HCI.TOPHCI, made easy

arrow_backBack to questions View categoryarrow_forward

AI Explainability, Trust, and Calibration / LLM Trust and Over/Under-Reliance

Users struggle to achieve naturalness and trust when interacting with conversational AI.

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Users struggle to achieve naturalness and trust when interacting with conversational AI.

UbiComp '24The Personality Dimensions GPT-3 Expresses During Human-Chatbot Interactions

Similar questions

lightbulbPractical problemLLM Trust and Over/Under-Reliance

When operating multi-sensor smart devices, environments are complex and misoperations occur frequently.

IUI '25A Dynamic Bayesian Network Based Framework for Multimodal Context-Aware Interactions

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Users struggle to understand complex AI ecosystems, affecting privacy decisions.

IUI '25Mental Models of Generative AI Chatbot Ecosystem

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Ordinary users cannot effectively understand the behavioral logic and information sources of complex generative AI.

IUI '25Building Appropriate Mental Models: What Users Know and Want to Know about an Agentic AI Chatbot

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Users' inability to appropriately trust LLMs leads to wrong decisions or missed opportunities.

CHI '25To Rely or Not to Rely? Evaluating Interventions for Appropriate Reliance on Large Language Models

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Practitioners struggle to manage the large-scale, complex data required for LLM development.

CHI '25Emerging Data Practices: Data Work in the Era of Large Language Models

lightbulbPractical problemLLM Trust and Over/Under-Reliance

Existing text evaluation systems have limited coverage and unreliable results, affecting education and news generation applications.

CHI '25Think Together and Work Better: Combining Humans' and LLMs' Think-Aloud Outcomes for Effective Text Evaluation

Related papers

A Dynamic Bayesian Network Based Framework for Multimodal Context-Aware Interactions

Violet Yinuo Han, Tianyi Wang, Hyunsung Cho

Mental Models of Generative AI Chatbot Ecosystem

Xingyi Wang, Xiaozheng Wang, Sunyup Park

Building Appropriate Mental Models: What Users Know and Want to Know about an Agentic AI Chatbot

Michelle Brachman, Siya Kunde, Sarah Miller

To Rely or Not to Rely? Evaluating Interventions for Appropriate Reliance on Large Language Models

Jessica Y Bo, Sophia Wan, Ashton Anderson

Emerging Data Practices: Data Work in the Era of Large Language Models

Adriana Alvarado Garcia, Heloisa Candello, Karla Badillo-Urquiola

Think Together and Work Better: Combining Humans' and LLMs' Think-Aloud Outcomes for Effective Text Evaluation

SeongYeub Chu, JongWoo Kim, Mun Yong Yi

Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant

Gaole He, Gianluca Demartini, Ujwal Gadiraju

Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance

Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein

Generative AI in Documentary Photography: Exploring Opportunities and Challenges for Visual Storytelling

Lenny Martinez, Baptiste Caramiaux, Sarah Fdili Alaoui

Mind the Gap! Choice Independence in Using Multilingual LLMs for Persuasive Co-Writing Tasks in Different Languages

Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju

Understanding the Dynamics in Deploying AI-Based Content Creation Support Tools in Broadcasting Systems - Benefits, Challenges, and Directions

Joon Gi Chung, Soongi Hong, Junho Choi

Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies

Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao