A military drone misidentifies enemy tanks as friendlies. A self-driving car swerves into oncoming traffic. An NLP bot gives an erroneous summary of an intercepted wire. These are examples of how AI systems can be hacked, which is an area of increased focus for government and industrial leaders alike.
As AI technology matures, it’s being adopted widely, which is great. That is what is supposed to happen, after all. However, greater reliance on automated decision-making in the real world brings a greater threat that bad actors will employ techniques like adversarial machine learning and data poisoning to hack our AI systems.
https://www.datanami.com/2020/07/28/hacking-ai-exposing-vulnerabilities-in-machine-learning/
As AI technology matures, it’s being adopted widely, which is great. That is what is supposed to happen, after all. However, greater reliance on automated decision-making in the real world brings a greater threat that bad actors will employ techniques like adversarial machine learning and data poisoning to hack our AI systems.
https://www.datanami.com/2020/07/28/hacking-ai-exposing-vulnerabilities-in-machine-learning/
