arXiv 2006.108082020-06-18cs.HC

数据驱动的游戏开发：伦理考量

Data-Driven Game Development: Ethical Considerations

Magy Seif El-Nasr, Erica Kleinman

发表信息：: Foundations of Digital Games 2020

摘要：

近年来，游戏行业已经朝着数据驱动的开发方向迈出了一大步，使用数据分析和玩家建模来为设计决策提供信息。数据驱动技术是有益的，因为它们允许大规模研究玩家行为，使其非常适用于现代数字游戏开发。然而，随着这种向数据驱动决策的转变，出现了一些道德问题。先前在玩家建模以及人工智能和机器学习领域的工作已经证明了算法决策可能由于数据或算法偏见或缺乏特定群体的数据而存在缺陷的几种方式。此外，黑盒算法由于缺乏基于数据开发的结果或模型的可解释性和透明度而产生信任问题，需要盲目相信结果。在这份立场文件中，我们讨论了在开发周期中影响游戏数据使用的几个因素。除了以前的工作提出的问题，我们还提出了一些问题，算法边缘化某些球员群体和缺陷，在由此产生的模型，由于他们无法推理的情况下影响球员的决定因素。此外，我们还概述了一些旨在解决这些问题的工作，并确定了一些有关伦理和游戏数据科学的开放问题。

英文摘要：

In recent years, the games industry has made a major move towards data-driven development, using data analytics and player modeling to inform design decisions. Data-driven techniques are beneficial as they allow for the study of player behavior at scale, making them very applicable to modern digital game development. However, with this move towards data driven decision-making comes a number of ethical concerns. Previous work in player modeling as well as work in the fields of AI and machine learning have demonstrated several ways in which algorithmic decision-making can be flawed due to data or algorithmic bias or lack of data from specific groups. Further, black box algorithms create a trust problem due to lack of interpretability and transparency of the results or models developed based on the data, requiring blind faith in the results. In this position paper, we discuss several factors affecting the use of game data in the development cycle. In addition to issues raised by previous work, we also raise issues with algorithms marginalizing certain player groups and flaws in the resulting models due to their inability to reason about situational factors affecting players' decisions. Further, we outline some work that seeks to address these problems and identify some open problems concerning ethics and game data science.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

摘要：

英文摘要：

相关论文