Synthetic Data

Synthetic Data

The creation of plausible, factually-grounded data for training of machine models rather than, or in addition to, importing real-world data. Synthetic data use is intended to reduce bias, quickly train models, and improve accuracy. For example, synthesizing demographically-accurate data about the population of a university might be preferable to risking leaks of individuals' real addresses, grades, or other private information.

"The credit-scoring firm introduced synthetic data that corrected for  inherited privilege, to counteract societal biases against women."

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Overview

How to Think About

Synthetic Data

Practical Applications of

Synthetic Data