human-in-the-loop

This paper evaluates 19 unsupervised anomaly detection models on the BowTie manufacturing dataset, finding performance less stable than benchmarks suggest, and presents a deployed human-in-the-loop framework for manufactured-part inspection.

This paper proposes a 'Capability Ladder' framework for modernizing computing curricula in the AI era, arguing that near-term AI effects involve task reallocation rather than job replacement and advocating targeted curriculum updates around durable capabilities.

The author contrasts AI sidekicks with autonomous background agents, arguing that background agents deliver 10x more enterprise value but are far harder to build due to workflow re-engineering and limited AI talent.

A reflective post questioning where the line should be drawn on AI agent autonomy, discussing the risk levels of various actions and whether human approval should remain mandatory for certain decisions.

A tweet discusses the missing piece in self-improving agents: a strict review gate where an experienced engineer must approve each skill. It explains how a growing library improves discovery and extraction quality, with humans approving all merges to keep the system trustworthy.

Discusses how human approval in AI agent workflows can be meaningless if the approved action differs from the executed one, urging stricter binding between approval and final action.

A practitioner argues that autonomous AI agents are unreliable in production, advocating for constrained agentic workflows with human-in-the-loop triggers instead of full autonomy.

A browser game simulating human-in-the-loop approval of AI coding agent commands shows that players miss about 1 in 3 threats on average, with credential-exfiltrating commands missed far more often than destructive ones.

The author shares experience building a human-in-the-loop approval system for an enterprise agent platform, emphasizing that the approval step must be a true blocking pause with editable parameters and first-class rejection/editing outcomes, and asks how others structure agent suspension.

This design-based study investigates how pedagogical scaffolding can help ethnic minority preparatory students shift from passive consumption to critical co-creation with Generative AI in prompt engineering tasks, resulting in improved prompt self-efficacy and active gatekeeping of AI-generated content.

A developer reflects on an AI automation project that achieved 95% accuracy but still required full human review, leading to a redesign that routes uncertain outputs to a review queue and saves time overall.

This paper presents a human-in-the-loop workflow for creating a corpus of LLM-based simplifications of scientific summaries, using SciSummNet and GPT-4o-mini with non-expert and expert feedback to improve cross-disciplinary accessibility.

ProcAgent is a fully on-device, agentic, vision-based procedural assistant that uses a propose-and-verify architecture for real-time adaptive guidance on an NVIDIA Jetson AGX Orin. It supports both reactive and proactive modes with human-in-the-loop confirmation, achieving responsive interaction and positive user study ratings.

A team used AI to automate a manual document sorting process, reducing labor from 50-70 hours to 3-5 hours per month by grouping scanned pages into documents and generating PDFs.

Un rapport KPMG indique que 59% des entreprises utilisent déjà l'IA en marketing en 2026, mais beaucoup sans cadre, ce qui entraîne des hallucinations, une dilution de la voix de marque et des problèmes de SEO. L'article détaille 7 pièges majeurs et propose des parades comme le human-in-the-loop, le RAG, le GEO et la gouvernance.

This paper presents a human-in-the-loop bootstrapping method for detecting PFM-1 mines in UAV hyperspectral imagery, showing that ACE with bootstrapping can find all targets in 2 rounds of inspection, while aggregate ROC-AUC scores hide large operational differences between detectors.

The article discusses a design decision where AI drafts a reply for users to approve before sending, emphasizing a human-in-the-loop approach to maintain control and quality.

This article discusses how human testers who evaluate AI systems for dangers are struggling to keep up with the rapid pace of AI development, highlighting growing concerns about safety oversight.

This paper presents a retrieval-augmented, multi-agent LLM framework with human-in-the-loop for detecting cutaneous immune-related adverse events from clinical notes, achieving higher accuracy, improved inter-rater agreement, and halved review time compared to manual review.

Aventos explains their workflow for creating AI-generated anime, balancing human creativity in writing, directing, and post-production with AI for animation and effects.