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Related Experiment Video

Updated: May 31, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Reported trust varies with graded value alignment in AI-attributed economic-environmental choices.

Lidan Cui1,2, Lingyun Sun2, Guibing He3

  • 1Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, 310058, China.

Scientific Reports
|May 28, 2026
PubMed
Summary
This summary is machine-generated.

As artificial intelligence (AI) advisors make value-based decisions, users assess alignment with their priorities. Closer alignment between AI choices and user values significantly increases trust in AI systems.

Related Experiment Videos

Last Updated: May 31, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Area of Science:

  • Human-computer interaction
  • Artificial intelligence ethics
  • Decision science

Background:

  • Artificial intelligence (AI) systems are increasingly involved in decisions with ethical implications.
  • Understanding how users perceive and trust AI based on value alignment is crucial.
  • Existing theories suggest value similarity fosters trust, but the impact of graded alignment needs further investigation.

Purpose of the Study:

  • To investigate how objectively measured, graded value alignment influences user trust in AI decision-making.
  • To examine the relationship between perceived value alignment and self-reported trust in AI.
  • To explore the effect of decision orientation (economy vs. environment) on trust.

Main Methods:

  • A controlled economic-environmental trade-off task was conducted with 250 participants.
  • Participants' subjective equivalence points were calibrated using matching and titration tasks.
  • Participants observed AI choices varying in objective value alignment and decision orientation, then reported trust.

Main Results:

  • Self-reported trust in the AI advisor increased monotonically as AI choices became more aligned with participants' calibrated trade-off points.
  • Perceived value alignment also increased with objective alignment and was strongly correlated with trust.
  • A slight, less consistent trust advantage was observed for environment-leaning AI choices.

Conclusions:

  • Objective value alignment serves as a graded cue influencing user trust in AI decision support.
  • Perceived value alignment is closely linked to trust, highlighting its importance in human-AI interaction.
  • The study provides empirical evidence for the graded nature of trust formation in AI based on value congruence.