explainable ai

Judgment-Centred Software Engineering Education: A Post-Hype Review and Framework for AI-Augmented Learning

The concept of comprehension debt is extended: the deferred learning and maintenance cost that arises when AI-assisted production outpaces a learner's or team's ability to explain, test, modify, and justify the resulting software.

Risk Scoring and Algorithmic Systems in Law Enforcement: Explainability, Human Oversight and the Right to Challenge

This report examines the use of algorithmic risk assessments in law enforcement and the safeguards required when a score influences an individual's treatment. It analyses data quality, the object of prediction, classification errors, discriminatory effects and the distinction between an intermediate assessment and a de...

Hypersonics Explained: High-Speed Aerodynamics, Flow Systems & Advanced Flight

This academic curriculum module delivers an analytical, physical, and computational exposition of hypersonics, high-speed aerodynamics, and aerothermodynamic transport phenomena across Mach 5+ atmospheric and reentry flight regimes. Key Technical Topics & Curricular Areas Covered:1. High-Enthalpy Compressible Aerodynam...

UNIFYING CONVENTIONAL AND LIGHTWEIGHT CONCRETE: AN EXPLAINABLE AI WEB APPLICATION FOR COMPRESSIVE STRENGTH PREDICTION

Explainable Anomaly Detection for Privacy-Preserving IoT Assistive Environments in Neurocognitive Healthcare

The use of artificial intelligence in education is currently discussed through the prism of personalization, conversational assistance, automated evaluation, and adoption on an institutional level, yet the entrepreneurial and cybersecurity sides of the progress are not included exhaustively. This chapter is based on th...

Code for Schizophrenia Classification from Multichannel EEG Using EEGNet with SHAP and Grad-CAM

This repository contains the code developed for EEG-based schizophrenia classification using the publicly available RepOD resting-state EEG dataset. The implementation includes EEG preprocessing, STFT-based input generation for the 3D-CNN, EEGNet classification, participant-wise Leave-One-Subject-Out (LOSO) and Stratif...

Aerospace Structures Explained: Materials, Design & Structural Engineering Systems

This academic curriculum module delivers an analytical, physical, and computational treatment of aerospace structures, thin-walled semimonocoque mechanics, and airframe structural integrity across atmospheric and space environments. Key Technical Topics & Curricular Areas Covered:1. Semimonocoque Structural Mechanics:...

Beyond Simulation: What Would It Take for Matter to Feel? An Explainer on a Falsifiable Programme for Primary Interoceptive Sentience

A popular-science explainer (not a scientific contribution in its own right) on the research programme "Necessary Conditions for Primary Interoceptive Sentience in Continuous Substrates: A Falsifiable Programme" (doi:10.5281/zenodo.22895484). It covers the No-Go Theorem for Consciousness on a Chip as heuristic motivati...

Solving the Cross-Sector Generalization Gap: A Generalizable AI Framework for Detecting Known and Unseen Cyberattacks in Critical Infrastructure

Governing generative AI in urban mobility: a five-pillar framework and twelve falsifiable propositions for operations, accountability, and public trust

Background Generative artificial intelligence (GenAI), encompassing large language models (LLMs), multimodal foundation models, diffusion-based traffic simulators, and agentic planners, is entering urban mobility operations across signal control, dynamic routing, demand forecasting, customer service, and autonomous fle...

AI-Driven Governance for Stablecoin Risk and Stability

This chapter examines the design, systemic risk behavior, and governance mechanisms of stablecoins within decentralized financial ecosystems. The study categorizes stablecoins into fiat-collateralized, crypto-collateralized, and algorithmic models while analyzing stabilization mechanisms, liquidity dynamics, and regula...

Human-Centered AI for Older Adults.

A set of actionable design recommendations was proposed to improve AI-powered technologies for older adults and highlighted older adults' concerns related to usability, personalization, privacy, and explainability of these technologies.