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explainable ai

2,810 papers

#explainable ai Review Open access Sep 2026

Preserving Professional Skepticism in the Age of Algorithmic Auditing: A Conceptual Framework for AI Adoption in Accounting Practice

Generative artificial intelligence (AI) has moved beyond the transactional automation that characterized earlier accounting technologies such as robotic process automation and rule-based expert systems. Large language models and machine-learning-based analytics can now draft audit memoranda, flag anomalies in real time...

Pathan Aiyubkhan, Vaidhya Narendrabhai · 0 citations
#explainable ai Open access Sep 2026

Accessibility-Aware Adaptive AI Interfaces for Intelligent Web Applications: A Human-in-the-Loop Framework

Intelligent web applications increasingly personalize content, navigation and task support through artificial intelligence. However, many adaptive interfaces are optimized for engagement or efficiency rather than accessibility, which can create new barriers for users with visual, motor, cognitive or situational limitat...

Teja Kolli Venkata Krishna · 0 citations
#explainable ai Sep 2026

Machine learning integrated explainable artificial intelligence in predicting toxicities of enfortumab vedotin in urothelial carcinoma: an exploratory study.

Preliminary, hypothesis-generating findings suggest ML may predict EV-related toxicities, but single train-test split, small event counts, and lack of external validation preclude clinical use.

K. Sridharan, Mattia Alberto Di Civita, G. Sivaramakrishnan et al. · 0 citations
#explainable ai Open access Sep 2026

Artificial Intelligence in Public Health: Optimizing Clinical Triage and Preventing Infectious Disease Outbreaks

Artificial intelligence (AI) is increasingly transforming public health from a predominantlyreactive model of treating established disease towards proactive detection, prediction, andprevention. Within hospitals, natural language processing and machine learning can analyseelectronic health records, clinical observation...

Max Van Massey · 0 citations
#explainable ai Open access Sep 2026

Segmentation Guided Explainable Deep Learning for Multi-Class Skin Disease Detection

This research centers on the creation of a "Segmentation-Guided" Explainable Deep Learning system, built specifically to sharpen the accuracy of skin disease detection and fix the "trust gap" currently plaguing digital dermatology. To move past the limitations of typical "black-box" models—where the inner logic is hidd...

Anika Ayesha Azam, Hasan Md. Imrul · 0 citations
#explainable ai Open access Sep 2026

Elements: SWXACE: Space Weather Explainable Analytics Cyber Ecosystem

Space weather forecasting requires models that are accurate, interpretable, and actionable. This project delivers a set of modular cyberinfrastructure, including models, datasets, and software, for trustworthy solar transient prediction by integrating novel local and global explanations and uncertainty quantification t...

Berkay Aydin, Manolis Georgoulis · 0 citations
#explainable ai Open access Sep 2026

AI-Based Detection of Dark Patterns in Digital Interfaces

This research presents an AI-based approach for detecting dark patterns in digital interfaces. The proposed framework analyzes textual, visual, and structural elements of websites and applications to identify potentially manipulative design practices. It uses multimodal analysis and explainable AI to provide understand...

Inas Fathima · 0 citations
#explainable ai Open access Sep 2026

The Dollar or the Worm? Your Bait Matters When You Hook Participants for Psychological Research

While online psychological research relies heavily on paid crowdsourcing platforms (e.g., Prolific, MTurk), existing platform evaluations focus almost exclusively on surface-level task engagement (attention checks, completion time) rather than psychological validity. This paper introduces the distinction between "dolla...

Maria Aleksandrova · 0 citations
#explainable ai Open access Sep 2026

Transport Papers T11. The Origin of Mass

T11 of the Transport Papers. Version 1.0. 24 pages. Epistemic status: Tier B. Mass enters a conformally invariant theory where scale does: as coupling to the frozen point, the parallel scale tractor of squared norm Λ/3. We prove the mass-weight dictionary: a density of conformal weight w coupled to the frozen point thr...

Leon Butler · 0 citations
#explainable ai Review Open access Sep 2026

AI Transparency, Privacy Control, and Consumer Trust as Drivers of Purchase Intention in Omnichannel Retail

This study examines the effects of AI transparency and privacy control on purchase intention through consumer trust in omnichannel retail. Methods: An explanatory quantitative design was applied to survey data from 100 omnichannel consumers in Yogyakarta City selected through purposive sampling. The reflective measurem...

Salamatun Asakdiyah, Nur Afifah, Hetty Karunia Tunjungsari · 0 citations
#explainable ai Open access Sep 2026

Transport Papers T11. The Origin of Mass

T11 of the Transport Papers. Version 1.0. 24 pages. Epistemic status: Tier B. Mass enters a conformally invariant theory where scale does: as coupling to the frozen point, the parallel scale tractor of squared norm Λ/3. We prove the mass-weight dictionary: a density of conformal weight w coupled to the frozen point thr...

Leon Butler · 0 citations
#explainable ai Open access Sep 2026

Impact of AI on Students' Performance in Economics in Kaduna Metropolis Secondary Schools

This study investigated the effect of Artificial Intelligence (AI) tools on the academic performance of Senior Secondary School students in Economics in selected schools within Kaduna Metropolis, Kaduna State, Nigeria. Adopting a descriptive correlational survey design, data were collected from five hundred (500) Senio...

Ayo David Adeyemi, Chinedu Okocha, Saheed Hammed et al. · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 30, 2026

Q&A: Hey AI, who should I vote for this year?

MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.

Microsoft Research Blog Oct 30, 2026

From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence

Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.

GPT-Lab Oct 30, 2026

Black October? The Week AI Changed the Cybersecurity Conversation

Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.

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