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Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions.

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Summary
This summary is machine-generated.

This study explores how inner speech, a human cognitive process, could enhance trust in human-robot interactions. Implementing robot inner speech may boost transparency and anthropomorphism, influencing user confidence.

Keywords:
anthropomorphismautomationhuman-automation interactionhuman-robot interactioninner speechrobottrust

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Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Robotics

Background:

  • Inner speech is a fundamental cognitive process crucial for self-regulation and self-awareness in humans.
  • Recent advancements in machine consciousness enable computational models for robot speech, including inner speech capabilities.
  • Human-automation interaction is a growing field where trust is a critical factor.

Purpose of the Study:

  • To discuss the potential impact of inner speech on trust in human-automation interaction.
  • To explore how implementing inner speech in robots could influence user perception and trust.
  • To examine the relationship between robot inner speech, transparency, and anthropomorphism.

Main Methods:

  • Conceptual analysis and discussion of existing research in cognitive science, AI, and human-robot interaction.
  • Exploration of computational models for implementing inner speech in robotic systems.
  • Theoretical framework development linking inner speech to trust dynamics.

Main Results:

  • Robot inner speech presents a novel mechanism for potentially increasing trust in human-automation interactions.
  • Implementing inner speech in robots may enhance perceived transparency by simulating internal cognitive processes.
  • Increased anthropomorphism resulting from robot inner speech could significantly influence user trust and acceptance.

Conclusions:

  • Inner speech in robots is a promising area for future research in human-automation trust.
  • Further investigation is needed to empirically validate the effects of robot inner speech on trust, transparency, and anthropomorphism.
  • This concept could lead to more intuitive and trustworthy human-robot collaboration.