Jefferson Institute's Military Archives Project in Serbia: From Ruins of War, a Nation's History Preserved

Analyzes the impact and challenges of a project supported by Knight to digitize Serbia's military documents and make them publicly available in a searchable archive, including evidence for prosecuting war criminals and locating secret mass graves

J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News

The rapid proliferation of AI-generated text online is profoundly reshaping the information landscape. Among various types of AI-generated text, AI-generated news presents a significant threat as it can be a prominent source of misinformation online. While several recent efforts have focused on detecting AI-generated text in general, these methods require enhanced reliability, given concerns about their vulnerability to simple adversarial attacks. Furthermore, due to the eccentricities of news writing, applying these detection methods for AI-generated news can produce false positives, potentially damaging the reputation of news organizations. To address these challenges, we leverage the expertise of an interdisciplinary team to develop a framework, J-Guard, capable of steering existing supervised AI text detectors for detecting AI-generated news while boosting adversarial robustness. By incorporating stylistic cues inspired by the unique journalistic attributes, J-Guard effectively distinguishes between real-world journalism and AI-generated news articles. Our experiments on news articles generated by a vast array of AI models, including ChatGPT (GPT3.5), demonstrate the effectiveness of J-Guard in enhancing detection capabilities while maintaining an average performance decrease of as low as 7% when faced with adversarial attacks.Comment: This Paper is Accepted to The 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2023

VIRAL HEALTH MISINFORMATION FROM GEOCITIES TO COVID-19

Although often discussed in the public discourse as a phenomenon newly exacerbated by social media, the use of the Internet to spread health-related misinformation is as old as the Internet itself. Techniques, networks, and narratives from prior novel health outbreaks such as HIV or Ebola continue to circulate and are repurposed in the current COVID-19 pandemic. We examine and compare two case studies of health misinformation — HIV mis/disinformation in from the mid-1990s to early 2000s circulating in GeoCities and the role of official COVID-19 Dashboards in present-day COVID-19 mis/disinformation. This contributes to our understanding of current and historical health misinformation as well as the connections between them