artificial intelligence

Backlash of AI Monitoring: Untangling the Cause of Counterproductive Work Behavior in Construction Projects

While the ubiquitous adoption of artificial intelligence (AI) monitoring in construction projects has substantiated significant gains in operational efficiency and safety, its backlash remains theoretically underdeveloped. In practice, AI is gradually replacing human supervisors to monitor workers’ operation trajecto...

Artificial Intelligence-Based Biomarkers for Alzheimer's Disease: Current Advances, Challenges, and Future Directions

Artificial intelligence of things for autonomous irrigation: A systematic review and system maturity model

Responsible Research Assessment in the Age of Artificial Intelligence: Challenges and Future Directions

Artificial intelligence-driven traffic flow prediction: A comprehensive survey of models, applications, and future directions

Pengaruh Literasi Digital terhadap Etika Penggunaan Artificial Intelligence pada Mahasiswa Perguruan Tinggi

Findings indicate that students with higher digital literacy tend to use AI more ethically, responsibly, and transparently, and this study recommends strengthening digital literacy programs with an emphasis on AI ethics in higher education.

Human-AI Communication Symbiosis: How Educators Reconstruct Authority and Identity in the Algorithmic Era

Teachers' epistemological authority is diminishing as they negotiate the hegemonic algorithmic communication, and they respond to the students' fear of cognitive degradation by reorienting from a "knowledge transmitting" communicative practice towards "ethical verifiers" and "empathetic listeners".

Vision-Language Model-Based System for Automated and Proactive Construction Fence Management to Enhance Severe Weather Preparedness

Construction fences can become unstable during high-wind events, particularly when attached objects such as signage, banners, or shade cloths increase the surface area exposed to wind. However, current inspection and preparedness practices often rely on manual observation, limited time and labor, and practitioners’ f...

WMIP: A Working-Memory-Inspired Programmable Probe of Cumulative State Tracking in Large Language Models

This work introduces a working-memory-inspired probe of cumulative state tracking with program-computed answers, 3 to 100 updates, and final-state, intermediate-state, or multi-target queries and compares protocols on identical items.

Computational Phenomenology of Borderline Personality Disorder: A Comparative Evaluation of LLM-Simulated Expert Personas and Human Clinical Experts

Building on a human-led thematic analysis of clinical life-story interviews (> 150,000 words) with inpatients with Borderline Personality Disorder, this study examines the capacity of large language models (OpenAI's GPT, Google's Gemini, and Anthropic's Claude) to support qualitative clinical analysis. The models' inte...

On Discovering Algorithms for Adversarial Imitation Learning

Adversarial Imitation Learning (AIL) methods, while effective in settings with limited expert demonstrations, are often considered unstable. These approaches typically decompose into two components: Density Ratio (DR) estimation $\frac{\rho_E}{\rho_{\pi}}$, where a discriminator estimates the relative occupancy of stat...

Preserving the Privacy of Reward Functions in MDPs through Deception

Preserving the privacy of preferences (or rewards) of a sequential decision-making agent when decisions are observable is crucial in many physical and cybersecurity domains. For instance, in wildlife monitoring, agents must allocate patrolling resources without revealing animal locations to poachers. This paper address...