In statistical world, false positive and false negative are called Type I and Type II errors respectively. If you are not a statistician, don’t fret and don’t brush away these terms. It is applicable to every one across all levels, because it is the consequence of the decisions we make and we all make decisions in our lives every day. More importantly, we don’t always make right decisions. So we need to understand how we make the wrong decisions, i.e. the difference between false positive and false negative results because making wrong decisions can be costly.
We have to make decisions because we don’t know the outcome at that point in time and we need to decide to move forward. We decide based on our assumptions, our intuition and/or analysis. So clearly, they are all estimations which may not necessarily be right. False positive is the result of you approving something that you think is right but turns out to be the wrong. False negative is the result of you rejecting something that you think is wrong but turns out to be right.
Have you ever made any false positive and/or false negative decisions in your personal or professional lives? I’m sure you have. It could be on choosing which idea to execute, which investment to make, which house to buy, which job to take etc.
For example, buying a house. You think that House A will appreciate more in value than House B based on your research and instincts. So you decide to buy House A. But 10 years down the road, you found out that House B appreciated by more than expected, more than House A, the house you ended up buying. This is called false positive.
Another example, an investment in startup. Based on your analysis etc, you decided not to invest in a particular startup. But the startup ended up flourished and became a unicorn. This is called false negative.
The reason I brought up this matter is to increase your awareness so that you make less false positive and false negative decisions and you shouldn’t rely solely on intuitions to make decisions. As Adam Grant highlighted in his book Original,
- Intuitions are only accurate in domains where we have a lot of experience
- Intuitions are only trustworthy when people build up experience making judgments in a predictable environment
- But lessons of experience can easily point us in the wrong direction in a rapidly changing world
- So this makes intuition less reliable as a source of insight about new ideas and places a growing premium on analysis
This will also help you in assessing other people’s views/decisions.