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English(EN) Births are difficult to predict even with rich survey and full-population register data

AI模型难以预测生育等人类生命事件

最近一项发表在arXiv上的研究探讨了重大人生事件的可预测性,特别是关注在三年内预测生育。该研究涉及147名参与者,他们使用了包括逻辑回归、大型语言模型和Transformer在内的各种方法来预测荷兰18-45岁居民的生育情况。虽然预测显示出中等准确性,但先进模型并未显著优于经典模型,而数据来源(调查与人口登记)对性能的影响有限。研究还估计了一个理论上的预测上限,表明生物过程中的固有随机性和未建模因素导致了精确预测个体人生事件的困难。 AI

影响 展示了当前AI在预测复杂人类行为方面的局限性,强调了随机性和数据质量的作用。

排序理由 该集群包含一篇详细介绍研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI模型难以预测生育等人类生命事件

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该集群包含一篇详细介绍研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Elizaveta Sivak, Emily M. Cantrell, Thomas Emery, Javier Garcia-Bernardo, Flavio Hafner, Kasia Karpinska, Malte L\"uken, Adrienne Mendrik, Joris Mulder, Hanzhang Ren, Varun Satish, Mark Verhagen, Angelica M. Maineri, Paulina Pankowska, Jasmin Abdel Ghany… ·

    即使拥有丰富的调查和全人口登记数据,生育率也难以预测

    arXiv:2609.01194v1 Announce Type: new Abstract: Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child within three years - through a near-ideal setting for…