Buchumschlag

AI Knows What's Wrong But Cannot Fix It: Helicoid Dynamics in Frontier LLMs Under High-Stakes Decisions

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
1. Verfasser:	Jadad, Alejandro R
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Artificial Intelligence Human-Computer Interaction
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Leading Across the Spectrum of Human-AI Relationships: A Conceptual Framework for Increasingly Heterogeneous Teams
von: Jadad, Alejandro R.
Veröffentlicht: (2026)

Engaging with AI: How Interface Design Shapes Human-AI Collaboration in High-Stakes Decision-Making
von: Chen, Zichen, et al.
Veröffentlicht: (2025)

Responsible LLM Deployment for High-Stake Decisions by Decentralized Technologies and Human-AI Interactions
von: Sachan, Swati, et al.
Veröffentlicht: (2025)

Who Does What? Archetypes of Roles Assigned to LLMs During Human-AI Decision-Making
von: Chappidi, Shreya, et al.
Veröffentlicht: (2026)

What Do People Want to Know About Artificial Intelligence (AI)? The Importance of Answering End-User Questions to Explain Autonomous Vehicle (AV) Decisions
von: Molaei, Somayeh, et al.
Veröffentlicht: (2025)

Making LLMs Reliable When It Matters Most: A Five-Layer Architecture for High-Stakes Decisions
von: Jadad, Alejandro R.
Veröffentlicht: (2025)

Model Cards for AI Teammates: Comparing Human-AI Team Familiarization Methods for High-Stakes Environments
von: Bowers, Ryan, et al.
Veröffentlicht: (2025)

"My Grade is Wrong!": A Contestable AI Framework for Interactive Feedback in Evaluating Student Essays
von: Hong, Shengxin, et al.
Veröffentlicht: (2024)

Supporting Data-Frame Dynamics in AI-assisted Decision Making
von: Zheng, Chengbo, et al.
Veröffentlicht: (2025)

Humans Perceive Wrong Narratives from AI Reasoning Texts
von: Levy, Mosh, et al.
Veröffentlicht: (2025)

What Large Language Models Know and What People Think They Know
von: Steyvers, Mark, et al.
Veröffentlicht: (2024)

It Cannot Be Right If It Was Written by AI: On Lawyers' Preferences of Documents Perceived as Authored by an LLM vs a Human
von: Harasta, Jakub, et al.
Veröffentlicht: (2024)

Using AI Uncertainty Quantification to Improve Human Decision-Making
von: Marusich, Laura R., et al.
Veröffentlicht: (2023)

Bridging the Experimental Last Mile: Digitizing Laboratory Know-How for Safe AI-Assisted Support
von: Miura, Akira, et al.
Veröffentlicht: (2026)

"Over-the-Hood" AI Inclusivity Bugs and How 3 AI Product Teams Found and Fixed Them
von: Anderson, Andrew, et al.
Veröffentlicht: (2025)

Not All Trust is the Same: Effects of Decision Workflow and Explanations in Human-AI Decision Making
von: Spillner, Laura, et al.
Veröffentlicht: (2026)

From Evidence to Decision: Exploring Evaluative AI
von: Le, Thao, et al.
Veröffentlicht: (2024)

AI and Collective Decisions: Strengthening Legitimacy and Losers' Consent
von: Fulay, Suyash, et al.
Veröffentlicht: (2026)

A Decision Theoretic Framework for Measuring AI Reliance
von: Guo, Ziyang, et al.
Veröffentlicht: (2024)

Biased AI can Influence Political Decision-Making
von: Fisher, Jillian, et al.
Veröffentlicht: (2024)

The Impact of Imperfect XAI on Human-AI Decision-Making
von: Morrison, Katelyn, et al.
Veröffentlicht: (2023)

ComplLLM: Fine-tuning LLMs to Discover Complementary Signals for Decision-making
von: Guo, Ziyang, et al.
Veröffentlicht: (2026)

Beyond Accuracy: How AI Metacognitive Sensitivity improves AI-assisted Decision Making
von: Li, ZhaoBin, et al.
Veröffentlicht: (2025)

Augmenting Human Cognition With Generative AI: Lessons From AI-Assisted Decision-Making
von: Zhang, Zelun Tony, et al.
Veröffentlicht: (2025)

Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making
von: Ma, Shuai, et al.
Veröffentlicht: (2024)

Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making
von: Schoeffer, Jakob, et al.
Veröffentlicht: (2022)

Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions
von: Cau, Federico Maria, et al.
Veröffentlicht: (2025)

AI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventions
von: Schoeffer, Jakob, et al.
Veröffentlicht: (2023)

Beyond Recommender: An Exploratory Study of the Effects of Different AI Roles in AI-Assisted Decision Making
von: Ma, Shuai, et al.
Veröffentlicht: (2024)

Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings
von: Silva, Inês Oliveira e, et al.
Veröffentlicht: (2026)

Rethinking Health Agents: From Siloed AI to Collaborative Decision Mediators
von: Chung, Ray-Yuan, et al.
Veröffentlicht: (2026)

Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision Making
von: Li, Zhuoyan, et al.
Veröffentlicht: (2024)

As Confidence Aligns: Exploring the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making
von: Li, Jingshu, et al.
Veröffentlicht: (2025)

User Decision Guidance with Selective Explanation Presentation from Explainable-AI
von: Fukuchi, Yosuke, et al.
Veröffentlicht: (2024)

2-Factor Retrieval for Improved Human-AI Decision Making in Radiology
von: Solomon, Jim, et al.
Veröffentlicht: (2024)

What happens when reviewers receive AI feedback in their reviews?
von: Chen, Shiping, et al.
Veröffentlicht: (2026)

How Culture Shapes What People Want From AI
von: Ge, Xiao, et al.
Veröffentlicht: (2024)

AI persuading AI vs AI persuading Humans: LLMs' Differential Effectiveness in Promoting Pro-Environmental Behavior
von: Doudkin, Alexander, et al.
Veröffentlicht: (2025)

Anthropomorphism on Risk Perception: The Role of Trust and Domain Knowledge in Decision-Support AI
von: Reani, Manuele, et al.
Veröffentlicht: (2026)

Understanding the Effects of Miscalibrated AI Confidence on User Trust, Reliance, and Decision Efficacy
von: Li, Jingshu, et al.
Veröffentlicht: (2024)