outlier
What It Means
An outlier is a data point that looks completely different from the rest of your data - like finding a 25-year-old in a retirement home or a $50,000 salary among executives making $500,000. These unusual values can throw off your AI models because they're so far from what's typical. Think of them as the weird data points that make you wonder if something went wrong in data collection.
Why Chief AI Officers Care
Outliers can completely derail AI model performance, causing wildly inaccurate predictions that hurt business decisions and customer trust. They often signal data quality problems, fraud, or system errors that need immediate attention. If not handled properly, a few outliers can make your entire AI system unreliable, leading to poor recommendations, pricing errors, or missed opportunities.
Real-World Example
A credit card company's fraud detection system sees thousands of $20-200 transactions daily, but suddenly encounters a $45,000 purchase at a gas station in another country. This outlier could indicate fraud and should trigger an alert, but if the system wasn't trained to handle such extreme values, it might either miss the fraud entirely or start flagging normal transactions as suspicious.
Common Confusion
People often think all outliers are errors or bad data that should be deleted, but some outliers represent the most valuable insights - like identifying your highest-value customers or detecting critical system failures. The key is distinguishing between outliers that reveal important patterns versus those that corrupt your analysis.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, outliers often represent critical cases like a 20-year-old with advanced heart disease or lab values i...
Finance: In finance, outliers often signal market anomalies, fraud, or data quality issues that can severely distort risk models,...
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Technical Definitions
NISTNational Institute of Standards and Technology
"An outlier is a data point that is far from other points."Source: Russell_and_Norvig
"An outlier is a data value that lies in the tail of the statistical distribution of a set of data values."Source: OECD
"Values distant from most other values. In machine learning, any of the following are outliers: • Weights with high absolute values • Predicted values relatively far away from the actual values • Input data whose values are more than roughly 3 standard deviations from the mean Outliers often cause problems in model training. Clipping is one way of managing outliers"Source: aime_measurement_2022 citing Machine Learning Glossary by Google
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