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Healthy online discourse is becoming less and less accessible beneath the growing noise of controversy, mis- and dis-information, and toxic speech. While IR is crucial in detecting harmful speech, researchers must work across disciplines to develop interventions, and partner with industry to deploy them rapidly and effectively. In this position paper, we argue that both detecting online information disorders and deploying novel, real-world content moderation tools is crucial in promoting empathy in social networks, and maintaining free expression and discourse. We detail our insights in studying different social networks such as Parler and Reddit. Finally, we discuss the joys and challenges as a lab-grown startup working with both academia and other industrial partners in finding a path toward a better, more trustworthy online ecosystem. 

Most Fairness in AI research focuses on exposing biases in AI systems. A broader lens on fairness reveals that AI can serve a greater aspiration: rooting out societal inequities from their source. Specifically, we focus on inequities in health information, and aim to reduce bias in that domain using AI. The AI algorithms under the hood of search engines and social media, many of which are based on recommender systems, have an outsized impact on the quality of medical and health information online. Therefore, embedding bias detection and reduction into these recommender systems serving up medical and health content online could have an outsized positive impact on patient outcomes and wellbeing. In this position paper, we offer the following contributions: (1) we propose a novel framework of Fairness via AI, inspired by insights from medical education, sociology and antiracism; (2) we define a new term, bisinformation, which is related to, but distinct from, misinformation, and encourage researchers to study it; (3) we propose using AI to study, detect and mitigate biased, harmful, and/or false health information that disproportionately hurts minority groups in society; and (4) we suggest several pillars and pose several open problems in order to seed inquiry inthis new space. While part (3) of this work specifically focuses on the health domain, the fundamental computer science advances and contributions stemming from research efforts in bias reduction and Fairness via AI have broad implications in all areas of society.