Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2025

Abstract

Traditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address this, we incorporate an adversarial mechanic in the design of the dialogue-based serious game Cracking Aegis. Leveraging LLMs to simulate natural interactions, the game challenges players to impersonate characters and extract sensitive information from an AI agent, Aegis. A user study (n=22) revealed that players employed diverse deceptive linguistic strategies, including storytelling and emotional rapport, to manipulate Aegis. After playing, players reported connecting in-game scenarios with real-world privacy vulnerabilities, such as phishing and impersonation, and expressed intentions to strengthen privacy control, such as avoiding oversharing personal information with AI systems. This work highlights the potential of LLMs to simulate complex relational interactions in serious games, while demonstrating how an adversarial game strategy provides unique insights for designs for social good, particularly privacy protection.

Keywords

Serious games, LLMs, Privacy education

Discipline

Graphics and Human Computer Interfaces

Research Areas

Information Systems and Management

Areas of Excellence

Digital transformation

Publication

DIS '25: Proceedings of the 2025 ACM Designing Interactive Systems Conference, Madeira, Portugal, July 5-9

First Page

639

Last Page

662

Identifier

10.1145/3715336.37358

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3715336.37358

Download

Share

COinS