1 Introduction  
2 Trustworthy Machine Learning Topics from Data Perspective  
2.1 Robustness  
2.2 Fairness  
2.3 XAI: Interpretability and Explainability  
2.4 A Theme of Trustworthy Machine Learning from Data Perspective  
3 Trustworthy Machine Learning in Causality Perspectives  
3.1 Background in Causality  
3.2 Intervention: the Second Level  
3.3 Counterfactuals: the Third Level  
3.4 Summary  
4 Trustworthy Machine Learning in the Context of Pretrained Models  
4.1 Large Pretrained Models and Their Trustworthiness Challenges  
4.2 Techniques with Large Models  
4.3 Trustworthy Solutions for Large Models  
4.4 Summary  
5 Applications Where Trustworthy Machine Learning Play Important Roles  
5.1 Vision  
5.2 Language  
5.3 Vision-Language  
6 Conclusion