TED: What to trust in a "post-truth" world | Alex Edmans

The video discusses the story of Belle Gibson, who falsely claimed to have cured her cancer through diet, highlighting the dangers of confirmation bias and the post-truth era. It explains Bayesian inference and the importance of distinguishing between data and evidence. The video emphasizes the need for multiple data points, expert opinions, and responsible information sharing to avoid misleading conclusions.

What was the main issue with Belle Gibson's story?

• It was a true story.

• It was a common story shared by many.

• It was supported by scientific evidence.

• It was a single story that went viral.

What does Bayesian inference help us understand?

• How to confirm a theory with any data.

• How to check if data supports a theory.

• How to ignore rival theories.

• How to create new theories from data.

Why is relying on a single story problematic?

• It is always supported by evidence.

• It ignores the majority of cases.

• It is the best way to understand a theory.

• It always provides accurate data.

How can you ensure that data is considered evidence?

• By checking if it supports multiple theories.

• By ensuring it rules out rival theories.

• By ignoring the source of the data.

• By confirming it is consistent with any theory.

What is a key strategy to avoid confirmation bias?

• Only listen to people who agree with you.

• Ignore expert opinions.

• Seek out diverse viewpoints.

• Rely solely on personal experiences.

Why is it important to listen to experts?

• Experts provide evidence-based insights.

• Experts never make mistakes.

• Experts always agree with each other.

• Experts are always in touch with the public.

What is a common misconception about experts?

• They never disagree with each other.

• They base their insights on evidence.

• They are always out of touch with reality.

• They always provide the same advice.

What is the role of peer review in academic journals?

• To avoid any form of criticism.

• To publish papers without evidence.

• To scrutinize papers for quality.

• To ensure all papers are accepted.

What should you do before sharing information?

• Ensure it aligns with your beliefs.

• Verify its truth and evidence.

• Share it if it sounds interesting.

• Ignore the source of the information.

What is the danger of confirmation bias in sharing stories?

• It leads to sharing only verified stories.

• It results in spreading unverified information.

• It ensures all viewpoints are considered.

• It prevents the spread of misinformation.