Generative AI May Reduce Machine Learning Costs but Heighten Cybersecurity Risks
| Source: Tech Xplore on MSN | Original article
Generative AI may reduce machine-learning costs, but increases cyberattack risks. It poses new data leak threats.
Generative AI may cut costs in machine-learning systems, but it increases risks of cyberattacks and data leaks, according to computer scientist Michael Lones. In a paper published in Patterns, Lones argues that using generative AI to design, train, or perform steps within a machine-learning system is risky. This is because large language models can introduce vulnerabilities that malicious actors can exploit, leading to cyberattacks and data leaks.
This warning matters because companies are increasingly deploying generative AI systems to reduce operational costs and enhance efficiency. While these systems may improve the user experience, they also pose significant risks, including bias and unfairness. As we previously reported, the use of AI models like RAG can lead to data leaks, and the restructuring of companies like OpenAI may exacerbate these risks.
As the adoption of generative AI continues to grow, it is essential to watch how companies balance the benefits of cost savings with the need to mitigate cyber risks. Researchers and developers must prioritize the development of secure and transparent AI systems to prevent the negative consequences of widespread generative AI adoption. With the potential for significant cost savings, companies like Geisinger have already seen success with AI-powered solutions, but the industry must proceed with caution to avoid the pitfalls of generative AI.
Sources
Back to AIPULSEN