FBLA Data Science & AI Practice Test 2025 - Free Data Science & AI Practice Questions and Study Guide

The concept that highlights the necessity for AI systems to shield data from unauthorized access aligns with the notion of security risks. Security risks of large language models (LLMs) refer to potential vulnerabilities that can lead to breaches or misuse of data. In this context, protecting data means implementing measures that prevent unauthorized personnel from accessing sensitive information, ensuring that data integrity and privacy are maintained.

Organizations deploying AI systems must recognize the myriad of threats that can target data, including cyberattacks, data leaks, and improper access controls. Consequently, a robust understanding of security risks allows developers and data scientists to create AI systems with strong safeguards, ensuring compliance with regulations and protecting user trust.

Other choices, while relevant in different contexts, do not specifically highlight the need for data protection against unauthorized access in the same way as the concept of security risks.