Indian Institute of Technology Hyderabad researchers have developed a method by which the inner workings of Artificial Intelligence models can be understood in terms of causal attributes. 'Artificial Neural Networks' (ANN) are AI models and programs that mimic the working of the human brain so that machines can learn to make decisions in a more human-like manner. Modern ANNs, often also called Deep Learning (DL), have increased tremendously in complexity such that machines can train themselves to process and learn from data that has been supplied to them as input, and almost match human performance in many tasks. However, how they arrive at decisions is unknown, making them less useful when the reason for decisions is necessary. This work has been performed by Dr Vineeth N Balasubramanian, Associate Professor, Department of Computer Science and Engineering, IIT Hyderabad, and his students Aditya Chattopadhyay, Piyushi Manupriya, and Anirban Sarkar. Their work has recently been published in the Proceedings of 36th International Conference on Machine Learning, considered worldwide to be one of the highest-rated conferences in the area of Artificial Intelligence and Machine Learning.