Computational Sociology of Humans and Machines; Conflict and Collaboration

TL;DR

This paper explores the complex dynamics of conflict and collaboration in large-scale human-machine systems, analyzing interaction patterns, the role of algorithmic agents, and proposing policies for improved synergy.

Contribution

It provides a detailed analysis of interaction microstructures and the dual role of bots in human-machine collaboration, offering new insights and policy recommendations.

Findings

Identifies recurring interaction patterns like serial attacks and revenge.

Highlights the dual role of algorithmic agents in collaboration and conflict.

Recommends transparency and cultural sensitivity policies.

Abstract

This Chapter examines the dynamics of conflict and collaboration in human-machine systems, with a particular focus on large-scale, internet-based collaborative platforms. While these platforms represent successful examples of collective knowledge production, they are also sites of significant conflict, as diverse participants with differing intentions and perspectives interact. The analysis identifies recurring patterns of interaction, including serial attacks, reciprocal revenge, and third-party interventions. These microstructures reveal the role of experience, cultural differences, and topic sensitivity in shaping human-human, human-machine, and machine-machine interactions. The chapter further investigates the role of algorithmic agents and bots, highlighting their dual nature: they enhance collaboration by automating tasks but can also contribute to persistent conflicts with both humans and other machines. We conclude with policy recommendations that emphasize transparency, balance, cultural sensitivity, and governance to maximize the benefits of human-machine synergy while minimizing potential detriments.