Conference: Hawaii International Conference on System Sciences (HICSS-56) | January 3-6, 2023*Minitrack: Human-centered Digital Privacy Solutions for Digital and Social Media**Track: Digital and Social Media**Submission Deadline: June 15, 2022 (11:59 PM HST)* The burgeoning growth of artificial intelligence (AI) and machine learning (ML) solutions, the ubiquity of social media and digital repositories, and cross-platform data usage have raised the stakes of addressing digital privacy. Semi-structured digital records, like emails, and unstructured text, like social media posts, present a significant threat of privacy breaches. The enormity of data presents an uphill task to identify and mitigate private information on digital and social media platforms. While AI-powered privacy solutions are a welcomed step, it is only recently that researchers have focused on more human-centered and transdisciplinary (Polk, 2015) digital privacy solutions. Privacy protection is a legal and ethical responsibility of both public and private sector organizations, and AI development and deployment should account for the diversity of the target audience, the cultural contexts, and extant biases (Ehsan et al., 2021). Privacy solutions should not only be effective and accurate but also human-centered and accountable (Hepenstal et al., 2019). This minitrack aims to attract submissions on digital privacy solutions that bring different disciplines together, especially computer science, system sciences, information science, social science, and law. The focus of this minitrack is to bridge the gap between algorithmic development (automated decision-making systems, fair, accountable, and transparent systems) and human-centered approaches (usability studies, surveys, user interviews). We encourage submissions that address privacy concerns in digital and social media through inter- and trans-disciplinary approaches, including but not limited to AI and ML. Potential submissions for this minitrack should address (but are not limited to) the following research topics: - quantitative, qualitative, and computational studies on digital (e.g., images, webpages, emails, websites) and social media (e,g., Instagram, Twitter, Reddit, Facebook, TikTok, Weibo) privacy; - qualitative studies using interviews, surveys, and usability studies to identify the privacy behavior of users (when using digital and social media); - quantitative work on digital privacy using statistical analysis; - machine and deep learning approaches to identify, classify, and mitigate sensitive and private information on digital and social media platforms; - novel privacy solutions using explainable AI, transparent ML algorithms, or any interdisciplinary methods. Minitrack Chair and Co-Chairs: Dr. Souvick Ghosh San Jose State University, USA souvick.ghosh@sjsu.edu Dr. Darra Hofman San Jose State University, USA darra.hofman@sjsu.edu Dr. Aylin Imeri (Ilhan) Heinrich Heine University Düsseldorf, Germany Aylin.ilhan@hhu.de Dr. Michele A. L. Villagran San Jose State University, USA michele.villagran@sjsu.edu