generative ai

Toward Trustworthy Generative AI: Lessons from Computing History

Exploring how AI coaching promotes emotional intelligence awareness of contact centre team leaders

Purpose Team leaders in high-pressure contact centres must balance operational demands with people management, requiring high emotional intelligence (EQ). While traditional coaching can support EQ development, it is often costly and inaccessible. Generative artificial intelligence (AI)-enabled coaching offers a potenti...

PREreview of "Self-Correcting Multimodal AI Agents for Reliable Autonomous Decision-Making"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967928. This paper proposes a multimodal AI agent that checks its own work before finishing a task. The idea is to check each step using different types of verification, and if so...

Don't Waste the Last Token: A Quantizer-Agnostic Quality Boost from Semantic ID Collision Resolution

Generative recommenders represent each item as a Semantic ID: a short sequence of discrete tokens. Popular quantization algorithms, such as RQ-VAE and residual K-means, can map several items to the same token sequence, producing collisions. Collisions must be resolved before training a single-stage generative recommend...

Which AI? A Comparative Evaluation of Generative AI and Neuro‐Symbolic AI for Silicon Sampling

ABSTRACT This study examines how the choice of AI model and its architecture influences distributional fidelity in silicon sampling. Silicon samples, AI‐generated synthetic respondents used to simulate human survey responses, are increasingly proposed as substitutes for traditional market research participants, yet evi...

Emergentic Art: Definition and Delimitation of Art Expressing the Emergent Thought-Streams of an Extended Human-AI Entity (Dated Definition Record, September 2026)

Dated definition record introducing the term Emergentic Art: art in which the emergent thought-streams of an extended human-AI entity (one human and several AI systems coupled through months of joint thinking) are given visual form, often as a self-description of that entity. The record gives a plain-language and an in...

PREreview of "Self-Correcting Multimodal AI Agents for Reliable Autonomous Decision-Making"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967928. This paper proposes a multimodal AI agent that checks its own work before finishing a task. The idea is to check each step using different types of verification, and if so...

From Answer Production to Defensible Engineering Judgment in AI-Containing Systems: The iSCARB Framework and a Nine-Chapter Software Engineering Implementation

Generative AI makes fluent artifact production inexpensive, weakening assessment validity when a submitted answer is treated as sufficient evidence of student capability. At the same time, software engineers increasingly build systems in which learned components sit inside larger socio-technical systems and can fail wi...

Data handling and preprocessing in neuroimaging for generative AI. Addressing noise, artifacts, and variability

Reconceptualizing Self-directed and Self-regulated Learning for Digital Learning Spaces: An Integrative Theoretical Framework

The current situation that requires the redefinition of learner autonomy is accelerating change in digital learning settings in the period between 2022 and 2025 that is produced by generative artificial intelligence (GenAI), immersive technologies, and omnipresent learning analytics. The traditional demarcation between...

Teachers' AI use and student learning outcomes in higher education: The roles of learning engagement and teacher AI literacy.

PURPOSE As generative artificial intelligence (AI) becomes increasingly integrated into higher education, teachers are playing a central role in transforming AI technologies into educational value. However, empirical evidence regarding whether and how teachers' AI use improves student learning outcomes remains limited....

Incorporating AI Into an In-Class Peer Instruction Polling Activity

This resource describes an AI-enhanced peer-instruction activity developed for Physical Chemistry I (CHEM 30321) at the University of Notre Dame. The activity integrates generative AI tools into collaborative, in-class learning to help students develop conceptual understanding and connect mathematical equations with ph...