helpResearch questionTrust, Transparency, and Response Latency Design
How can users effectively detect and reduce leakage of sensitive personal information when interacting with LLM-driven chatbots?Direction: Agents, Robotics, and Social Interaction
Trust, Transparency, and Response Latency Design
Stats are based on currently indexed question data; missing sources remain visible.
39
items
10
sources
2025
latest
All questions
39 items
helpResearch questionTrust, Transparency, and Response Latency Design
Can small language models run locally on user devices to provide efficient privacy control without relying on cloud computing?helpResearch questionTrust, Transparency, and Response Latency Design
How do replacement and abstraction de-identification methods compare in efficiency and user satisfaction across contexts?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users easily leak sensitive personal information when interacting with chatbots but lack convenient, effective privacy protection tools.helpResearch questionTrust, Transparency, and Response Latency Design
What behaviors and motivations do humans exhibit when interacting with large-scale soft robots?helpResearch questionTrust, Transparency, and Response Latency Design
How do biomimetic design and gamified interaction enhance trust and emotional connection with soft robots?helpResearch questionTrust, Transparency, and Response Latency Design
What new application scenarios can large-scale soft robots provide in public spaces?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Public spaces lack natural, safe, and engaging human-robot interaction.helpResearch questionTrust, Transparency, and Response Latency Design
Can mimicking human typing behaviors such as hesitation and self-correction improve chat agent naturalness and credibility?helpResearch questionTrust, Transparency, and Response Latency Design
What are users' perceptions and preferences regarding different types of chat agent typing behaviors (hesitation, self-correction)?helpResearch questionTrust, Transparency, and Response Latency Design
How do chat agents with adjustable typing behaviors affect user engagement and interaction duration?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Chatbots appear inhuman and unnatural because they generate responses too quickly.helpResearch questionTrust, Transparency, and Response Latency Design
How does response time affect users' trust in chatbots, perceived transparency, and social presence?CUI '24Explaining Delays: How to Provide Reasonable Explanations for Chatbot Response Times to Influence User Trust
helpResearch questionTrust, Transparency, and Response Latency Design
How does providing reasonable explanations for chatbot response time affect transparency and user trust?CUI '24Explaining Delays: How to Provide Reasonable Explanations for Chatbot Response Times to Influence User Trust
lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users lack trust because the chatbot's information generation process is opaque.CUI '24Explaining Delays: How to Provide Reasonable Explanations for Chatbot Response Times to Influence User Trust
helpResearch questionTrust, Transparency, and Response Latency Design
What deficiencies exist in current large language models (LLMs) and conversational agents (CAs) when expressing empathy?helpResearch questionTrust, Transparency, and Response Latency Design
How can interaction mechanisms of human-human empathy be distinguished from human-machine empathy?helpResearch questionTrust, Transparency, and Response Latency Design
How effective is using NLP empathy classifiers to evaluate machine empathy performance?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users often feel that empathy expressed by robots lacks depth and may even cause harm.helpResearch questionTrust, Transparency, and Response Latency Design
How do response variability (dynamic delays and varied replies) and reply suggestion buttons respectively affect users' acceptance of chatbot recommendations?helpResearch questionTrust, Transparency, and Response Latency Design
In diverse task scenarios, how can chatbot design features such as reply suggestion buttons improve user task efficiency and accuracy?helpResearch questionTrust, Transparency, and Response Latency Design
Do chatbot design features such as response variability induce cognitive biases in users?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users may distrust chatbot recommendations and experience low efficiency in multitask scenarios.helpResearch questionTrust, Transparency, and Response Latency Design
How can the appropriateness of LLM-based chatbot responses in specific conversational contexts be evaluated and explained?CUI '23Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
helpResearch questionTrust, Transparency, and Response Latency Design
