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.
Zamislite paradu prepoznavanja gde je od deset svedoka zatraženo da identifikuju pljačkaša banke koga su letimično spazili kako beži s mesta zločina. Ako šestoro njih izabere istu osobu, dobre su šanse da se radi o stvarnom krivcu, a ako svih desetoro naprave isti izbor, pomislili biste da se radi o čvrstom slučaju, ali ne biste bili u pravu. Za većinu nas ovo zvuči prilično čudno. Konačno, naše se društvo uglavnom oslanja na glas većine i konsenzus, bilo u politici, poslu ili zabavi, Pa je prirodno misliti da je više konsenzusa nešto dobro. I do određene tačke, obično jeste. Ali ponekad, što se više približavate potpunom slaganju, rezultat je sve nepouzdaniji. Ovo se naziva paradoksom jednoglasnosti. Ključ za razumevanje ovog očiglednog paradoksa je u razmatranju sveukupnog stepena nesigurnosti uključenog u situaciju kojom se bavite. Ako bismo tražili od svedoka da prepoznaju jabuku u ovom prepoznavanju, na primer, ne bi nas iznenadila jednoglasna presuda. Ali u slučajevima gde postoji razlog da očekujemo neke prirodne varijacije, takođe bi trebalo da očekujemo varijaciju u distribuciji. Ako bacite novčić stotinu puta, očekivali biste da dobijete glavu negde oko 50% puta. Ali ako bi vaš rezultat bio sve viši rezultatu 100% glava, posumnjali biste da nešto nije u redu, ne s vašim pojedinačnim bacanjima, već sa samim novčićem. Naravno da identifikacija osumnjičenih nije nasumična kao bacanje novčića, ali nije ni tako precizna kao razlikovanje jabuka od banana. Zapravo, istraživanje iz 1994. je otkrilo da do 48% svedoka bira pogrešnu osobu u paradi prepoznavanja, čak i kad je većina njih sigurna u svoj izbor. Sećanje zasnovano na letimičnom pogledu može da bude nepouzdano, a mi često precenjujemo sopstvenu preciznost. Znajući sve ovo, jednoglasna identifikacija sve manje zvuči kao izvesna krivica a sve više kao sistemska greška ili predrasuda u paradi prepoznavanja. A sistemske greške se ne pojavljuju samo kod ljudskog prosuđivanja. Od 1993. do 2008, DNK iste žene je pronađen na više mesta zločina širom Evrope, okrivljujući neuhvatljivog ubicu označenog kao Fantom iz Heilborna. Ali DNK dokaz je bio toliko dosledan baš zato što je bio pogrešan. Ispostavilo se da je pamučne tampone, korišćene za sakupljanje DNK uzoraka, sve slučajno kontaminirala žena koja je radila u fabrici tampona. U drugim slučajevima, sistemska greška nastaje namernom prevarom, poput predsedničkog referenduma koji je održao Sadam Husein 2002, koda je tvrđeno da je odziv glasača bio 100% i svih 100% su navodno glasali za novi sedmogodišnji mandat Huseina. Posmatrano na ovaj način, paradoks jednoglasnosti nije uopšte toliko paradoksalan. Jednoglasni sporazum je i dalje teoretski idealan, naročito u slučajevima gde ne očekujete značajnu promenljivost i neizvesnost, ali u praksi, njegovo dostizanje u situacijama gde je savršen sporazum skoro nemoguć govori nam da verovatno imamo skriveni faktor koji utiče na sistem. Iako težimo harmoniji i konsenzusu, u mnogim situacijama bi trebalo prirodno da očekujemo greške i neslaganje. Ako savršen rezultat izgleda suviše dobro da bi bio istina, verovatno i jeste.