1 Introduction
2 Causality Characteristics and Uniqueness
3 Causality Types, Relationships and Inference
4 Causality Applications and Usages
5 Preconditions and Architecture for Implementing Causality on Datasets
6 Causality Evaluation and Metrics
7 Causality Trustworthiness
8 Causality and Explainable AI (XAI)
9 Causality and Machine Learning (ML), AI, Genetic Algorithms (GA), and Generative AI (GAI) Approaches
10 Causality and Big Data
11 Causality and Reinforcement Learning (RL)
12 Integration between Causality, Machine and Deep Learning, and Genetic Algorithms
13 Causality and Generative AI (GAI)
14 Causality and Fuzzy Logic
15 Conclusions and Future Directions