Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Nelson Navajas Fernández

dblp:432/6683 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0009-4298-9658ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 46% Collaborative and social computing · 46% Wearable and physiological sensing · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction
AI-mediated communication
1.012026
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement · CHI 2026
Collaborative and social computing › computer-mediated communication
interpersonal trust
1.012026
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement · CHI 2026
Human-AI interaction
trust in AI
1.012026
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement · CHI 2026
Collaborative and social computing › computer-mediated communication › virtual communication
video-mediated communication
1.012026
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement · CHI 2026
Wearable and physiological sensing
deception detection
0.312026
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement · CHI 2026

Methods — techniques the papers use, named apart from their topics

preregistered study · 1.0online experiment · 1.0
YearPublicationVenuePosition
2026 Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement
abstract
AI-based tools that mediate, enhance or generate parts of video communication may interfere with how people evaluate trustworthiness and credibility. In two preregistered online experiments (N = 2,000), we examined whether AI-mediated video retouching, background replacement and avatars affect interpersonal trust, people’s ability to detect lies and confidence in their judgments. Participants watched short videos of speakers making truthful or deceptive statements across three conditions with varying levels of AI mediation. We observed that perceived trust and confidence in judgments declined in AI-mediated videos, particularly in settings in which some participants used avatars while others did not. However, participants’ actual judgment accuracy remained unchanged, and they were no more inclined to suspect those using AI tools of lying. Our findings provide evidence against concerns that AI mediation undermines people’s ability to distinguish truth from lies, and against cue-based accounts of lie detection more generally. They highlight the importance of trustworthy AI mediation tools in contexts where not only truth, but also trust and confidence matter.
Nelson Navajas Fernández, Jeffrey T. Hancock, Maurice Jakesch
CHI1