Imagine a police lineup where ten witnesses are asked to identify a bank robber they glimpsed fleeing the crime scene. If six of them pick out the same person, there's a good chance that's the real culprit, and if all ten make the same choice, you might think the case is rock solid, but you'd be wrong. For most of us, this sounds pretty strange. After all, much of our society relies on majority vote and consensus, whether it's politics, business, or entertainment. So it's natural to think that more consensus is a good thing. And up until a certain point, it usually is. But sometimes, the closer you start to get to total agreement, the less reliable the result becomes. This is called the paradox of unanimity. The key to understanding this apparent paradox is in considering the overall level of uncertainty involved in the type of situation you're dealing with. If we asked witnesses to identify the apple in this lineup, for example, we shouldn't be surprised by a unanimous verdict. But in cases where we have reason to expect some natural variance, we should also expect varied distribution. If you toss a coin one hundred times, you would expect to get heads somewhere around 50% of the time. But if your results started to approach 100% heads, you'd suspect that something was wrong, not with your individual flips, but with the coin itself. Of course, suspect identifications aren't as random as coin tosses, but they're not as clear cut as telling apples from bananas, either. In fact, a 1994 study found that up to 48% of witnesses tend to pick the wrong person out of a lineup, even when many are confident in their choice. Memory based on short glimpses can be unreliable, and we often overestimate our own accuracy. Knowing all this, a unanimous identification starts to seem less like certain guilt, and more like a systemic error, or bias in the lineup. And systemic errors don't just appear in matters of human judgement. From 1993-2008, the same female DNA was found in multiple crime scenes around Europe, incriminating an elusive killer dubbed the Phantom of Heilbronn. But the DNA evidence was so consistent precisely because it was wrong. It turned out that the cotton swabs used to collect the DNA samples had all been accidentally contaminated by a woman working in the swab factory. In other cases, systematic errors arise through deliberate fraud, like the presidential referendum held by Saddam Hussein in 2002, which claimed a turnout of 100% of voters with all 100% supposedly voting in favor of another seven-year term. When you look at it this way, the paradox of unanimity isn't actually all that paradoxical. Unanimous agreement is still theoretically ideal, especially in cases when you'd expect very low odds of variability and uncertainty, but in practice, achieving it in situations where perfect agreement is highly unlikely should tell us that there's probably some hidden factor affecting the system. Although we may strive for harmony and consensus, in many situations, error and disagreement should be naturally expected. And if a perfect result seems too good to be true, it probably is.
想像一個「列隊指認」, 十位目擊者 被要求指認在現場瞥見 逃跑的銀行搶劫犯。 如果其中六位指認同一人, 那他很可能是真的罪犯, 如果十人的指認都相同, 你可能想這情況罪證確鑿, 但你錯了! 我們多數會覺得這聽起來很奇怪, 畢竟,我們社會大多 依賴 多數表決與共識, 無論是政治、商業或娛樂活動。 所以視 ‘越多共識是件好事’ 是理所當然的。 到某個程度,它通常是這樣的。 但有時,當開始越靠近完全一致時, 結果變得越不可靠, 這稱為「一致性悖論」。 了解這明顯矛盾論點的關鍵 在於考量整體不確定性, 它涉及你正在處理的情況類型。 例如,我們要求目擊者 指認這個列隊中的蘋果, 對有一致性的判斷 是無需驚訝的。 但有理由預料會有些自然差異的存在下, 我們也應預期會有不同的分佈。 如果你擲一個硬幣一百次, 你會預期得到人頭的次數 約在 50% 左右, 但若結果開始趨近 100% 的人頭, 你會懷疑有什麼不對勁了, 問題不在於你每次的拋擲, 而是硬幣本身。 當然,嫌疑犯的指認 不同於擲硬幣的隨機性, 但也不像分辨蘋果與香蕉那樣明確。 事實上,一個 1994 年的研究發現 高達 48% 的目擊者 往往會在列隊中指認錯人, 即便許多人很確信自己的指認。 短暫一瞥的記憶 可能是靠不住的, 而且我們常高估自己的準確度。 知道這些之後, 一致性的指認開始看起來 似乎不一定有罪, 而較像體制上的錯誤, 或對列隊中的人有偏見。 體制錯誤不只發生在 人為判斷的事而已。 從 1993 - 2008, 在歐洲各地許多犯罪現場 發現同一位女性的 DNA, 這位涉罪行蹤飄忽的殺手 被命名 「海布隆魅影」。 但 DNA 証據如此一致性 正因為它是錯的, 原來是用來收集 DNA 檢體的棉棒, 全被一位在棉棒工廠工作的女性 不經意地給污染了。 在其他情況, 體制錯誤是因於蓄意欺詐, 例如 2002 年,薩達姆•海珊主導的 全民公投總統大選, 宣稱投票率 100%, 且據稱有 100% 是贊成 他另一個七年任期。 從這個方面考量時, 「一致性悖論」事實上 並不是全然荒謬的。 一致同意仍是理論上的理想, 尤其在一些情況 預期變異及不確定的機率很低時, 但實際上, 在極不可能完全一致的情況下 卻出現一致時, 這告訴了我們 可能有些隱藏因素影響了體制。 雖然我們力求和諧與共識, 但許多情況, 錯誤與分歧理當是預料中之事, 若一個完美結果好得令人難以置信, 它大概真的其中有詐了。