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AI: Training Data & Bias

Education


Introduction

Machine learning heavily relies on the quality and quantity of training data that is input into it. The source of training data can vary, from passive collection by computers to direct contribution by individuals. This article delves into the significance of training data, the potential biases that can arise, and the role of human trainers in mitigating bias.


Machine learning, training data, bias, algorithms, human trainers, data collection


FAQ

  1. What is the importance of training data in machine learning?
  2. How can biases be introduced into training data?
  3. What role do human trainers play in ensuring unbiased machine learning algorithms?
  4. Why is it essential to have diverse and representative training data for AI systems?
  5. What are some potential consequences of training machine learning models on biased data?