Tracing Words, Tracking People: Ethical Concerns in AI-Driven Demographic Profiling

DESCRIPTION OF SESSION

Once a tool for literary analysis and forensic linguistics, stylometry has evolved into a powerful AI-driven technique for authorship attribution, plagiarism detection, and demographic profiling. With the integration of natural language processing (NLP) and deep learning, researchers now use stylometry to screen for mental health conditions, predict neurological disorders, and infer personal attributes such as gender identity and national origin. These advancements, while powerful, raise significant ethical concerns around privacy, consent, and bias, as stylometric methods can prospectively uncover identities from seemingly anonymous data. This talk will explore the history and future of stylometry, discussing key applications, emerging methods, and controversial uses, while addressing the ethical principles that should shape research ethics oversight. Attendees will gain a clearer understanding of stylometry's potential and the ethical safeguards required for responsible research implementations.