Is there a highly explainable chatbot debugging framework for non-technical designers?CUI '23Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
helpResearch questionTrust, Transparency, and Response Latency Design
How can dialogue act (DA) modeling be used to systematically evaluate and explain inappropriate robot responses?CUI '23Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
lightbulbPractical problemTrust, Transparency, and Response Latency Design
Chatbot replies often appear correct yet contextually inappropriate, making them difficult to debug.CUI '23Democratizing Chatbot Debugging: A Computational Framework for Evaluating and Explaining Inappropriate Chatbot Responses
helpResearch questionTrust, Transparency, and Response Latency Design
How do linguistic features in dialogue architecture affect user perceptions of conversational agents?helpResearch questionTrust, Transparency, and Response Latency Design
Which aspects of user perception (e.g., interactivity, competence) are associated with specific dialogue architecture elements?helpResearch questionTrust, Transparency, and Response Latency Design
What underexplored factors must be considered when designing conversational architectures that promote trust and utility?lightbulbPractical problemTrust, Transparency, and Response Latency Design
User perceptions of conversational agents often diverge from design expectations, affecting the user experience.helpResearch questionTrust, Transparency, and Response Latency Design
How can social bots on social media intervene in misinformation spread in a friendly manner?CUI '21Agents for Fighting Misinformation Spread on Twitter: Design Challenges
helpResearch questionTrust, Transparency, and Response Latency Design
How can conversational agents with natural language explanation capabilities help users improve media literacy?CUI '21Agents for Fighting Misinformation Spread on Twitter: Design Challenges
helpResearch questionTrust, Transparency, and Response Latency Design
Which information credibility indicators (e.g., source or content consistency) do users prefer?CUI '21Agents for Fighting Misinformation Spread on Twitter: Design Challenges
lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users struggle to identify the sources and credibility of misinformation when receiving social media information.CUI '21Agents for Fighting Misinformation Spread on Twitter: Design Challenges
helpResearch questionTrust, Transparency, and Response Latency Design
How do users judge whether Twitter accounts are human or social bots based on viewpoint alignment?helpResearch questionTrust, Transparency, and Response Latency Design
Does viewpoint alignment affect judgment of accounts explicitly labeled as human or bot?helpResearch questionTrust, Transparency, and Response Latency Design
Does trust evaluation (credibility) mediate the relationship between viewpoint alignment and account identification?lightbulbPractical problemTrust, Transparency, and Response Latency Design
Users cannot accurately identify social bots, affecting judgments of social media credibility.Related papers
CHI 2025
Rescriber: Smaller-LLM-Powered User-Led Data Minimization for LLM-Based Chatbots
Jijie Zhou, Eryue Xu, Yaoyao Wu
CHI 2025
Encounter with the Giants: Understanding Interaction with Large-scale Inflatable Soft Robots
Bijetri Biswas Biswas, Emma Powell, Robert Nixdorf
CUI 2024
Beyond Words: Infusing Conversational Agents with Human-like Typing Behaviors
Jijie Zhou, Yuhan Hu
CHI 2024
The Illusion of Empathy? Notes on Displays of Emotion in Human-Computer Interaction
Andrea Cuadra, Maria Wang, Lynn Andrea Stein
CUI 2023
Chatbots as Advisers: the Effects of Response Variability and Reply Suggestion Buttons
Federico Milana, Enrico Costanza, Joel E Fischer
CUI 2023
The Bot on Speaking Terms: The Effects of Conversation Architecture on Perceptions of Conversational Agents
Christina Ziying Wei, Young-Ho Kim, Anastasia Kuzminykh
CHI 2021
Disagree? You Must Be a Bot! How Beliefs Shape Twitter Profile Perceptions
Magdalena Wischnewski, Rebecca Bernemann, Thao Ngo
Adjacent categories
Agents, Robotics, and Social Interaction
Conversational Agent and Chatbot Design
87 items
Agents, Robotics, and Social Interaction
Mental Health, Emotion Regulation, and Behavior Change Support
84 items
Agents, Robotics, and Social Interaction
Conversational Agent Persona, Personality, and Social Trait Design
68 items
Agents, Robotics, and Social Interaction
Social Agent Emotional and Nonverbal Expression
60 items
Agents, Robotics, and Social Interaction
Gaze and Attention Guidance in Remote Collaboration
45 items
Agents, Robotics, and Social Interaction
Public Space, Ethics, and Inclusive HRI
43 items
Agents, Robotics, and Social Interaction
Social, Service, and Care Robot Interaction Design
37 items
Agents, Robotics, and Social Interaction
Emotion, Trust, and Social Interaction
36 items