TedTest

From the Ted Talk by Derek Abbott: Should you trust unanimous decisions?

Unscramble the Blue Letters

Imagine a police lineup where ten witnesses are asked to identify a bank reobbr they glimpsed fleeing the crime sncee. 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 pinot, it usually is. But sometimes, the closer you start to get to total agreement, the less reballie the result becomes. This is called the paradox of uniitmnay. The key to understanding this apparent paarodx is in considering the overall level of uncertainty involved in the type of situation you're dealing with. If we asekd wsesitnes 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 tmeis, you would expect to get heads somewhere around 50% of the time. But if your results started to approach 100% hdaes, you'd suspect that something was wrong, not with your individual fpils, 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 alppes from bananas, either. In fact, a 1994 study found that up to 48% of witnesses tend to pick the wrong porsen out of a lineup, even when many are confident in their cohcie. Memory besad on short glimpses can be ubinrelale, and we often overestimate our own aarcccuy. Knowing all this, a unamuions icifoaenititdn starts to seem less like certain guilt, and more like a stmyiesc 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 cirme scenes around Europe, incriminating an elusive killer dubbed the Phantom of hobielrnn. But the DNA eecvnide was so consistent precisely because it was wrong. It tnuerd 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 cseas, systematic errors arise through deliberate fraud, like the presidential referendum held by sddaam hueissn in 2002, which calmeid a turnout of 100% of vrteos 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 siianttous, eorrr and disagreement should be naturally expected. And if a perfect result seems too good to be true, it probably is.

Open Cloze

Imagine a police lineup where ten witnesses are asked to identify a bank ______ they glimpsed fleeing the crime _____. 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 _____, it usually is. But sometimes, the closer you start to get to total agreement, the less ________ the result becomes. This is called the paradox of _________. The key to understanding this apparent _______ is in considering the overall level of uncertainty involved in the type of situation you're dealing with. If we _____ _________ 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 _____, you would expect to get heads somewhere around 50% of the time. But if your results started to approach 100% _____, you'd suspect that something was wrong, not with your individual _____, 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 ______ from bananas, either. In fact, a 1994 study found that up to 48% of witnesses tend to pick the wrong ______ out of a lineup, even when many are confident in their ______. Memory _____ on short glimpses can be __________, and we often overestimate our own ________. Knowing all this, a _________ ______________ starts to seem less like certain guilt, and more like a ________ 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 _____ scenes around Europe, incriminating an elusive killer dubbed the Phantom of _________. But the DNA ________ was so consistent precisely because it was wrong. It ______ 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 _____, systematic errors arise through deliberate fraud, like the presidential referendum held by ______ _______ in 2002, which _______ a turnout of 100% of ______ 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 __________, _____ and disagreement should be naturally expected. And if a perfect result seems too good to be true, it probably is.

Solution

claimed
systemic
error
paradox
situations
unanimity
hussein
crime
robber
choice
evidence
turned
unreliable
asked
identification
voters
accuracy
heads
scene
flips
apples
cases
saddam
heilbronn
reliable
based
times
point
person
witnesses
unanimous

Original Text

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.

Frequently Occurring Word Combinations

Important Words

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