Teaching Tech Policy requires a unique combination of studying public policy, public administration, and regulatory governance concepts, along with conceptualization of core issues related to each policy field. On top of that, students need hands-on experience to be able to counter tech policy issues in real world settings.
To do so, our Hub offers an array of undergraduate & graduate level classes, taught by our affiliated faculty. The offered courses are listed below:
INST 756 – Information Risk Management:
This class is taught by Prof. Sivan-Sevilla to offer students real-world experience in wrestling with information risk management challenges. The information revolution has been creating and amplifying risks for organizations. In this experiential learning-based class, the first four weeks aim to create a foundational understanding of the causes, treatments, and challenges in three main information risk domains: (1) cybersecurity, (2) privacy, and (3) ethics, based on the International Risk Governance Council (IRGC) framework. We will then discuss the art of project management and match groups of students with real-world clients to assist in an information risk problem during the semester. Students will learn about the causes and risk factors of different information risks, the methods to mitigate and prevent those risks, and apply their skills to provide a well-studied consultancy-level report on an information risk problem for their client. By the end of the class, students are expected to have a rounded understanding of contemporary information risks and practical experience on how to address those issues in the real world. In past semesters we had clients such as Keystone Strategy & Maryland’s Department of Information Technology.
INST 771 – Foundations of Cybersecurity: [Syllabus available here]
This class is taught by Prof. Sivan-Sevilla to enable students with no technical background develop a deep understanding of core technical and regulatory concepts regarding cybersecurity.The rapid and widespread growth in computation, connectivity, and digital storage capacities created a new human-made domain – c yberspace. The cyberspace domain challenges traditional assumptions, boundaries, and opportunities for social life. Most notably, cyberspace changes the meaning, methods, and trust assumptions necessary to achieve security and protect our privacy. Cybersecurity, then, is not merely ‘security in cyberspace.’ It is the study of how and why the human transition to cyberspace changes security risk assumptions and how to respond to those challenges. The purpose of this class is to provide the fundamentals for understanding the core technical and social components that construct the cybersecurity problem. We will unpack the concepts of vulnerabilities & exploits; discuss their manifestation in different operating systems, supply chain providers, and computer networks; learn how to measure the severity of vulnerabilities; detail the hacking process and corresponding threat intelligence; learn about main threats in the threat landscape; and discuss how and why cybersecurity is governed across top-down & bottom-up governance arrangements. We will start with understanding what is unique about cyberspace [module #1], explain what is at the core of technical cyber insecurity: exploits and vulnerabilities across mobile, desktops, servers, networks, and third-party software [module #2], overview of the hacking process and corresponding threat intelligence [module #3], survey the threat landscape from nations, criminals, and hacktivists [module #4], and explain what is currently being done for governing the cybersecurity problem across top-down and bottom-up governance mechanisms [module #5]. By the end of this class, students will have a comprehensive understanding of the cybersecurity problem, its history, core components, technical solutions, threat intelligence, and up-to-date governance mechanisms.
INST 878 – Governing Algorithms and Algorithmic Governance: [Syllabus available here]
This class is taught by both Prof. Sivan Sevilla (INFO) & Prof. Gabriel Kaptchuk (CS). It is a cross-cutting interdisciplinary course, taught jointly between the College of Information Studies and the Department of Computer Science, investigating the role that algorithms and automated decision-making systems play in markets, societies, and policymaking, and shedding light on the technologies we have to address their unintended consequences. The course connects policy and computational conceptualizations of transparency, security, fairness, privacy, manipulation, and accountability through a series of case studies and burning debates. Students will collaborate cross-disciplinary and be encouraged to work through difficult trade-offs to reach consensus. By discussing recent applications of algorithms for social and consumer sorting, and the moderation and generation of content, all in the context of the technologies designed to address algorithmic harms, students will engage with the pressing challenges and opportunities in the governance of and by algorithms. In the first module we will address the integration of algorithms in society, their harm, and the limitations of law, policy, and regulation to address them. We then dive into our case subjects: The second module is designed around machine learning decisions on societal outcomes and what to do about it, unpacking computational and non-computational tools to address machine harms. The third module is about the right to privacy in the use of algorithms – what is the actual problem, how agencies & industries are dealing with and what regulators are trying to do, using the European General Data Protection (GDPR) as the case study and the computational and non-computational tools that are deployed to govern for privacy in our algorithmic society. The fourth module is dedicated to the role of technology in regulating society. We will discuss evidence-based policymaking and its limitations, and how to use technology to advance the (loosely defined) public interest.
