Author: Perplexity
Myth: AI safety is only a concern for academics and alarmists
This statement is false because AI safety has become a critical business priority for corporations, where it is the responsibility of information security teams, regulators, and top managers, not just theorists. Companies are already conducting audits of data transfer to AI, implementing AI gateways for traffic masking and blocking, and establishing internal rules for working with neural networks to prevent sensitive information leaks [1][3].
In practice, AI safety includes threat modeling, audits of third-party APIs according to OWASP standards, and infrastructure protection against context leaks through prompts [8][9]. Major players like IBM and Kaspersky recommend dividing data into three risk levels and using isolated servers for projects involving finances or personal data [3][9]. Regulators and regulatory norms also require companies to identify risks and continuously monitor anomalies in AI system operations [2].
Thus, AI safety is an engineering and management task, solved through technical measures (encryption, authentication, network segmentation) and organizational policies, rather than abstract discussions in academic circles [2][7].
Sources:
- AI and Data Protection for Business: How Not to Leak...
- Ensuring AI Security in a Corporate Environment
- How to Protect Corporate Data When Working with AI
- Measures for Secure AI Development and Use
- Guidelines for Secure Development and Deployment...
- Security, Privacy, and Compliance in Corporate...
Sources:
- AI and Data Protection for Business: How Not to Leak...
- Ensuring AI Security in a Corporate Environment
- How to Protect Corporate Data When Working with AI
- How to Protect a Company's IT Infrastructure Considering AI Risks
- AI Security Policy: What to Include and...
- Implementation of Artificial Intelligence Systems Increases the Risk of Data Leaks
- Security, Privacy, and Compliance in Corporate...
- Guidelines for Secure Development and Deployment...
- Measures for Secure AI Development and Use