intelligence

1st World Conference on Explainable Artificial Intelligence (XAI 2023) The World Conference on Explainable Artificial Intelligence (XAI 2023) is an annual event that aims to bring together researchers, academics, and professionals, promoting the sharing and discussion of knowledge, new perspectives, experiences, and innovations in the field of eXplainable Artificial Intelligence (XAI). This event is multidisciplinary and interdisciplinary, …

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Call for papers

1st International Conference on eXplainable Artificial Intelligence (xAI 2023) Call for papers (26/28 July 2023, Lisbon, Portugal) Artificial intelligence has seen a significant shift in focus towards designing and developing intelligent systems that are interpretable and explainable. This is due to the complexity of the models, built from data, and the legal requirements imposed by …

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Call for Doctoral Consortium papers

1st International Conference on eXplainable Artificial Intelligence (xAI 2023) Call for Doctoral Consortium papers (26/28 July 2023, Lisbon, Portugal) The conference provides an opportunity for doctoral scholars to explore and develop their research interests under the guidance of distinguished researchers and industry practitioners from the field. Doctoral scholars should consider participating in the Doctoral Consortium …

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Call for Late-Breaking works & demos

1st International Conference on eXplainable Artificial Intelligence (xAI 2023) Call for late-breaking results & demos (26/28 July 2023, Lisbon, Portugal) The conference organisation invites Late-Breaking Results (LBR) and demonstration papers of innovative XAI-based systems (including research prototypes), as described below. Late-Breaking Results We encourage researchers and practitioners to submit late-breaking work as it provides a …

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Action Influence Graphs, Agent-based explainable systems, Ante-hoc approaches for interpretability, Argumentative-based approaches for explanations, Argumentation theory for explainable AI, Attention mechanisms for XAI, Automata for explaining Recurrent Neural Network models, Auto-encoders & explainability of latent spaces, Bayesian modelling for interpretable models, Black-boxes vs white-boxes, Case-based explanations for AI systems, Causal inference & explanations, Constraints-based explanations, Decomposition of neural network-based models for XAI, Deep learning & XAI methods, Defeasible reasoning for explainability, Evaluation approaches for XAI-based systems, Explainable methods for edge computing, Expert systems for explainability, Explainability & the semantic web, Explainability of signal processing methods, Finite state machines for enabling explainability, Fuzzy systems & logic for explainability, Graph neural networks for explainability, Hybrid & transparent black box modelling, Interpreting & explaining Convolutional Neural Network, Interpretable representational learning, Methods for latent spaces interpretations, Model-specific vs model-agnostic methods for XAI, Neuro-symbolic reasoning for XAI, Natural language processing for explanations, Ontologies & taxonomies for supporting XAI, Pruning methods with XAI, Post-hoc methods for explainability, Reinforcement learning for enhancing XAI systems, Reasoning under uncertainty for explanation, Rule-based XAI systems, Robotics & explainability, Sample-centric & Dataset-centric explanations, Self-explainable methods for XAI, Sentence embeddings to explainable semantic features, Transparent & explainable learning methods, User interfaces for explainability, Visual methods for representational learning, XAI Benchmarking, XAI methods for neuroimaging & neural signals, XAI & reservoir computing. Accountability & responsibility in XAI-based technologies,
Addressing user-centric requirements for XAI systems,
Assessment of model accuracy & interpretability trade-off,
Explainable Bias & fairness of XAI-based systems,
Explainability for discovering,
 improving,
 controlling & justifying,
Explainability as a prerequisite for responsible AI systems,
Explainability & data fusion,
Explainability & responsibility in policy guidelines,
Explainability pitfalls & dark patterns in XAI,
Historical foundations of XAI,
Moral principles & dilemma for XAI-based systems,
Multimodal XAI approaches,
Philosophical consideration of synthetic explanations,
Prevention & detection of deceptive AI explanations,
Social implications of automatically-generated explanations,
Theoretical foundations of XAI,
Trust & explainable AI,
The logic of scientific explanation for/in AI,
The epistemic & moral goods expected from explaining AI,
XAI for fairness checking,
XAI for time series-based approaches,
XAI for transparency & unbiased decision making,
Algorithmic transparency & actionability,
Cognitive approaches & architectures for explanations,
Cognitive relief in explanations,
Contrastive nature of explanations,
Comprehensibility vs interpretability vs explainability,
Counterfactual explanations,
Designing new explanation styles,
Explanations for correctability,
Faithfulness & intelligibility of explanations,
Interpretability vs traceability,
Interestingness & informativeness of explanations,
Irrelevance of probabilities to explanations,
Iterative dialogue explanations,
Justification & explanations in AI-based systems,
Local vs global interpretability & explainability,
Methods for assessing the quality of explanations,
Non-technical explanations in AI-based systems,
Notions and metrics of/for explainability,
Persuasiveness & robustness of explanations,
Psychometrics of human explanations,
Qualitative approaches for explainability,
Questionnaires & surveys for explainability,
Scrutability & diagnosis of XAI methods,
Soundness & stability of XAI methods,
Theories of explanation,
Adaptive explainable systems,
Backward & forward-looking responsibility forms to XAI,
Data provenance & explainability,
Explainability for reputation,
Epistemic and non-epistemic values for XAI,
Human-centric explainable AI,
Person-specific XAI systems,
Presentation & personalization of AI explanations for target groups,
Social nature of explanations,
Black-box model auditing & explanation,
Explainability in regulatory compliance,
Human rights for explanations in AI systems,
Policy-based systems of explanations,
The potential harm of explainability in AI,
Trustworthiness of explanations for clinicians & patients,
XAI methods for model governance,
XAI in policy development,
XAI to increase situational awareness & compliance behaviour,
Adversarial attacks explanations,
Explanations for risk assessment,
Explainability of federated learning,
Explainable IoT malware detection,
Privacy & agency of explanations,
XAI for Privacy-Preserving Systems,
XAI techniques of stealing attack & defence,
XAI for human-AI cooperation,
XAI & models output confidence estimation,
Application of XAI in cognitive computing,
Dialogue systems for enhancing explainability,
Explainable methods for medical diagnosis,
Business & Marketing,
Biomedical knowledge discovery & explainability,
Explainable methods for Human-computer Interaction,
Explainability in decision-support systems,
Explainable recommender systems,
Explainable methods for finance & automatic trading systems,
Explainability in agricultural AI-based methods,
Explainability in transportation systems,
Explainability for unmanned aerial vehicles (UAV),
Explainability in brain-computer interface systems,
Interactive applications for XAI,
Manufacturing chains & application of XAI systems,
Models of explanations in criminology,
 cybersecurity & defence,
XAI approaches in Industry 4.0,
XAI systems for health-care,
XAI technologies for autonomous driving,
XAI methods for bioinformatics,
XAI methods for linguistics & machine translation,
XAI methods for neuroscience,
XAI models & applications for IoT,
XAI methods for XAI for terrestrial,
 atmospheric,
 & ocean remote sensing,
XAI in sustainable finance & climate finance,
XAI in bio-signals analysis

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