La verdad que evitamos: por qué ignoramos los datos | Fernando de la Rosa | TEDxValencia

Quick Overview

The speaker argues that people generally trust data that confirms their existing beliefs (confirmation bias) and ignore data that challenges them, using specific scenarios involving GPS directions, sleep tracking, and restaurant reviews to illustrate how individuals selectively accept or reject information based on prior conviction rather than objective truth.

Key Points: People often reject new data if it contradicts deeply held beliefs, such as those about politics, religion, or even sports teams. The speaker uses three examples: GPS directing you left when you believe you should turn right, sleep tracking showing less than 8 hours, and low restaurant scores, to show how bias dictates data acceptance. The concept of 'Confirmation Bias' is identified as the mechanism where humans seek out and favor data confirming existing views, leading to the rejection of conflicting evidence. Data that is 'close' to one's belief (e.g., a 3% error margin in a flat-earth scenario) is often accepted, whereas data that significantly contradicts it is dismissed as 'fake news' or error. The speaker challenges the audience to question their beliefs, asking if they would change their mind about the Earth being flat if presented with contradictory data. The underlying problem is that our brains are not trained to process overwhelming amounts of data objectively; instead, we use our existing beliefs as a filter. The overall conclusion is that we must actively work to recognize and counteract our inherent biases when interpreting real-world data.

Context: This TEDxValencia talk, delivered by Fernando de la Rosa, addresses the pervasive human tendency to selectively interpret information, focusing specifically on how people process data—or dismiss it—based on pre-existing convictions, a phenomenon he labels as confirmation bias and highlights through relatable, everyday examples.

Detailed Analysis

Fernando de la Rosa opens by stating that we live in an exciting era where digital technology allows science to advance at an incredible speed, all based on data. He immediately introduces the core conflict: we often prefer our beliefs over the data presented to us. He illustrates this with three scenarios to demonstrate confirmation bias. First, when GPS tells you to turn left, but you strongly believe you should turn right, you distrust the GPS, claiming you've always gone right. Second, he asks the audience how many sleep less than 8 hours; many raise their hands, but when he presents data suggesting that people who sleep less than 8 hours are happier, those who raised their hands often lower them, indicating a rejection of data that contradicts a perceived need for more sleep. Third, he discusses the concept of a 'Nutritional Score' for food packaging: if an item has a good score, people trust it; if it has a low score, they dismiss it as flawed. He then tests the audience on whether they would change their belief that the Earth is flat if presented with data showing otherwise, noting that only a small percentage (3%) would likely change their minds, regardless of the data's precision. The speaker explains that this is because our brains are not trained to process massive amounts of data continuously; instead, we use our existing beliefs—whether political, religious, or personal—as a filter. He concludes by urging the audience to be aware of these cognitive shortcuts and actively work to interpret data more objectively, rather than letting ingrained beliefs dictate what we accept as truth.