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Related Experiment Video

Updated: Nov 29, 2025

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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Thinking about Trust: People, Process, and Place.

Stephen Marsh1, Tosan Atele-Williams1, Anirban Basu2

  • 1Faculty of Business and IT, Ontario Tech University, Oshawa, ON L1G 0C5, Canada.

Patterns (New York, N.Y.)
|November 18, 2020
PubMed
Summary
This summary is machine-generated.

This paper explores the concept of trust, examining how it can be measured, compared, and rated across various entities like data, artificial intelligence, and humans. It delves into trust systems, empowerment, models, and applications, highlighting the inherent worth of trust.

Keywords:
artificial intelligencedatapeopletrusttrust empowermenttrustworthiness

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Area of Science:

  • Trust and artificial intelligence
  • Human-computer interaction
  • Data science ethics

Background:

  • Trust is a fundamental concept impacting interactions across diverse entities.
  • Existing research often focuses on specific trust applications rather than a holistic view.
  • Understanding trust is crucial for developing reliable AI and data systems.

Purpose of the Study:

  • To explore the multifaceted nature of trust.
  • To investigate the measurability, comparability, and rating of trust.
  • To examine trust systems, empowerment, models, and applications.

Main Methods:

  • Conceptual analysis of trust from various perspectives.
  • Exploration of trust measurement and comparison frameworks.
  • Review of trust systems, empowerment strategies, and model creation.

Main Results:

  • Trust can be conceptualized and potentially measured across data, AI, and human systems.
  • Trust empowerment offers a more effective approach than trust enforcement.
  • Trust models and applications are diverse and valuable.

Conclusions:

  • Trust is a valuable and measurable construct applicable to artificial intelligence, data, and human interactions.
  • Focusing on trust empowerment is key for building reliable systems.
  • Further research into trust models and applications is warranted.