Agnieszka Faleńska was invited to give a keynote talk at the Institute of Computer Science, Polish Academy of Sciences.
For many, Natural Language Processing (NLP) systems have become everyday necessities, with applications ranging from automatic document translation to voice-controlled personal assistants. Recently, the increasing influence of these AI tools on human lives has raised significant concerns about the possible harm these tools can cause.
In this talk, I will start by showing a few examples of such harmful behaviors and discussing their potential origins. I will argue that biases in NLP models should be addressed by advancing our understanding of their linguistic sources. Then, the talk will zoom into three compelling case studies that shed light on inequalities in commonly used training data sources: Wikipedia, instructional texts, and discussion forums. Through these case studies, I will show that regardless of the perspective on the particular demographic group (speaking about, speaking to, and speaking as), subtle biases are present in all these datasets and can perpetuate harmful outcomes of NLP models.
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