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Linguistic alignment with an artificial agent: A commentary and re-analysis.

Simone Gastaldon1, Giulia Calignano2

  • 1Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padua, Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Padua, Italy.

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Summary

This study re-analyzed data on conceptual alignment with a social robot, finding that aligning with category labels is strategic, not automatic. Limited generalizability suggests individual task strategies, not genuine alignment.

Keywords:
AutomaticityJoint picture namingLinguistic alignmentOpen scienceResponse times

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Area of Science:

  • Cognitive Psychology
  • Human-Robot Interaction
  • Linguistics

Background:

  • Cirillo et al. (2022) suggested automatic conceptual alignment in joint picture naming with a social robot based on response proportions.
  • Their study examined adaptation to the robot's lexical choices, specifically category vs. basic names.
  • This work provides a commentary and complementary analysis of the existing dataset.

Purpose of the Study:

  • To conduct a complementary analysis of conceptual alignment using response times (RTs) as a measure of cognitive processing.
  • To investigate the automaticity versus strategic nature of alignment in a joint picture naming task with a social robot.
  • To assess the generalizability of observed alignment effects.

Main Methods:

  • Re-analysis of the openly available dataset from Cirillo et al. (2022).
  • Employed a multiverse approach focusing on response times (RTs).
  • Conducted comprehensive visual exploration of response proportions and leave-one-out robustness checks.

Main Results:

  • Alignment in the Category condition (superordinate label) correlated with longer RTs and greater variability, suggesting strategic processing.
  • Alignment in the Basic condition showed shorter RTs and reduced variability, consistent with the basic-level advantage.
  • Alignment effects were primarily observed in specific semantic categories and for low-frequency or novel stimuli, indicating limited generalizability.

Conclusions:

  • Findings support the view that aligning with category labels in this task is a strategic, effortful process, not an automatic one.
  • The limited generalizability suggests that observed effects may reflect individual task strategies rather than true linguistic alignment.
  • Recommends future research directions for linguistic alignment, emphasizing Open Science principles.