This tutorial aims to bring together research from different fields such as computer science and the social sciences and policy to show how counterspeech is currently used to tackle abuse and misinformation by individuals, activists and organisations, how Natural Language Processing (NLP) and Generation (NLG) can be applied to automate its production, and the implications of using large language models for this task. It will also address, but not be limited to, the questions of how to evaluate and measure the impacts of counterspeech, the importance of expert knowledge from civil society in the development of counterspeech datasets and taxonomies, and how to ensure fairness and mitigate the biases present in language models when generating counterspeech.

The tutorial will bring diverse multidisciplinary perspectives to safety research by including case studies from industry and public policy to share insights on the impact of counterspeech and social correction and the implications of applying NLP to critical real-world problems. It will also go deeper into the challenging task of tackling hate and misinformation together, which represents an open research question yet to be addressed in NLP but gaining attention as a stand alone topic.