From ef498720c08dc5ed38184329c0e629e1a7ef8ab2 Mon Sep 17 00:00:00 2001 From: mindwind Date: Wed, 13 Mar 2024 14:54:28 +0800 Subject: [PATCH] New post 02-29 --- ...12\345\231\252\345\243\260\343\200\213.md" | 85 ++++++++++++++++++ archive/archive.md | 1 + assets/article_images/2024-02-29-1.png | Bin 0 -> 47076 bytes assets/article_images/2024-02-29-2.png | Bin 0 -> 142773 bytes assets/article_images/2024-02-29-3.png | Bin 0 -> 85612 bytes assets/article_images/2024-02-29-4.png | Bin 0 -> 154980 bytes assets/article_images/2024-02-29.jpg | Bin 0 -> 404307 bytes 7 files changed, 86 insertions(+) create mode 100644 "_posts/2024-02-29-\346\264\273\345\234\250\345\205\205\346\273\241\350\257\257\345\267\256\347\232\204\344\270\226\347\225\214\351\207\214\342\200\224\342\200\224\350\257\273\343\200\212\345\231\252\345\243\260\343\200\213.md" create mode 100644 assets/article_images/2024-02-29-1.png create mode 100644 assets/article_images/2024-02-29-2.png create mode 100644 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+author : 慢文(mindwind) +categories: blog +tags : 读书 误差 偏差 噪声 +image : /assets/article_images/2024-02-29.jpg +elapse : 4h +--- + +摘要:看清现实,理解世界的不完美 + +--- + +今年的春节档电影就看了《第二十条》,电影中的一个核心矛盾点是关于司法案件中“正当防卫”和“故意伤害”之间的判决。故事的矛盾冲突就在于过往大量类似正当防卫的案例被判成了故意伤害,这是一种什么问题?这让我想起了上个月刚读过的一本书——《噪声》。 + + +## 判断中的两类错误 +《噪声》的作者之一丹尼尔·卡尼曼,大名鼎鼎的诺奖得主,他之所以写这本书的原因之一就在于发现人类社会中存在大量的判断问题,其中司法判决是一个重灾区。司法判决追求的目标是公平与正义,而书中调研的案例中同样类似的案件,不同的法官或者同一法官在不同时期的判罚的标准相差巨大。如果同一个罪,适当的判罚是5年,但有一个人被判1年,另一个人被判9年,平均下来也是5年,这个平均的5年还能代表公平正义吗?电影《第二十条》更戏剧极端化一些,判决的一边是无罪的正当防卫,另一边则是故意杀人。 + +这本书的序言中有句话,直击要害: + +>> 判断是人生阅历的核心组成部分,也是所有组织运作的中枢要点。 + +而经过卡尼曼他们的研究认为:人类的判断中存在两类错误。第一种叫偏差,第二种叫噪声;两类错误组成共同形成了人类判断中的误差。 + +书中有个很形象的图示案例,展示了什么是偏差和噪声。 + +![](/assets/article_images/2024-02-29-1.png) + + +上图是一个ABCD四队打靶的结果,展示的是靶的背面,我们看不见靶心在哪。但从分布情况也知道,CD两队很分散,不可能都接近靶心,而AB两队则看不出来。下面我们再看看靶的正面: + +![](/assets/article_images/2024-02-29-2.png) + +结果如上图,很明显。A队全部在靶心中,可以说以靶心为目标,他们的结果误差很小。CD两队则呈现无规律分散,B队则集中分布在左下侧。CD两队结果中体现出的就是噪声,而B队结果体现出的就是偏差,偏差方向很稳定。