Arknights: Playable Explanation and Player Agency under Opacity
Shuai Guo

TL;DR
This paper explores how digital games like Arknights serve as explainable interfaces, shifting player agency from control to interpretive reasoning due to incomplete and delayed AI explanations.
Contribution
It introduces the concept of explanatory agency, analyzing how game interfaces mediate understanding and decision-making under AI opacity.
Findings
PRTS provides usable but unverifiable explanations
Player agency shifts from control to interpretive reasoning
Incomplete info and delayed feedback affect trust and understanding
Abstract
As generative AI increasingly mediates learning and decision-making, users often act effectively while struggling to interpret how system outcomes are produced. While Explainable Artificial Intelligence (XAI) research has primarily addressed this problem through transparency and visualization, less attention has been paid to how explanation is constructed through interaction. This paper examines digital games as explainable interfaces by analyzing how explanation can be configured as a playable process. Using Arknights as a case study, the paper conducts a qualitative close reading and interface analysis of the diegetic AI system PRTS, focusing on the implied player. The analysis shows that PRTS provides usable but unverifiable explanations: sufficient to initiate action, yet insufficient to stabilize causal understanding. Through incomplete information, delayed feedback, and narrative…
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