Reciprocity and alignment: Quantifying coupling in dynamic interactions

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Guillaume Dumas - , University of Montreal, Mila - Quebec Artificial Intelligence Institute (Author)
  • Merle T. Fairhurst - , Bundeswehr University of Munich, Ludwig Maximilian University of Munich (Author)

Abstract

Recent accounts of social cognition focus on how we do things together, suggesting that becoming aligned relies on a reciprocal exchange of information. The next step is to develop richer computational methods that quantify the degree of coupling and describe the nature of the information exchange. We put forward a definition of coupling, comparing it to related terminology and detail, available computational methods and the level of organization to which they pertain, presenting them as a hierarchy from weakest to richest forms of coupling. The rationale is that a temporally coherent link between two dynamical systems at the lowest level of organization sustains mutual adaptation and alignment at the highest level. Postulating that when we do things together, we do so dynamically over time and we argue that to determine and measure instances of true reciprocity in social exchanges is key. Along with this computationally rich definition of coupling, we present challenges for the field to be tackled by a diverse community working towards a dynamic account of social cognition.

Details

Original languageEnglish
Article number210138
JournalRoyal Society open science
Volume8
Issue number5
Publication statusPublished - May 2021
Peer-reviewedYes
Externally publishedYes

External IDs

ORCID /0000-0001-6540-5891/work/150883500

Keywords

ASJC Scopus subject areas

Keywords

  • alignment, coupling, multi-scale dynamics, reciprocity, social cognition