无论偏差还是噪声,最终的结果都是离目标产生了误差。 + + +## 偏差和噪声 +如打靶案例中的B队,偏差可能来自枪准心本来就是歪的,谁用这把枪打都稳定的歪向左下侧。而电影《第二十条》中检察官查阅了历史上很多类似案例的判罚都是判故意伤害或杀人,所以他一开始觉得自己的判断也没错,但这就是一种明显的历史群体偏差。 + +而噪声则不同,噪声有三种:水平噪声、模式噪声和情景噪声。 + +如果电影中历史上的案例有些判故意伤害,有些判正当防卫,那就是噪声的一种类型:水平噪声。“水平噪声”是不同法官做出的判决和均值之间产生较大差异。 + +如果同一个法官,类似案件这次判3年,另一次又判7年,那这个人本身可能存在模式噪声。书中给了个案例研究,同一个法官,有人总是对白人判罚更轻,对惯犯更严格。这就是存在于一个人身上稳定的模式噪声,受到个人长期形成的世界观和价值观影响。 + +而情景噪声则是转瞬即逝的,如果法官因为开庭前一天有好事发生,第二天的判罚可能就更轻。只是这种影响很难被观察和测量出来,但从生活的经历感性中我们也知道这样的影响确实存在。这种影响来自情绪,而情绪是情境噪声的源头。 + + +## 误差公式 +至此,我们分析了误差的来源:偏差和噪声。就可以用一个公式来量化误差(如下图): + +![](/assets/article_images/2024-02-29-3.png) + +这是天才的数学家高斯提出来的“最小二乘法”,他在测量总体误差时使用均差——个体误差平方的平均值。数学证明它的正确性,大概要用到高等数学里的一些求导知识(不好意思我已经忘了)。但这里只是用这个数学概念来形象理解现实世界的判断,而现实中的很多判断是难以量化的,比如就像电影中案件的判罚,如何才能量化出真实合理的判罚,这种情况不像打靶,我们没有靶心。但高斯的数学原理告诉我们,用多次判断取最小均差的值,得到的判罚就是最小误差的,而这个判罚也许就是最接近真实的公平正义的。 + + +## 减少误差 +误差可以分解为偏差和噪声,而噪声又可以进一步分解为三种(如下图)。 + +![](/assets/article_images/2024-02-29-4.png) + +偏差产生的结果是固有的、稳定的,就如歪了准心的枪,称重总是偏重的称。只要偏差足够明显,总是可以观察出来的。而有些偏差来自人类心理效应,比如电影《第二十条》中表现的检察官历史判决总是偏向故意伤害一边,这来自一种现状偏差——指人们倾向于保持现状。历史上都这么判,我也这么判,心里感觉大差不差。直到这个偏差的结果足够显著,才引发了反思。 + +对于噪声,水平噪声来源于不同人的差异;而稳定的模式噪声则是每个人形成世界观和价值观过程中固有的模式,个人甚至很难察觉;情景噪声发生的场景转瞬即逝,因人而异更是微妙。那么为了减少噪声对判断的影响,现实中最常见的场景还是由多人独立判断取平均值,这也符合高斯的数学原理。 + +取平均值的关键是:多人、独立。不独立,又会相互影响带来偏差,而多人具体来说应该是多少?从数学角度:平均值减少的噪声量=1-判断总数平方根的倒数。也就是说,如果有100个独立判断,那么将减少90%的噪声。而现实中,大部分情况我们只能消除一半多些的判断噪声。想想如职场中,像面试场景,会有几个人来独立判断?绩效或晋升评估又会有几个人来独立判断?所以大部分的判断场景中都充斥中不少比例的噪声。 + +还有一种是用算法模型来消除噪声。是的,算法没有噪声,但有偏差。最近,谷歌大模型出了个丑闻,用文字生成图片时,罔顾事实,把马斯克画成黑人。这就是偏差,只是一种很容易看出显著差异的偏差。我们并不知道算法中的偏差是人为引入的,还是训练的大数据本身就包含偏差。 + +现在进入了AI时代,即使在很多领域取代了人类的判断,但类似这样的算法偏差依然会悄悄存在,世界里的误差永远不会被消除,我们终将一直生活在这样的世界里。 + +... + +末了,回到书本身。和丹尼尔·卡尼曼另外一本书《思考,快与慢》类似,本书也是一本非常理论化的书,这类书读起来往往枯燥,但其中又闪烁着智慧的结晶,熠熠发光。 + +书山有路,读书无非就是寻着一点光芒,去寻找那一块块闪烁的宝石。 + + +--- +写点文字,记录此刻。 +微信公众号「瞬息之间」,既然遇见,不如同行。 +![](/assets/images/qrcode_wechat_avatar.jpg) diff --git a/archive/archive.md b/archive/archive.md index 5ddd381..af4829d 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