当AI成为社会的“显微镜”:一场正在发生的权力透明化革命
几个世纪以来,现代国家的形成伴随着其将社会变得“清晰可读”的能力——通过普查、地图、档案来管理和控制。然而,以ChatGPT为代表的大语言模型,正赋予普通公民一种前所未有的反向能力:以前所未有的深度和广度,去解析、监督和问责那个原本试图“看清”他们的庞然大物。这并非简单的透明度提升,而是一场静悄悄的权力结构革命。
核心观点:AI正在从根本上改变政府与社会之间的信息不对称格局,将“可读性”的权力从国家机器下放给公民个体,这不仅是技术工具的创新,更是一场深刻的政治权力再分配,其最终结果可能重塑民主社会的问责与参与模式。
在政治学和社会学经典《国家的视角》中,詹姆斯·C·斯科特深刻剖析了现代国家如何通过简化、标准化和量化,将复杂、凌乱的社会现实改造为清晰可读的“地图”,以便于管理、征税和控制。这种“可读性”是单向的,是国家看向社会的独眼视角。公民面对国家机器时,常感到的是一种巨大的、不透明的、难以理解的复杂性无力感。一份长达四千页的综合拨款法案在法律意义上是公开透明的,但对99.9%的公民而言,它无异于天书。这种信息不对称,构成了传统代议制民主中问责乏力的核心瓶颈:不是没有信息,而是信息过于庞杂,超出了普通公民甚至大多数专业人士的处理能力,只有少数精英(如调查记者、专业游说分析机构)才能在其中导航。然而,以大型语言模型为代表的AI技术,正在成为打破这一千年困局的杠杆。它并非创造了新的信息——政府的预算、法案、投票记录、游说披露、采购合同、司法文书等数据早已公开——而是革命性地降低了处理、关联和理解这些信息的智力门槛与时间成本。AI正在将“可读性”的权力,从国家和社会精英手中,部分地转移给每一个能访问互联网的公民。
这场变革的核心机制,是AI对非结构化、高维度信息的理解和推理能力的质变。过去,分析一项法案的影响,需要法律专家逐条研读;追踪一个利益集团的影响网络,需要政治学家手动梳理数万份披露文件;监督地方政府的市政合同,需要记者投入数月调查。现在,一个公民或许只需要向AI提出一系列连贯的问题:“请对比本届政府与上届政府在教育拨款上的具体变化,并指出资金流向最大的五个学区及其政治背景。”“分析这位议员过去三年的投票记录,与其在竞选时关于环保的承诺是否一致,并找出其投票立场发生转变的时间点,以及同期与其会面的游说团体。”“扫描过去一年本市所有超过一百万美元的市政合同,找出中标公司之间的关联,并评估其投标价格与市场均价的偏差。”AI可以瞬间消化TB级的数据,建立跨数据库的关联,并以人类可理解的语言呈现洞察。这不仅仅是效率的提升,更是能力的范式转移。它使得“分布式监督”成为可能:不再依赖少数中央化的监督机构,而是可以发动成千上万的公民,从各自关心的角度,对权力的运行进行显微镜式的检视。
这种“自下而上的可读性”将首先在最容易被忽视的层面产生爆炸性影响:地方政治。全国性政治有媒体聚光灯,而县市议会、学区委员会、地方规划局的决策,往往在缺乏关注的情况下进行,却直接影响居民的房产价值、子女教育和社区环境。AI工具可以使地方记者、社区组织者甚至普通居民,轻松分析市政会议纪要、追踪 zoning 法规变更、监控警力部署数据、审计学校董事会预算。一个社区可以集体使用AI工具,模拟一项新开发项目对交通、房价和公共设施的影响,从而在听证会上提出数据翔实的质询,而非仅仅表达情绪化的反对。这极大地增强了地方治理的参与度和制衡力,可能催生更接地气、更负责任的基层民主。
然而,这场透明化革命并非一片玫瑰色的乐观图景。技术是一把双刃剑,AI赋权的监督能力,同样可以被权力者或恶意行为者利用,走向其反面。政府可以利用更先进的AI进行大规模监控和社会信用评分,将“可读性”推向 Orwellian 的极端。政治斗争可能进入一个“AI辅助的抹黑”新时代,通过对海量公开信息进行有倾向性的关联挖掘和叙事构建,制造出看似数据确凿、实则断章取义的攻击材料。信息环境可能变得更加嘈杂,当每个人都能生成看似专业的分析报告时,辨别真伪、区分深度洞察与肤浅关联的挑战将更大。此外,新的数字鸿沟会出现:能够熟练运用这些AI工具、拥有高质量数据获取渠道的精英阶层,与普通大众之间的监督能力差距可能反而拉大,形成“监督阶级”。
更深层的挑战在于政治系统本身的适应性问题。现行的政治运作和问责机制,是建立在之前的信息流动速度和处理成本之上的。当AI使得某些形式的监督变得极其高效和低成本时,系统可能面临过载。例如,如果每一位议员每天都需要回应成千上万条由AI生成的、数据详实的质询,议会是否还能正常运转?当任何政策细节都可能被瞬间放大并引发全网争议时,政府是否还有空间进行必要的、谨慎的政策权衡和妥协?这要求我们的政治制度必须进化,发展出新的规范、流程和沟通机制,来适应一个被AI极大加速和深化的公共辩论场。
最终,AI驱动的社会监督革命,其意义不在于确保一个毫无瑕疵的政府,而在于重新平衡国家与社会之间的权力关系。它使得“阳光是最好的防腐剂”这句格言,第一次拥有了技术上的普适可行性。它不能替代民主制度的核心——选举、代表、辩论和法治,但它能为这些核心机制注入更高质量的燃料:更知情、更具体的公众意见。这场革命的终点,或许不是一个完全透明的乌托邦,而是一个监督成本大幅降低、权力滥用难度显著增加的社会。在这样的社会中,公职人员的行为逻辑将不得不发生改变,因为他们知道,任何不当行为都可能被某个角落的公民,用他手机上的AI助手轻易地挖掘和曝光。这并非技术的胜利,而是借助技术得以可能实现的、公民权利的实质性拓展。我们正在步入一个时代,在这个时代里,看清权力的眼睛,不再只属于高高在上的国家,也属于每一个被权力所治理的普通人。
