ai-engineer-ai-safety-and-ethics-conducting-adversarial-testing

# ai-engineer-ai-safety-and-ethics-conducting-adversarial-testing

## Contents

__Roadmap info from [ roadmap website ] (https://roadmap.sh/ai-engineer/conducting-adversarial-testing@Pt-AJmSJrOxKvolb5_HEv) __

  ## Conducting adversarial testing

  Adversarial
  testing
  involves
  intentionally
  exposing
  machine
  learning
  models
  to
  deceptive, perturbed, or carefully crafted inputs to evaluate their robustness and identify vulnerabilities. The goal is to simulate potential attacks or edge cases where the model might fail, such as subtle manipulations in images, text, or data that cause the model to misclassify or produce incorrect outputs. This type of testing helps to improve model resilience, particularly in sensitive applications like cybersecurity, autonomous systems, and finance.