feature
What It Means
A feature is any piece of information or data point that an AI system uses to make predictions or decisions. Think of features as the individual ingredients that go into the AI's decision-making recipe - like age, income, purchase history, or location data that help predict whether a customer will buy a product.
Why Chief AI Officers Care
Features directly determine what your AI system can and cannot predict, making them critical for business outcomes and regulatory compliance. Poor feature selection can lead to biased decisions, privacy violations, or models that don't solve real business problems. The features you choose also determine what data you need to collect and maintain, impacting your data strategy and operational costs.
Real-World Example
A credit approval AI might use features like credit score, annual income, employment history, debt-to-income ratio, and number of existing accounts to predict loan default risk. Each of these data points is a feature that helps the system make lending decisions.
Common Confusion
People often confuse features with raw data - features are the processed, meaningful variables extracted from raw data that the AI actually uses. For instance, raw transaction logs become features like 'average monthly spending' or 'number of late payments in the past year.'
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, features are clinical data points like vital signs, lab values, medical history, imaging measurements,...
Finance: In financial AI systems, features are the specific data points used to assess creditworthiness, detect fraud, or make in...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"An attribute containing information for predicting the label."Source: AI_Fairness_360
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