参考来源
- Something I've been thinking about - I am bullish on people (empowered by AI) increasing the visibility, legibility and accountability of their governments.
- Historically, it is the governments that act to make society legible (e.g. "Seeing like a state" is the common reference), but with AI, society can dramatically improve its ability to do this in reverse. Government accountability has not been constrained by access (the various branches of government publish an enormous amount of data), it has been constrained by intelligence - the ability to process a lot of raw data, combine it with domain expertise and derive insights. As an example, the 4000-page omnibus bill is "transparent" in principle and in a legal sense, but certainly not in a practical sense for most people. There's a lot more like it: laws, spending bills, federal budgets, freedom of information act responses, lobbying disclosures... Only a few highly trained professionals (investigative journalists) could historically process this information. This bottleneck might dissolve - not only are the professionals further empowered, but a lot more people can participate.
- Some examples to be precise: Detailed accounting of spending and budgets, diff tracking of legislation, individual voting trends w.r.t. stated positions or speeches, lobbying and influence (e.g. graph of lobbyist -> firm -> client -> legislator -> committee -> vote -> regulation), procurement and contracting, regulatory capture warning lights, judicial and legal patterns, campaign finance... Local governments might be even more interesting because the governed population is smaller so there is less national coverage: city council meetings, decisions around zoning, policing, schools, utilities...
- Certainly, the same tools can easily cut the other way and it's worth being very mindful of that, but I lean optimistic overall that added participation, transparency and accountability will improve democratic, free societies.
- (the quoted tweet is half-ish related, but inspired me to post some recent thoughts) - https://nitter.net/karpathy/status/2040549459193704852#m
- 《重返未来:1999》三周年特别版本·3.7版本PV:他者的悲哀 - https://www.bilibili.com/video/BV1MPdBB8EEN
- 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