AI Search Summary
This video gives the answer to the Linda Test, a classic psychology example of the conjunction fallacy. It explains why many people judge "feminist bank teller" as more likely than "bank teller," even though a more specific combined category cannot be more probable than the broader category that contains it.
- Main question: Why is the Linda problem a conjunction fallacy?
- Short answer / core takeaway: A conjunction cannot be more likely than one of its component events, even when it feels more representative of the story.
- Evidence type: Cognitive-bias and judgment-under-uncertainty research.
- Search topics: Linda problem, conjunction fallacy, representativeness heuristic, Daniel Kahneman, probability reasoning, cognitive biases.
Common Search Questions
What is the correct answer to the Linda problem?
The answer is that Linda is more likely to be a bank teller than a feminist bank teller. "Feminist bank teller" is a subset of "bank teller," so it cannot have a higher probability than the broader category.
Why do people get the Linda Test wrong?
Many people rely on representativeness: Linda's description sounds more like their mental model of a feminist bank teller than a generic bank teller. That intuitive match can override the rules of probability.
What cognitive bias does the Linda Test show?
The Linda Test demonstrates the conjunction fallacy, where people mistakenly judge a combined, more specific event as more likely than one of the simpler events that includes it.
Key Takeaways
- The Linda problem is designed to reveal a conflict between narrative plausibility and probability logic.
- A narrower category cannot be statistically more likely than the broader category that contains it.
- The representativeness heuristic can make a detailed description feel more likely even when it is mathematically less likely.
- The video frames the exercise as a practical lesson in spotting cognitive biases.
Transcript
Revealing the setup
Can you pass the Linda Test? Almost 90% of Stanford students got it wrong.
Last video I gave the full version that I called the Social Perception Test. Yes, I was trying to trick you. It gives this description of Linda, and these possible descriptions that you had to rank in order of how likely they were to apply.
But really only three of these mattered. Pause and write down which of the three you think is most likely.
Ready for the answer?
The conjunction fallacy
This question set you up to fall for a cognitive bias known as the conjunction fallacy.
Our brains are really bad at probability. As many of you may have discovered in college. But it is not your fault. It is built in.
90% of students said that Linda was more likely to be a feminist bank teller than just a bank teller. But that is wrong.
Even if you knew nothing about Linda, B is included in A, and so cannot be more likely than it. Let's say A was 20%. B can only be less than 20%.
Why the wrong answer feels right
So why do we make this mistake?
Professor Daniel Kahneman proposed it was due to something called the representativeness heuristic.
When our brain is guessing at probabilities, it compares what is in front of it to its existing mental models or stereotypes. Because Linda seems to be more representative of the category of feminist bank tellers than just bank tellers, that translates to thinking it more likely, against all actual rules of probability.
Cognitive-bias series framing
If you like learning how to think better, hit that follow button. I'll be doing frequent segments on cognitive biases and how to spot them.
Additional Notes
Caption context
No caption text was available in the source page.
Keywords and topics
- Linda problem answer
- Conjunction fallacy example
- Representativeness heuristic
- Probability reasoning error
- Cognitive bias education
References
- Daniel Kahneman, judgment under uncertainty, and cognitive-bias context. Source link: https://pubs.aeaweb.org/doi/pdfplus/10.1257/089533005775196732
- Conjunction fallacy and reasoning research context. Source link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967104/