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Dec 11, 2023 ·

This article is written by Anima Anandkumar, a professor of Computer Science and Electrical Engineering at the California Institute of Technology. The article focuses on the need for security in AI systems.

Anandkumar starts off by noting that AI systems are becoming increasingly prevalent in everyday life, such as self-driving cars, facial recognition software, and various other applications. However, she notes that there is great potential for exploitation of these systems due to their reliance on data and algorithms. Anandkumar argues that AI systems must have security measures in place in order to protect from malicious use.

To this end, Anandkumar introduces the concept of "adversarial machine learning", which is an area of research that seeks to develop methods and techniques to identify and mitigate vulnerabilities in AI systems. She notes the importance of developing secure architectures and algorithms for these systems in order to protect against malicious activities or attacks.

Anandkumar then provides some examples of recent application of adversarial machine learning, such as identifying malicious accounts on social media sites or detecting malware disguised as benign programs. She also emphasizes the importance of defending against manipulation of data and models in order to ensure accuracy and reliability of results.

Finally, Anandkumar concludes her article by emphasizing the need for rigorous security measures to be implemented in AI systems. She expresses that this is crucial for the safety of users and society at large, and emphasizes the importance of creating secure systems that are both reliable and accurate.