AI Security
AI Security is a multidisciplinary field focused on protecting artificial intelligence systems from threats, vulnerabilities, and attacks, while ensuring their safe, ethical, and reliable operation. It encompasses techniques for securing AI models, data, and infrastructure against adversarial manipulation, data poisoning, model theft, and privacy breaches. The field also addresses broader concerns like AI safety, robustness, and alignment with human values.
Developers should learn AI Security when building or deploying AI systems in critical applications like autonomous vehicles, healthcare, finance, or cybersecurity, where failures or attacks could have severe consequences. It's essential for ensuring model integrity, protecting sensitive training data, and complying with regulations like GDPR, especially as AI becomes more integrated into high-stakes domains. Knowledge in this area helps mitigate risks such as adversarial examples that fool models or data leakage from machine learning pipelines.