超越人口数量与人力资本：有效认知人口作为AI时代规划的可分解容量单位
Beyond headcount and human capital: The Effective Cognitive Population as a decomposable capacity unit for AI-era planning
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中文总结 AI 辅助
该研究提出有效认知人口（ECP）这一可分解容量单位，结合HCI+与IMF AI准备度指数，能提升对144国总产出的解释力，为AI时代国家规划提供新工具。
中文摘要 AI 辅助
国家规划将人口、人力资本与人工智能准备度分别纳入不同核算体系。人口统计已从人口数量发展到经技能调整的存量核算，且仍在讨论技能建模后年龄结构的保留程度，但现有单位均未涵盖准备度转化为生产能力的条件。本研究引入有效认知人口（Effective Cognitive Population, ECP），这是一个可分解的单位，它根据人口的能力以及能力部署的条件对人口进行加权，以世界银行人力资本指数+（Human Capital Index Plus, HCI+）和国际货币基金组织（IMF）人工智能准备度指数的非重叠维度为锚定。该架构原则上具有可移植性，此处测试的案例为人工智能，其已有公开的准备度指数。针对144个国家，HCI+成为生产力水平，AI机会使用数字基础设施与创新整合，转化治理使用监管与伦理，基准为ECP = N H(1 + AC)。在相同人口基数下，对比2024年总产出，ECP将判定系数R²从经HCI+调整存量的0.849提升至0.882，将留一法交叉验证的均方根误差（RMSE）从0.723降至0.641，劳动年龄人口对比结果一致，且自举法（bootstrap）区间不包含零。144个国家中有89个国家的排名较人口数量至少变动10位，主要源于人力资本调整本身。结果在不同分母、版本、聚合形式及27规则多元宇宙中均保持稳定。A与C的直接交互未得到统计支持，因此该结合是一项规划规则而非因果互补性。ECP是一个诊断性核算体系，其范围不包含人口衰退预测与AI因果生产力效应估计。
英文摘要
National planning counts population, human capital, and artificial-intelligence preparedness in separate ledgers. Demographic accounting has advanced from headcount to skills-adjusted stocks and still debates how much age structure retains once skills are modeled, yet no existing unit carries the conditions under which preparedness becomes productive capacity. This study introduces the Effective Cognitive Population (ECP), a decomposable unit that weights population by capability and by the conditions under which capability is deployed, anchored to the World Bank Human Capital Index Plus (HCI+) and the non-overlapping dimensions of the IMF AI Preparedness Index. The architecture is portable in principle; the case tested here is artificial intelligence, which has a published preparedness index. For 144 countries, HCI+ becomes a productivity level, AI opportunity uses digital infrastructure and innovation integration, conversion governance uses regulation and ethics, and the benchmark is ECP = N H(1 + AC). Against 2024 total output on identical population bases, ECP raises criterion R-squared from 0.849 for the HCI+-adjusted stock to 0.882 and lowers leave-one-country-out RMSE from 0.723 to 0.641, with the working-age comparison identical and bootstrap intervals excluding zero. Eighty-nine of 144 countries move at least ten rank positions from headcount, mostly through the human-capital adjustment itself. Results are stable across denominators, vintages, aggregation forms, and a 27-rule multiverse. The direct A by C interaction is not statistically supported, so the conjunction is a planning rule rather than causal complementarity. ECP is a diagnostic ledger whose scope excludes forecasts of population decline and estimates of AI's causal productivity effect.
