Course Offerings

An introduction to sociotechnical perspectives on information systems, their effects, and how we intervene to make them better.

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Online communities are important to our cultural, social, and economic lives and especially to how we find and share information. Yet they also threaten our well-being and may undermine critical social institutions as well as the integrity of public discourse. This course is an interdisciplinary inquiry that seeks to understand online communities. It covers the history of online communities from their origins in the pre-Internet to the rise of social media platforms and contemporary challenges and also the social, psychological, and human-computer interaction research that both explains the practical barriers to building an online community and motivates technical and organizational designs that aim to overcome them.

Explore common data collection, management, and sharing practices around information technology and emerging technologies such as AI. Students will gain hands on experiences with collecting, analyzing, and managing user data in ethical and responsible manners. Students will design data-driven systems that are centered around user consent, transparency, and social responsibilities.

Critical exploration of the intersection between digital technologies and information access in emerging economies. Investigate the historical, socio-economic, and ethical dimensions of digital adoption in the Global South, analyzing its impact on governance, economies, cultures, and societal dynamics. Emphasis on critical thinking, ethical considerations, and collaborative approaches to address challenges such as the digital divide(s), data sovereignty, and technology-driven inequality. Through case studies and practical exercises, students will develop skills in digital research, global cultures, policy analysis, and technology innovation with a focus on promoting inclusive and sustainable digital transformation in Global South contexts. Also offered as I 320J.

Practical skills and understandings required to effectively work with open source software and understand the projects that build them. Includes git-based collaboration as well as conceptual understanding of licenses, security, technical and social processes in open source development. Class projects involve working with digital trace data from open source repositories. Also offered as Informatics 320D.

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This course examines disability beyond digital accessibility (i.e., web accessibility, user interface design) and focuses on disability from an organizational and socio-technical point of view. Students will learn about the legislation and policies impacting accessibility, the models that shape our perceptions of disability, and review case studies of disability in several contexts. In addition to the broader types of disabilities, we will consider other forms of disabilities (permanent, situational, temporary). Students will engage in class discussions, small group activities, homework assignments, and give oral presentations. Students will be equipped with the knowledge and skills to apply methods and models of accessibility in the workplace in various fields, including software design, data science, AI, and library science.

This class explores how to make arguments about and through design. The first half focuses on values, criticism, ethics, and analysis of technology, the latter portion aims to help a soon-to-graduate technologist envision positive social impact in a mission-driven enterprise. Students will practice synthesizing ethical tech considerations – as they will have to do for the rest of their careers – and combining this with an organizational mindset. Through exercises, role-playing, discussions, guest lectures from activist technologists, and wide-ranging readings, students will practice connecting broader implications of their designs with technical choices. Design for Social Impact seeks to arm students with diverse ways of reflecting on their authorial relationship to technology, drawing from art and design to political science and anthropology. Course participants will be encouraged to focus on areas of personal interest, enumerating the social, political, and economic parameters of particular technical systems: parameters that are as important as power consumption, usability, or efficiency.

Effective application of social and technical methods of analysis to specific existing systems with inseparable technical and social components to enable improvement. Covers techniques such as modeling, interviewing, observation, trace analysis, and benchmarking.

The class focuses on developing problem solving skills using Python as a programming language. Starting from procedural function development, we also explore object-oriented techniques, and discuss simple data structures that are often used in software development. The students usually do a few programming assignments, take a midterm, and submit a final project.

Database is the foundation of Data Science. It provides the unique design to store, retrieve, and manage data. Data become the essential gas to power the generative AI. How to model data, encode context, enforce business rules, and achieve efficiency are critical for database design. This course provides the introductory understanding of relational database design with the focus on three parts. The first part is centered around the database design lifecycle by introducing business rules, ER diagram, normalization, and UML chart. The second part talks about database query language SQL by explaining concepts and providing examples. The third part gives you the forward introduction of XML database which is the commonly used NoSQL database. The learning content will be delivered in the variety of exercises including lectures, tutorials, class activities, individual assignments, group assignments, and group projects. This course empathizes peer learning, hands-on practices, forward exploring, and risk taking.

Infrastructure is all around us, even (or perhaps especially) where we do not actively consider or account for it. In this course, students will learn how knowledge infrastructures such as repositories, classification systems, databases, networks, standards, and/or metadata both shape and are shaped by governmental policy, institutional decision making, technical advances, and professional and personal value systems. We consider how infrastructure matters in professional, personal, and political life, and employ infrastructure as a lens to evaluate and understand the legal, ethical, and policy consequences of knowledge work, data science, and information management. In this course, students will employ an infrastructural perspective to evaluate programs, systems, policies, and/or organizations. We will explore the consequences and societal impact of knowledge work at both global and local scales, and consider how infrastructure might be built or refined to support societal or organizational goals such as social justice, privacy, innovation, health, or security. This is primarily a discussion-oriented course, with assessment primarily coming through a multi-stage, semester-long, project oriented around a program evaluation.

