Counterfactual explanations can promote accountability, fairness, and transparency in AI-supported decision-making by demonstrating how changes in input data can alter outcomes, offering actionable feedback for users to revise unfavorable decisions. However, the majority of counterfactual algorithms focus on tabular an...
Eoin D. Delaney, Greta Warren, Derek Greene et al.· Proceedings of the AAAI/ACM...· 0 citations
Online scams increasingly leverage fluent and context-aware social-engineering strategies, creating growing demand for AI systems that explain why a message may be risky. However, explanations that cite detector-derived evidence may still semantically weaken or redirect the intended risk interpretation. We introduce VE...
Heajun An, Connor Ng, Sandesh Sharma Dulal et al.· Proceedings of the AAAI/ACM...· 0 citations
Abstract The oil&gas sector increasingly depends on agile, reliable, and explainable workflow automation to support production and operations activities such as wellbore fault diagnostic, maintenance, and pipeline scheduling. However, existing genAI-based agents technologies are limited by complex workflow forming, lac...
H. Chen, L. Zhao, H. Jiang et al.· SPE Asia Pacific Oil & Gas C...· 0 citations
Emotion regulation is a key construct in mental health, yet existing measures differ in conceptual coverage, with some focusing on specific strategies or regulatory difficulties rather than broader cognitive, behavioral, and contextual regulation processes. This study aimed to develop an Emotion Regulation Scale (ERS)...
Iman Aly Almohammadi, Malak Ali Alzahrani· BMC Psychology· 0 citations
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Machine learning systems increasingly make life-changing decisions about individuals, such as loan approvals, hiring, and cheating detection, raising a pressing question: how can individuals respond to negative decisions made by these opaque systems? While explainable artificial intelligence (XAI) has largely focused o...
Timo Freiesleben, Kristof Meding, Gunnar König· Proceedings of the AAAI/ACM...· 0 citations
The harms in which AI is implicated range in nature and scope from unsafe user interactions through to the societal-wide consequences of AI adoption. Classification of the diverse risks of AI is foundational to AI governance: regulators, technology firms, and policymakers need structured accounts of risk upon which to...
Glen Berman, Ned Cooper, Angel Hsing‐Chi Hwang et al.· Proceedings of the AAAI/ACM...· 0 citations
When algorithms make or influence consequential decisions—about loan eligibility, hiring, or healthcare—EU law grants affected individuals a Right to Explanation. Yet whether (and how) Explainable AI (XAI) can satisfy this right in practice remains poorly understood, with direct implications for individuals' ability to...
Benjamin Frész, Elena Dubovitskaya, Marco F. Huber· Proceedings of the AAAI/ACM...· 0 citations
Generative AI systems are increasingly deployed in high-stakes professional contexts, where their outputs shape what users believe, how they reason, and what they treat as settled. This raises a central question for responsible AI: under what conditions is reliance on generative AI outputs epistemically warranted rathe...
Nimisha Karnatak, Max Van Kleek, Nigel Shadbolt· Proceedings of the AAAI/ACM...· 0 citations
Value‑aware AI systems require explicit computational representations of human values (groundings) and their aggregation into value systems in order to align their decisions with ours. As such representations are difficult to elicit, value learning seeks to infer them by observing human behaviour. This work addresses t...
Andrés Holgado-Sánchez, Holger Billhardt, Sascha Ossowskí· Proceedings of the AAAI/ACM...· 0 citations
Preliminary, context-specific evidence that combining multimodal learner information with interpretable adaptive support may contribute to language development, engagement, and metacognitive reading-strategy awareness while preserving meaningful human oversight is provided.
Houda Boumediene, A. Aljohani, M. Bouakkaz· Acta Psychologica· 0 citations
INTRODUCTION
Although preventable, dental caries remains a global public health challenge due to its multifactorial nature and the deep influence of socio-structural determinants. This study evaluates the performance of Artificial Intelligence (AI) models as decision-support frameworks for population-level risk strati...
Jessye Melgarejo Do Amaral Giordani, Orlando Luiz Do Amaral, Maria Laura Braccini Fagundes et al.· Caries Research· 0 citations
Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder characterized by persistent symptoms of inattention, hyperactivity, and impulsivity that significantly affect cognitive, academic, and social functioning. Although electroencephalography (EEG) has emerged as a promising...
F. Rohani, S. Mostafavi, P. Ebrahimifakhar et al.· medRxiv· 0 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
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