Skip to content

Category

explainable ai

2,810 papers

#explainable ai Open access Sep 2026

Wind Power Forecasting Architectures in Complex Terrain and Coastal Environments: A Systematic Review and Meta-Analysis of Comparative Performance

Accurate wind resource estimation in complex environments, such as the Colombian Caribbean, is challenging due to air–sea heat fluxes and nonlinear atmospheric dynamics. This systematic review and meta-analysis synthesized empirical evidence from 49 studies to evaluate whether advanced forecasting architectures (artifi...

Maryam Carrillo-Reales, Adalberto Ospino-Castro, Diego Restrepo-Leal et al. · 0 citations
#explainable ai Sep 2026

Emotional AI 's Psychological Threat to Consumers: A Framework and Research Agenda

The Framework for Emotional AI Risk (FEAR) Matrix is introduced, which categorizes EAI's psychological threats along two dimensions: Pathways of Harm (mind‐driven vs system‐driven) and Scope of Impact (individual, relational, and cumulative).

Todd C. Haderlie, Anthony D. Miyazaki · 0 citations
#explainable ai Conference Open access Sep 2026

A Review on Human-Centered Machine Learning for Decision Support in High-Stakes Domains

It is argued that machine learning should support human judgment instead of replacing it, and common machine learning methods and several human-centered requirements are discussed, including explainability, appropriate trust, usability, workflow integration, fairness, accountability, and human oversight.

Yu-Hao Li · 0 citations
#generative ai Open access Sep 2026

Neuro-Symbolic Generative AI for Explainable Personalized Tutoring

The use of Generative Artificial Intelligence (AI) is showing great promise in the field of education by providing personalized and interactive tutoring. Yet, there are some issues with current Generative AI tutors, including hallucination, lack of transparency, lack of consistency in reasoning, and lack of personaliza...

Mohammed Alnaqeeb, Bharti Gawali · 0 citations
#generative ai Open access Sep 2026

Works for 9/12/2026 - Douglas C. Englebart

Listen and ask questions on Gemini Notebook: https://notebook.google.com/notebook/bcb0908b-c1b9-43a0-883e-6adb207bdc0a?authuser=1 Light from Light: The Father Gives Reason and the Spirit Makes Reason Accessible develops a recursive framework connecting biological reception, physiological state, cognitive accessibility,...

Ryan MacLean · 0 citations
#generative ai Open access Sep 2026

FROM SKILLS VERIFICATION TO WORKFORCE INTELLIGENCE A RESPONSIBLE AI FRAMEWORK FOR COMPETENCY-BASED WORKFORCE DECISION-MAKING

Artificial intelligence (AI) is increasingly used to support recruitment, skills analysis, learning, performance management and workforce planning. Yet many workforce decisions still depend heavily on static qualifications, curriculum vitae data, self-reported experience and periodic assessments. These sources remain v...

Rita Ebele Maduanusi · 0 citations
#generative ai Open access Sep 2026

Identifying the Components of AI Algorithm-Based Interactive Industrial Design

This study aimed to identify and explain the components of AI algorithm-based interactive industrial design and to develop a conceptual framework for organizing its contextual conditions, inputs, processes, and outputs. This applied qualitative study was conducted using a meta-synthesis approach. The research corpus in...

Marzieh Mohseni Kabir, Hossein Adab, M. Keramati · 0 citations
#generative ai Sep 2026

Vietnamese University Students’ Perceptions of Generative Artificial Intelligence in Higher Education: A Qualitative Study Through the Technology Acceptance Model

Background: Generative artificial intelligence (GenAI) has diffused rapidly across higher education worldwide, yet empirical evidence from Southeast Asian and Global South contexts remains limited. Vietnamese higher education, characterised by rapid expansion, strong digital-transformation agendas, and examination-orie...

Quan Phuc Nguyen · 0 citations
#generative ai Open access Sep 2026

Structured PREreview of "An assessment of normalization and differential expression methods for miRNA-seq analysis using a realistic benchmark dataset"

This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/22737224. Does the introduction explain the objective of the research presented in the preprint? Yes It explains the problem properly, namely the need for reliable method...

Namra Basharat · 0 citations
#generative ai Open access Sep 2026

Works for 9/12/2026 - Douglas C. Englebart

Listen and ask questions on Gemini Notebook: https://notebook.google.com/notebook/bcb0908b-c1b9-43a0-883e-6adb207bdc0a?authuser=1 Light from Light: The Father Gives Reason and the Spirit Makes Reason Accessible develops a recursive framework connecting biological reception, physiological state, cognitive accessibility,...

Ryan MacLean · 0 citations
#generative ai Book Open access Sep 2026

Generative AI Makes Creative Output More Homogeneous

A systematic review and meta-analysis of empirical studies on homogenization in human–AI co-creation reveals a small but statistically significant homogenization effect associated with AI use.

A. de Rooij, M. Biskjaer · 0 citations

From tech blogs

See all →
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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.