Prejudiced Futures? Algorithmic Bias in Time Series Forecasting and Its Ethical Implications
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带偏见的未来？时间序列预测中的算法偏倚及其伦理含义
- 研究问题
- 时间序列预测系统如何通过历史数据、问题设定、代理变量和反馈机制延续不平等，又应怎样在动态环境中评价与治理偏倚？
- 方法与思路
- 作者从社会技术视角梳理预测流程中的偏倚来源，讨论因果建模、可解释系统与参与式治理，并倡议多指标和时间感知的公平评价。
- 材料陈述的贡献
- 摘要提出偏倚的社会技术解释、贯穿流程的诊断框架，以及将公平纳入制度治理和设计过程的改革建议，强调动态环境评价。
- 阅读关注点
- 应核对公平指标及其规范依据、时间变化和反馈的处理方式，并区分概念性倡议、可实施评价程序与已有验证证据。
- 阅读边界
- 这是 arXiv 预印本，不能据此确认同行评审或期刊接收；摘要未给出正式检验、数据实验或量化效果，治理建议的有效性尚未展示。
原文摘要
Time series prediction algorithms are increasingly central to decision-making in high-stakes domains such as healthcare, energy management, and economic planning. Yet, these systems often inherit and amplify biases embedded in historical data, flawed problem specifications, and socio-technical design decisions. This paper critically examines the ethical foundations and mitigation strategies for algorithmic bias in time series prediction. We outline how predictive models, particularly in temporally dynamic domains, can reproduce structural inequalities and emergent discrimination through proxy variables and feedback loops. The paper advances a threefold contribution: First, it reframes algorithmic bias as a socio-technical phenomenon rooted in normative choices and institutional constraints. Second, it offers a structured diagnosis of bias sources across the pipeline, emphasizing the need for causal modeling, interpretable systems, and inclusive design practices. Third, it advocates for structural reforms that embed fairness through participatory governance, stakeholder engagement, and legally enforceable safeguards. Special attention is given to fairness validation in dynamic environments, proposing multi-metric, temporally-aware, and context-sensitive evaluation methods. Ultimately, we call for an integrated ethics-by-design approach that positions fairness not as a trade-off against performance, but as a co-requisite of responsible innovation. This framework is essential to developing predictive systems that are not only effective and adaptive but also aligned with democratic values and social equity.