Socially Responsible Natural Language Processing

Yulia Tsvetkov, Vinodkumar Prabhakaran, Rob Voigt

Abstract: As language technologies have become increasingly prevalent in analyzing online data, there is a growing awareness that decisions we make about our data, methods, and tools often have immense impact on people and societies. This tutorial will provide an overview of real-world applications of Natural Language Processing technologies and their potential ethical implications. We intend to provide the researchers with an overview of tools to ensure that the data, algorithms, and models that they build are socially responsible. These tools will include a checklist of common pitfalls that one should avoid, as well as methods to mitigate these issues. Issues of bias, ethics, and impact are often not clear-cut; this tutorial will also discuss the complexities inherent in this area.