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Surveying Neural Network Validation through analysis and classification premised on varied standpoints

The future of artificial intelligence is not only limited to the technology itself. It also includes the way we live with this new tech, and how it will shape our future. AI is a powerful tool that can help us make better decisions about everything from healthcare to education. However, it also has its downsides like privacy concerns and bias in algorithms. In this paper, the author dives into the problems associated with the anomalies in the behaviors of machine learning models. They review the different methods in literature to identify such behaviors and prevent them. The author then attempts to verify the authenticity of these methods through three different perspectives. This paper surveys these works with the goal of culling out verification methods capable of addressing major challenges.