Hello, I’m Pang Ying. Welcome to Episode 9 of Think Like a Debater. Today we examine statistical errors, beginning with a debate motion.

Season Seven of I Can I BB asked: “If you could become famous overnight at twenty, should you take the opportunity?”

The affirmative naturally described benefits such as self-realization and the chance to influence people and society.

The opposition described risks a young person might not manage: money, temptation, and the strong possibility of fading from fame. Some child stars developed psychological problems; the Home Alone actor later struggled with alcohol and drugs.

Everything has two sides. The first clash was whether young people could manage overnight fame, realize its benefits, and avoid its harms.

One affirmative debater had himself become famous at twenty: “They say I’ll fade away; I haven’t. They say I’ll cater to others; I haven’t.”

The opposition replied: “That’s survivorship bias!”

What is survivorship bias?

Data collected from visible survivors are incomplete because unseen casualties are missing.

The classic example comes from World War II. The U.S. military studied returning aircraft and proposed reinforcing the areas with the most bullet holes, such as the wings.

Columbia mathematician Abraham Wald advised the opposite: reinforce areas with few hits, especially engines, because planes hit there never returned. Studying only survivors biases the conclusion, and Wald proved right.

The show’s teams illustrated the point. The affirmative consisted of successful returning guests, including former BB King Xiao Xiao and public figure Jiang Sida. The opposition comprised relative newcomers, including teacher Xiong Hao and student Xi Rui.

Guests invited back are necessarily excellent and still visible; those unable to manage fame no longer appear onstage. Survivorship bias therefore creates excessive optimism.

It occurs in many settings.

People say old products were better made, old crafts finer, old buildings prettier, or past musicians greater. But only the best perhaps 1% survived as classics; discarded mediocrity disappeared. Judging an era from its surviving 1% is biased.