Explainable AI for Transparent Decision-Making in Game Systems
Anna Ross 2025-02-02

Explainable AI for Transparent Decision-Making in Game Systems

Thanks to Anna Ross for contributing the article "Explainable AI for Transparent Decision-Making in Game Systems".

Explainable AI for Transparent Decision-Making in Game Systems

This paper investigates the legal and ethical considerations surrounding data collection and user tracking in mobile games. The research examines how mobile game developers collect, store, and utilize player data, including behavioral data, location information, and in-app purchases, to enhance gameplay and monetization strategies. Drawing on data privacy laws such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), the study explores the compliance challenges that mobile game developers face and the ethical implications of player data usage. The paper provides a critical analysis of how developers can balance the need for data with respect for user privacy, offering guidelines for transparent data practices and ethical data management in mobile game development.

This study applies social psychology theories to understand how group identity and collective behavior are formed and manifested within multiplayer mobile games. The research investigates the ways in which players form alliances, establish group norms, and engage in cooperative or competitive behaviors. By analyzing case studies of popular multiplayer mobile games, the paper explores the role of ingroups and outgroups, social influence, and group polarization within game environments. It also examines the psychological effects of online social interaction in gaming communities, discussing how mobile games foster both prosocial behavior and toxic interactions within groups.

This systematic review examines existing literature on the effects of mobile gaming on mental health, identifying both beneficial and detrimental outcomes. It provides evidence-based recommendations for stakeholders in the gaming industry and healthcare sectors.

This research applies behavioral economics theories to the analysis of in-game purchasing behavior in mobile games, exploring how psychological factors such as loss aversion, framing effects, and the endowment effect influence players' spending decisions. The study investigates the role of game design in encouraging or discouraging spending behavior, particularly within free-to-play models that rely on microtransactions. The paper examines how developers use pricing strategies, scarcity mechanisms, and rewards to motivate players to make purchases, and how these strategies impact player satisfaction, long-term retention, and overall game profitability. The research also considers the ethical concerns associated with in-game purchases, particularly in relation to vulnerable players.

This research investigates how machine learning (ML) algorithms are used in mobile games to predict player behavior and improve game design. The study examines how game developers utilize data from players’ actions, preferences, and progress to create more personalized and engaging experiences. Drawing on predictive analytics and reinforcement learning, the paper explores how AI can optimize game content, such as dynamically adjusting difficulty levels, rewards, and narratives based on player interactions. The research also evaluates the ethical considerations surrounding data collection, privacy concerns, and algorithmic fairness in the context of player behavior prediction, offering recommendations for responsible use of AI in mobile games.

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