The Conjunction Fallacy is another idea that originated with psychologists Daniel Kahneman and Amos Tversky. In 1983 they came up with an experiment known as “The Linda Problem:”
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice and also participated in anti-nuclear demonstrations.
Which is more probable?
- Linda is a bank teller.
- Linda is a bank teller and is active in the feminist movement.
Tversky and Kahneman argued that many people would pick the wrong answer here (option 2) because they use a heuristic called ”representativeness.”
To many, the second option seems more “representative” of Linda based on the original description of her: several relatively progressive descriptions, however, there’s no mention of feminism.
Many might assume since she seems progressive, she must also be involved in the feminist movement, even though it’s mathematically less likely that Linda would be both a bank teller and a feminist activist.
However, it’s more probable that Linda is only a bank teller.
This bias directly relates to the UX research team and those who are making decisions based on research insights. Make sure that you are aware of this bias as you synthesize research findings and weigh different options for the team.
🎯 Here are some key takeaways:
Educate everyone on probability
Most people on your team will not be experts in statistics and probability. Provide the team with clear explanations about how probability works and the applicable principles to help them make informed decisions.
Use simple language
Present information using straightforward language and avoid jargon that might confuse the team and lead to erroneous judgments.
Utilize visual aids
Incorporate data visualization when possible to help the team understand the likelihood of events and make more rational choices based on the presented data.
Keep it simple
Don’t assume elaborate conclusions make the most sense, when in reality they may be the most unlikely scenarios. Don’t allow your stereotypes and biases to cloud your judgment.
Understand the stakes
Like most of the biases related to statistics and probably it may be necessary to act before having all the data. Assume the right risks when necessary and always ask “What if we’re wrong?”
📚 Keep exploring
To dive deeper into the topic of the conjunction fallacy and its implications for decision-making, check out these resources:
