Opinion
Tal Feldman is a Yale Law School student who previously built artificial intelligence models for the U.S. government. Ibrahim Dagher is pursuing law and PhD degrees at Yale and writes about AI policy and national security.
TL;DR
- AI systems are becoming attractive targets for hackers due to their increasing use in critical infrastructure and decision-making.
- Hackers can attack AI by poisoning training data or exploiting algorithm weaknesses, leading to biased outputs or unauthorized access.
- Protecting the large datasets AI systems use is crucial for preventing data exfiltration.
- AI companies need to implement strong security measures at all stages of the AI lifecycle, including access controls, encryption, and regular audits.
- Developing resilient AI systems through methods like adversarial training and anomaly detection is vital.
- Collaboration between AI developers, cybersecurity experts, and policymakers is necessary to establish best practices and regulations.