explainable ai

Not another Superintelligence doom story

This paper pushes back on the scary narrative that superintelligent AI is about to "kill" us all, coming straight from the mouths of Big AI companies, AI safety community and AI experts. It uses the AI safety community's own math to show that what they call "rogue AI" is really just a program trying to get a good score...

Stiffness Fields on Skeleton--Surface Lines: Structured Physical Inference for AI-Driven Dynamics of Gaussian-Splat Entities

Physics-integrated Gaussian Splatting either prescribes material parameters by hand or estimates them point-wise from appearance, leaving unstructured numbers that inherit appearance confounding. We show that stiffness can instead be carried by structure: a two-dimensional field $F(s,t)$ on skeleton--surface lines, wit...

Stiffness Fields on Skeleton--Surface Lines: Structured Physical Inference for AI-Driven Dynamics of Gaussian-Splat Entities

Physics-integrated Gaussian Splatting either prescribes material parameters by hand or estimates them point-wise from appearance, leaving unstructured numbers that inherit appearance confounding. We show that stiffness can instead be carried by structure: a two-dimensional field $F(s,t)$ on skeleton--surface lines, wit...

Human Factors in Data Preparation

Data preparation is a cornerstone of the data science lifecycle, yet it remains one of the most time-consuming and human-dependent stages. Human factors are critical here, shaping how users interact with tools, perceive data quality, and make trade-offs under uncertainty. At the crossroads of Human–Computer Interaction...

AI Implementation Role Map

### How does an AI implementation role map work? An AI implementation role map assigns each build stage to people who can make decisions and operate the resulting workflow. Paloren provides AI strategy, implementation, automation and training, and Aaron Agius co-founded Paloren with Alex Agius before founding Louder. A...

Differentiated Coherence in Chinese News Media

This study examines how sociotechnical imaginaries of artificial intelligence (AI) in cultural heritage are organised across institutionally differentiated Chinese news media and reproduced over time. Drawing on nine outlets from 2022–2025, it combines exploratory computational mapping, thematic analysis, relation-focu...

An integrative theoretical model of AI-supported cybersecurity governance and organizational resilience

An integrative theoretical model explaining how and when AI-supported cybersecurity governance may contribute to organizational resilience is developed, and what AI changes in the positive pathway while explicitly recognizing heterogeneity across model classes and deployment arrangements is explained.

Internal Audit of Pension Funds: The Case of Georgias Funded Pension Scheme

DOI kodi: 10.52340/ekonomisti.2026.03.03 Annotation. Funded pension schemes in emerging economies are growing rapidly and accumulating substantial assets on behalf of millions of participants, placing exceptional demands on governance, risk management, and the internal audit function. This paper examines the extent to...

Eco-Sustainable Water Practice through Confidence-Bounded, Sensitive-Aware, and Explainable Machine Learning for Weir Oxygen Transfer

Autonomous Multi-agent Governance: AI Sentinel Framework for Mitigating Psychological Restraints in AI-Driven Fall Management

A Statistical-Signature Framework for Detecting Irreducible Stochasticity in CFD Simulations

Summary This preprint presents a 2D proof of concept for deciding, before an expensive simulation campaign, whether a pointwise (trajectory-level) grid-convergence study is an appropriate verification target. In chaotic flows, small differences, including those introduced by discretization, grow until pointwise agreeme...

Artificial Intelligence for Lacrimal Drainage Disorders: Advances in Diagnosis, Management, and Clinical Translation.

PURPOSE Lacrimal drainage disorders (LDDs) are common in oculoplastic practice, but their diagnostic evaluation continues to depend on tests that are variably subjective, operator-dependent, and at times invasive. In recent years, artificial intelligence (AI), spanning conventional machine learning (ML), deep learning...