AI Forensics: Did the Artificial Intelligence System Do It? Why?
Johannes Schneider, Frank Breitinger · arXiv (Cornell University) · 2020
In an increasingly autonomous manner AI make decisions impacting our daily life. Their actions might cause accidents, harm or, more generally, violate regulations -- either intentionally or not. Thus, AI might be considered suspects for various events. Therefore, it is essential to relate particular events to an AI, its owner and its creator. Given a multitude of AI from multiple manufactures, potentially, altered by their owner or changing through self-learning, this seems non-trivial. This paper discusses how to identify AI responsible for incidents as well as their motives that might be malicious by design. In addition to a conceptualization, we conduct two case studies based on reinforcement learning and convolutional neural networks to illustrate our proposed methods and challenges. Our cases illustrate that catching AI systems seems often far from trivial and requires extensive expertise in machine learning. Legislative measures that enforce mandatory information to be collected during operation of AI as well as means to uniquely identify might facilitate the problem.