The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing

Although popular and effective, large language models (LLM) are characterised by a performance vs. transparency trade-off that hinders their applicability to sensitive scenarios. This is the main reason behind many approaches focusing on local post-hoc explanations recently proposed by the XAI community. However, to the best of our knowledge,...

Evaluating catastrophic forgetting of state-of-the-art NLP models for predicting moral values

Personal moral values represent the motivation behind individuals' actions and opinions. Understanding these values is helpful both in predicting individuals' actions, such as violent protests, and building AI that can better collaborate with humans. Predicting moral values is a challenging problem due to the abstract and subjective essence of...

Evaluating interpretability of state-of-the-art NLP models for predicting moral values

Understanding personal values is a crucial aspect that can facilitate the collaboration between AI and humans. Nonetheless, the implementation of collaborative agents in real life greatly depends on the amount of trust that is built in their relationship with people. In order to bridge this gap, more extensive analysis of the explainability of...

Estimating the transferability of state-of-the-art models in predicting moral values

Moral values play a crucial role in our decision-making process by defining what is right and wrong. With the emergence of political activism and moral discourse on social media, and the latest developments in Natural Language Processing, we are looking at an opportunity to analyze moral values to observe trends as they form. Recent studies have...