Making Socially Sustainable and Ethical AI Systems: Integrating Impact Assessment in the Co-Design Approach -- Discrimination in Advertising and Personalization -- Biases and Ethical Considerations in ML Pipelines In The Computational Social Sciences -- Operationalizing Fairness -- Achieving Group and Individual Fairness in Clustering Algorithms -- Fair Allocation of Structured Set Systems -- Algorithmic Fairness for Decisions Across Time -- Algorithmic Fairness in Multi-stakeholder Platforms -- Fairness Testing, Debugging and Repairing -- Interpretability of Machine Learning Models.