“Does This Vehicle Belong to You?” Processing the Language of Policing for Improving Police-Community Relations
Police body-worn cameras have the potential to play an important role in understanding and improving police-community relations. In this talk I describe a series of studies conducted by our large interdisciplinary team at Stanford that use speech and natural language processing on body-camera recordings to model the interactions between police officers and community members in traffic stops. We use text and speech features to automatically measure linguistic aspects of the interaction, from discourse factors like conversational structure to social factors like respect. I describe the differences we find in the language directed toward black versus white community members, and offer suggestions for how these findings can be used to help improve the fraught relations between police officers and the communities they serve.
Dan Jurafsky (BA linguistics '79, UC Berkeley; Ph.D. computer science ’92, UC Berkeley) is professor and chair of linguistics and professor of computer science at Stanford University. His research has focused on the extraction of meaning, intention, and affect from text and speech, on the processing of Chinese, and on applying natural language processing to the cognitive and social sciences. Dan is very interested in NLP education, and he co-writes the widely-used textbook Speech and Language Processing and co-taught the first massive open online class on natural language processing. The recipient of a 2002 MacArthur Fellowship, Dan is also a 2015 James Beard Award Nominee for his book The Language of Food: A Linguist Reads the Menu.