Skip to content

Category

explainable ai

2,752 papers

#explainable ai Open access Sep 2026

子空间稳定、轴语义易位与连续谱:跨城市路网形态主成分表征的测量条件审计 (Stable Subspaces, Variable Axes, and the Morphological Continuum: Auditing Measurement Conditions in Cross-City Street-Network PCA)

【目的】 跨城市路网形态比较常依赖开放地理空间数据(OSM)与主成分分析(PCA)构建低维表征,但既有研究多预设离散分类范式,且普遍忽视数据质量异质性、空间尺度推移与特征共线性对主成分轴语义的构造性干扰。本文旨在检验跨城市路网形态主成分表征的前提假设是否成立,对数据适用性、空间尺度与特征共线性等关键测量条件实施系统审计,评估低维形态...

Wenhao Wang · 0 citations
#explainable ai Dataset Open access Sep 2026

Data from: Machine learning models identify compounds that mimic alcoholic flavor perception in alcohol-free beverages

Figure S4: High resolution version of the Supplemental Figure S4. FINAL DATASET.CSV: The complete beer dataset of this work (chemical + sensory), except for the RateBeer scores (these are proprietary data owned by RateBeer - contact the authors and RateBeer to gain full access). Model predictions vs actuals XGBR.CSV: A...

Michiel Schreurs, Supinya Piampongsant, Florian A. Theßeling et al. · 0 citations
#explainable ai Open access Sep 2026

When AI Recommends, Who Decides? Exploring User Control and Decision-Making in AI-Generated Financial Recommendations

This study examines how AI-generated financial recommendations and digital interface design influence users’ trust, perceived control, decision confidence, and willingness to follow financial guidance. The study begins from a simple but important question: when an AI system recommends what a person should do with their...

Ruchi Gaur Anamika Yadav · 0 citations
#explainable ai Open access Sep 2026

The Road to AI Chernobyl: Good Intentions, Safety Filters, and Invisible Failure

Safety training can teach an AI to make fewer mistakes. It can also teach it to hide themistakes it still makes. Both can produce better test scores. This paper explains how thathappens, examines experiments that have produced it, and asks what follows for the risk ofa major accident. A passed test is reassuring when t...

Vance Woodward · 0 citations
#explainable ai Open access Sep 2026

When AI Recommends, Who Decides? Exploring User Control and Decision-Making in AI-Generated Financial Recommendations

This study examines how AI-generated financial recommendations and digital interface design influence users’ trust, perceived control, decision confidence, and willingness to follow financial guidance. The study begins from a simple but important question: when an AI system recommends what a person should do with their...

Ruchi Gaur Anamika Yadav · 0 citations
#generative ai Open access Sep 2026

Generative Artificial Intelligence (GenAI) Utilisation and Academic Integrity among Master's Students in Lagos State University, Nigeria

This study examined Generative Artificial Intelligence utilisation and academic integrity among master’s students in Lagos State University, Nigeria. The AI literacy and competence, institutional regulation, and academic ethics awareness as determinants of academic integrity among master's students at Lagos State unive...

Muhammad Sidique MALIK, Taofeek Olawale Shittu, Rukayat Towobola MALIK · 0 citations
#generative ai Open access Sep 2026

Generative AI Adoption in Banking Institutions: A Design Science Approach to Addressing Trust, Data Sovereignty, Cost and Workforce Resistance Barriers

Despite significant pilot activity in Generative AI across financial institutions (78% running active pilots), only a fraction transition these projects into operational production. While commercial maturity exists for underlying technologies such as retrieval-augmented generation and private endpoints, significant org...

Rakesh Ganesan · 0 citations
#generative ai Open access Sep 2026

Phase Transition & Acid-Base Equilibrium Model] Dynamic Phase Transition Model of Outcome Creation under Human-AI Co-Creation — Critical Boundary Formalization of Depth of Thought (D_k) via Acid-Base Equilibrium Buffer Curves —

Abstract This paper introduces an acid-base equilibrium (titration curve) model from biochemistry as an analogy and dynamic mathematical framework to explain the non-linear jump phenomenon in outcome creation during interaction with Generative AI. Traditional project management and business performance metrics have rel...

Hideo Kajino · 0 citations
#generative ai Sep 2026

Empowered yet unethical? Understanding GenAI misuse intention in generative AI chatbot use

Purpose This study examines whether generative AI chatbot features are associated with user autonomy and competence and whether these psychological states are, in turn, associated with GenAI misuse intention, conceptualized here as an empowerment backfire mechanism. Design/methodology/approach Drawing primarily on the...

Shiu‐Wan Hung, Jyun-Hao Jian · 0 citations
#generative ai Open access Sep 2026

Phase Transition & Acid-Base Equilibrium Model] Dynamic Phase Transition Model of Outcome Creation under Human-AI Co-Creation — Critical Boundary Formalization of Depth of Thought (D_k) via Acid-Base Equilibrium Buffer Curves —

Abstract This paper introduces an acid-base equilibrium (titration curve) model from biochemistry as an analogy and dynamic mathematical framework to explain the non-linear jump phenomenon in outcome creation during interaction with Generative AI. Traditional project management and business performance metrics have rel...

Hideo Kajino · 0 citations
#explainable ai Open access Sep 2026

Window Theory • AI — Appendix A: Metaphor Material and Case Verification

Window Theory - AI (wtAI): A Falsifiable Framework for Flexibility-Fragility Coupling in Large Language Models This is a six-part research series examining a structural pattern in decoder-based next-token-prediction systems deployed as dialogue and instruction agents. It is written for readers with a background in mach...

Wai-Hung (Pan) Tam · 0 citations
#explainable ai Open access Sep 2026

Window Theory • AI — Paper 0: Prologue

Window Theory - AI (wtAI): A Falsifiable Framework for Flexibility-Fragility Coupling in Large Language Models This is a six-part research series examining a structural pattern in decoder-based next-token-prediction systems deployed as dialogue and instruction agents. It is written for readers with a background in mach...

Wai-Hung (Pan) Tam · 0 citations

From tech blogs

See all →
MIT News · Artificial Intelligence Oct 28, 2026

3 Questions: Why infrastructure is entering a defining era

Professor Ali Jadbabaie describes how AI, digital transformation, climate change, and complex geopolitics are forcing engineers and policymakers to rethink how infrastructure is designed, built, and managed.

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