Mihai Florin, Aleca Ofelia Ema, Iordache Daniel-Marius
Management Information Systems Department, Faculty of Accounting and Management Information Systems, Bucharest University of Economic Studies, 010552 Bucharest, Romania.
Behav Sci (Basel). 2025 Jun 4;15(6):779. doi: 10.3390/bs15060779.
Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and motivational processes, especially in relation to risk perception, decision-making, and betting persistence. Using ordinary least squares (OLS) and panel regression models applied to behavioral data from a gambling platform, we examine patterns that are consistent with increased personalization between two distinct time periods, 2016 and 2021. The datasets do not contain any direct metadata regarding AI interventions. However, we interpret changes in user behavior over time as indicative of evolving personalization dynamics within a broader technological and contextual landscape. Accordingly, our conclusions about algorithmic personalization are inferential and exploratory, drawn from temporal comparisons between 2016 and 2021. Our findings show that users receiving personalized bonuses or making early cash-out decisions tend to adjust their stake sizes and betting frequency in systematic ways, which may reflect indirect effects of technological reinforcement strategies. These behavioral patterns raise important ethical and regulatory questions, particularly regarding user autonomy, algorithmic transparency, and the protection of at-risk users. This research contributes to the literature on digital behavior influencing gambling by framing the analysis as observational and quasi-experimental and suggests that further studies use experimental and log-level data to more specifically analyze the algorithmic effects. However, no causal claims can be made about AI influence as the temporal contradictions are interpreted as broad phenomena of technological developments, since they are not measured as algorithmic interventions. Further studies should also investigate the development of predictive models aimed at countering gambling addiction; evaluate the long-term ethical implications of algorithmic personalization; and discuss potential solutions codeveloped to foster a responsible gambling climate.
人们普遍认为，算法个性化方面的技术进步会影响在线赌博平台上的用户行为。本研究探讨了这些发展，可能包括人工智能驱动的机制，如何影响认知和动机过程，特别是在风险感知、决策和投注持续性方面。我们使用应用于一个赌博平台行为数据的普通最小二乘法（OLS）和面板回归模型，研究了2016年和2021年这两个不同时间段内与个性化增强相一致的模式。数据集不包含任何关于人工智能干预的直接元数据。然而，我们将用户行为随时间的变化解释为更广泛技术和背景环境中个性化动态演变的指标。因此，我们关于算法个性化的结论是基于2016年和2021年之间的时间比较得出的推断性和探索性结论。我们的研究结果表明，获得个性化奖金或做出提前兑现决定的用户倾向于以系统的方式调整他们的赌注大小和投注频率，这可能反映了技术强化策略的间接影响。这些行为模式引发了重要的伦理和监管问题，特别是关于用户自主性、算法透明度和对有风险用户的保护。本研究通过将分析构建为观察性和准实验性研究，为影响赌博的数字行为文献做出了贡献，并建议进一步的研究使用实验性和日志级数据来更具体地分析算法效果。然而，由于时间上的矛盾被解释为技术发展的广泛现象，而非作为算法干预来衡量，因此无法对人工智能的影响做出因果论断。进一步的研究还应调查旨在对抗赌博成瘾的预测模型的发展；评估算法个性化的长期伦理影响；并讨论共同开发的潜在解决方案，以营造一个负责任的赌博环境。
