当社会开始“看见”国家:AI驱动的权力透明化革命
几个世纪以来,国家的形成与强化伴随着其‘使社会清晰化’的能力——通过统计、档案、法律将纷繁复杂的社会纳入可管理的范畴。如今,AI正在赋予社会前所未有的能力,去解读、分析、监督那台曾经唯一拥有全景视角的机器。这不仅仅是技术的进步,这是一场关于‘谁有权看见谁’的权力革命。
核心观点:以AI为代表的信息处理能力平民化,正在引发一场深刻的政治权力结构变迁:传统上由政府单方面对社会进行‘透视’与管理的‘利维坦之眼’模式,正在被社会反向‘透视’政府的‘数字复眼’模式所挑战,这既可能赋能民主问责,也潜藏着民粹操纵与隐私侵蚀的双重风险。
政治学家詹姆斯·C·斯科特在其经典著作《国家的视角》中揭示了一个核心命题:现代国家的构建与运作,依赖于其‘使社会清晰化’的能力。从人口普查、土地测量、标准化语言到城市规划,国家通过一系列技术手段,将复杂、凌乱、多维的社会现实,简化为清晰、统一、可计量、可管理的数据点。这双‘利维坦之眼’是国家权力得以实施的基础,但也天然地制造了一种信息不对称:国家能看到社会,而社会却难以看清国家的内部运作。这种不对称是传统治理模式的基石,也是问责制始终面临的根本性挑战。
如今,材料中AI研究者提出的愿景,正在动摇这一基石。他指出,政府问责的瓶颈从来不是信息获取——各国政府事实上产生了海量的数据,如法律条文、预算案、听证会记录、采购合同、游说披露信息等——而是信息处理能力。理解一份4000页的综合法案,追踪某项条款在立法过程中的每一次修改及其背后的利益关联,分析特定议员投票记录与其竞选资金源的隐秘模式,这些都需要极高的时间成本、专业知识和分析能力。历史上,只有极少数的‘看门人’——如调查记者、专业智库、利益集团的分析师——能够部分地承担起这种‘反向透视’的工作。而AI,特别是大型语言模型和多模态分析工具,正在以前所未有的规模降低这种能力门槛。
这意味着什么?这意味着‘利维坦之眼’的垄断正在被打破。社会不再仅仅是被观察、被分类、被管理的客体,它正在获得一双甚至无数双‘数字复眼’。任何一个公民团体、一家媒体、甚至一个感兴趣的个体,理论上都可以利用开源工具,对政府产生的海量数据进行深度挖掘。他们可以构建法案修改的自动追踪器,可视化特殊利益集团与立法成果之间的网络,实时分析政府开支中的异常模式,或者将冗长的市政会议记录转化为可搜索、可摘要、可质疑的知识库。这种‘反向透视’的能力,正在将传统上封闭在政治黑箱中的许多过程,暴露在数字化的阳光之下。
其潜在的民主赋能效应是巨大的。首先,它可能显著提高政治腐败和不当行为的发现概率与成本。当分析不再是少数专家的专利时,隐蔽的勾连更难藏身。其次,它能促进更精细、更基于事实的公共讨论。选民可以超越口号和意识形态标签,去具体考察代表们的实际投票与利益关联。第三,它可能催生新的公民参与形式。社区可以更有效地监督本地政府的 zoning(分区)决策、教育预算分配或警务数据,推动更贴近民意的治理。这实质上是在技术层面,为‘知情同意’这一民主基本原则提供了新的实现路径。社会不再仅仅是被动地接受治理结果,而是能更主动地理解、甚至介入治理过程。
然而,与所有强大的技术一样,这幅乐观图景的反面同样清晰且危险。首先,是‘武器化的透明’。AI驱动的分析工具本身并无立场,但其使用者和解读方式却充满偏见。同样的数据,可以被不同阵营加工成完全对立、却都看似‘有数据支撑’的叙事,进一步极化舆论。深度伪造技术甚至可能制造出完全虚假的‘证据’,使信任体系崩塌。其次,是新的数字鸿沟。拥有技术资源、数据科学家的政治行动委员会或大型媒体,与普通公民之间的分析能力差距可能依然巨大,甚至因技术而扩大,导致监督权被新的技术精英所垄断。第三,是隐私的噩梦。为了‘透视’政府,社会可能需要更全面地数字化自身——更多的会议直播、更详细的官员行程公开、更广泛的通讯记录归档(在合规前提下)。这本身就会创造出一个全景监控社会的副产品,而监控者可能不仅是国家,还包括彼此敌对的公民团体或商业实体。
更深层次的悖论在于:为了更有效地监督国家这头‘利维坦’,社会是否必须首先将自己转化为一个高度数字化、全息透明的‘数字利维坦’?监督所需的‘清晰化’需求,与社会本身的多元、模糊、隐私保护需求之间,存在着永恒的张力。AI放大了前者的力量,但未必能妥善解决后者。
此外,政府的应对策略也将决定这场革命的最终形态。它们可能拥抱透明,开放更多机器可读的数据接口,甚至主动利用AI向公众解释政策。它们也可能走向反制,通过信息过载(释放更多无意义的原始数据淹没有效信息)、复杂性加密(将决策过程包装得更加技术化、难以通俗理解)、或直接立法限制某些数据的使用方式,来维持某种程度的信息黑箱。权力从来不会心甘情愿地接受全方位的透视。
因此,我们面临的并非一条单向通往光明未来的坦途。AI带来的‘反向透视’能力,正在打开一个充满可能性的潘多拉魔盒。它既可能成为深化民主问责、激发公民智慧的利器,也可能沦为制造混乱、加深分裂、侵蚀隐私的凶器。其最终走向,不取决于技术本身,而取决于我们如何设计使用它的规则、如何培育解读它的素养、以及如何在提升透明度的同时,守护社会免于被过度‘清晰化’而失去必要的模糊空间与个人尊严。这场‘看见’与‘被看见’的博弈,将是数字时代政治形态定义的核心战场之一。我们需要的不仅是对技术的乐观,更需要对权力本质的清醒,以及对复杂性的敬畏。
如果把这个判断再往前推一步,真正重要的不是 RT by @paulg: A new…、《无限暖暖》2.5版本套装PV | 栖…、I was recommended @… 本身,而是它们共同暴露出的分配逻辑。 x、bilibili 在同一轮里把注意力推向同一问题,通常意味着这个主题正在从圈层内部经验,转向更可共享的公共议题。 这也是为什么这种内容值得写成长文:短帖只负责提醒你“这里有事发生”,但只有长文才能把背景、代价、误判空间和后续影响放到同一张桌面上。 换句话说,以AI为代表的信息处理能力平民化,正在引发一场深刻的政治权力结构变迁:传统上由政府单方面对社会进行‘透视’与管理的‘利维坦之眼’模式,正在被社会反向‘透视’政府的‘数字复眼’模式所挑战,这既可能赋能民主问责,也潜藏着民粹操纵与隐私侵蚀的双重风险。 之所以重要,不是因为它看上去新,而是因为它会重新定义用户接下来应该如何理解这一类内容。
参考来源
- RT by @paulg: A new paper in @Nature from David Reich, @aliakbari23 and colleagues breaks the conventional understanding of recent human evolution. The field believed that strong selection in the recent past (~10,000 years) was rare, with few exceptions like the lactase persistence locus. In this paper, the authors challenge that belief, showing that we weren't looking at the problem right.
- Previous studies that looked for evidence of selection using ancient DNA addressed the problem cross-sectionally, asking if allele frequencies differed across populations more than what one would expect based on genetic drift and migration. Most arrived at the conclusion that population structure primarily explained the observed differences. Here, the authors addressed the problem longitudinally, accounting for when ancient individuals lived by explicitly modeling time as a variable in the analysis. It turns out doing it this way dramatically increases power, increasing the number of genome-wide significant selection signals by 20-fold!
