Brief Introduction

In today’s digital society, online chaos has emerged as a persistent and multifaceted challenge with profound impacts on social welfare. Manifestations such as fake information, deceptive online reviews, hate speech, algorithmic manipulation, and information overload have increasingly eroded trust and distorted individual and organizational decision-making. In e-commerce, fake reviews severely damage the credibility of online product reviews and have a negative impact on stakeholders. These forms of online chaos reveal structural vulnerabilities within contemporary digital ecosystems, where information abundance, algorithmic curation, and asymmetric incentives jointly contribute to the erosion of social trust and welfare.

The rapid proliferation of generative AI technologies (GenAI) has further intensified this phenomenon by introducing a dual and inherently tension-laden role in managing online chaos. On one hand, GenAI-powered tools, such as advanced detection algorithms and automated fact-checking systems, offer powerful capabilities to identify, analyze, and counter online chaos. On the other hand, the advancements in GenAI have enabled malicious actors to generate increasingly sophisticated deceptive content, including hyperrealistic deepfakes, GenAI-generated texts, and manipulated media, which pose greater difficulties in detection and verification. This duality underscores the need to move beyond technologically deterministic views and instead adopt a more nuanced understanding of how GenAI reshapes the production, diffusion, and governance of online disorder.

This track aims to contribute to the comprehension of the opportunities and challenges related to Gen in managing diverse forms of online chaos. We welcome research that utilizes the mainstream scientific methods employed in business studies, including conceptual, empirical, experimental, analytical model, or mixed methods.

Topics

1. The economics of AI-generated chaos: incentives, markets, and impacts
2. Users’ abilities to identify fake information with GenAI assistance
3. Impacts of various GenAI agents, including AIGC and AIGS
4. User behavior and resilience in GenAI-polluted information environments
5. Cross-platform or cross-culture analysis of Gen’s impact
6. Misinformation, deepfakes, and the erosion of trust
7. GenAI for managing online chaos: new paradigms and impacts