- Looking at why accounting for the time variable led to such dramatic changes in results, the authors find that previous studies missed so much because selection often happened not on new variants leading to dramatic sweeps (the conventional model: new variant -> selection -> increase in frequency) but on already existing variants driven by transient environmental pressures. Many of these variants underwent reversals, selected up when a pressure existed, then purged when it disappeared or the trade-off cost became dominant. A great example is the TYK2 variant, where an allele boosting immunity was selected for thousands of years because it protected against TB, then got purged as TB endemicity declined and the autoimmune cost took over.
- The scale of what they found is striking: hundreds of loci showing strong selection in the past 10,000 years with a median selection coefficient of ~0.86%. This number is pretty big in evolutionary terms, meaning allele frequencies have been shifting by ~1% per generation in a consistent direction. Previous selection scans found a maximum of 20 loci, and this one finds hundreds. That isn't an incremental change. It fundamentally reframes our understanding of how common strong selection has been in recent human history.
- Some of the most striking findings come from polygenic selection, where hundreds of small-effect alleles were pushed in the same direction simultaneously. Polygenic scores based on large-scale GWAS of today predict recent negative selection for traits like body fat, waist circumference and schizophrenia, and positive selection for others like cognitive traits. One important caveat is that GWAS phenotypes are measured in industrialized societies today, and how well they capture what was actually being selected in ancient environments is debatable.
- For me personally, these findings have direct implications for drug discovery. When using human genetics to find drug targets, we often fixate on the benefit and risk profiles of variants visible today. But we need to be aware that a variant's benefit:harm ratio might be environmentally contingent, and could reverse when the wrong environment manifests. An evolutionary understanding of a variant's association with traits is therefore essential.
- The same logic applies, perhaps even more urgently, to embryo selection. Selecting embryos based on polygenic traits is humans making permanent, heritable decisions for their offspring with a narrow view of today's environment. The ancient DNA record now shows that cost-benefit landscapes flip over time. So, an embryo carrying man-made selections is carrying those changes into an unpredictable future environment.
- The broader takeaway is that human evolution didn't freeze in the last 10,000 years. We just lacked the tools and datasets to see its movement. The current findings are based on European populations. I am curious to see these analyses extended to other populations too, like South Asian, East Asian and African populations, which might be holding more surprises to blow our minds.
- Akbari et al. Nature 2026
- https://www.nature.com/articles/s41586-026-10358-1 - https://nitter.net/doctorveera/status/2044679999450664967#m
- 《无限暖暖》2.5版本套装PV | 栖骨生花&渡者无归 - https://www.bilibili.com/video/BV1x7oNBvEZs
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