Ethnographic research has found application and acceptance across various academic disciplines as well as industries. This course aims to introduce fundamental tenets of ethnographic methodology for investigating sociotechnical systems. Its foundation rests on interdisciplinary perspectives and anthropological insights, while simultaneously aligning with contemporary advancements such as design and speculative ethnography. The role of the future has perpetually held a central position in the utilization and shaping of technologies and information systems. A recurring narrative involves positioning a specific technology or system as "revolutionary" or "the future of" a certain domain. Adopting an ethnographic approach, this course seeks to critically examine sociotechnical imaginaries. Its objective is to glean insights from diverse communities, offering guidance in the construction of futures that are more inclusive, equitable, and diverse.

Ethnographic research has found application and acceptance across various academic disciplines as well as industries. This course aims to introduce fundamental tenets of ethnographic methodology for investigating sociotechnical systems. Its foundation rests on interdisciplinary perspectives and anthropological insights, while simultaneously aligning with contemporary advancements such as design and speculative ethnography. The role of the future has perpetually held a central position in the utilization and shaping of technologies and information systems. A recurring narrative involves positioning a specific technology or system as "revolutionary" or "the future of" a certain domain. Adopting an ethnographic approach, this course seeks to critically examine sociotechnical imaginaries. Its objective is to glean insights from diverse communities, offering guidance in the construction of futures that are more inclusive, equitable, and diverse.

*THIS TOPIC WILL NO LONGER BE OFFERED AFTER SPRING 2025In this course, we will work to understand and address the challenges of misinformation, disinformation, and strategic manipulation in online environments. First, we will work to develop a deep understanding of the problem space. We will read and discuss existing research (both historical and contemporary) on how and why misinformation and disinformation spread. Next, we will explore the process, both personal and interpersonal, by which these issues can be approached and addressed in our own lives. This will involve reflecting on our own presuppositions, beliefs, and biases about information; and doing a project in which we apply the principles of Human-Centered Design to investigate different design directions for addressing misleading information. Students will gain important contextual knowledge and hands-on design experience that they can take into future professional domains (from education to policy to technology), where they can contribute to building more trustworthy information systems.

Data storytelling is more than sharing data—at its most simple, it’s about designing charts and tables that make sense to the people who will be using them and help those people make better, faster decisions. While making a chart is as easy as a few clicks, doing it well requires much more. There is a science to how our eyes and minds process information as well as an art to making good graphic design choices. This comes together in an effective data presentation when the work is readable, usable, and above all actionable—not just aesthetically pleasing (though we’ll certainly address that too). As information professionals, we are well-positioned to understand and design for the needs of our users, to interrogate our data sources thoughtfully, and to ask future-thinking questions. This course will also draw on elements from cognitive psychology, user experience, data journalism, graphic design, business, and more. This multidisciplinary approach will take us on a grand tour that will touch on many aspects of data analysis and will serve as an excellent introduction to other data-oriented courses in the iSchool master’s program.

Data storytelling is more than sharing data—at its most simple, it’s about designing charts and tables that make sense to the people who will be using them and help those people make better, faster decisions. While making a chart is as easy as a few clicks, doing it well requires much more. There is a science to how our eyes and minds process information as well as an art to making good graphic design choices. This comes together in an effective data presentation when the work is readable, usable, and above all actionable—not just aesthetically pleasing (though we’ll certainly address that too). As information professionals, we are well-positioned to understand and design for the needs of our users, to interrogate our data sources thoughtfully, and to ask future-thinking questions. This course will also draw on elements from cognitive psychology, user experience, data journalism, graphic design, business, and more. This multidisciplinary approach will take us on a grand tour that will touch on many aspects of data analysis and will serve as an excellent introduction to other data-oriented courses in the iSchool master’s program.

Processes, techniques, and technologies that generate inscriptions (ready-to-take data), especially from or about people(s) or culture(s). Contexts, consequences, and history of datafication practices. Purposive intervention with datafication processes, practices, and artifacts.

Processes, techniques, and technologies that generate inscriptions (ready-to-take data), especially from or about people(s) or culture(s). Contexts, consequences, and history of datafication practices. Purposive intervention with datafication processes, practices, and artifacts.

Artificial intelligence (AI) is both a product of and a major influence on society. As AI plays an increasingly important role in society, it is critical to understand both the ethical factors that influence the design of AI and the ethical dimensions of the impacts of AI in society. The goal of this course is to prepare students for the important ethical responsibilities that come with developing systems that may have consequential, even life-and-death, consequences. Students first learn about both the history of ethics and the history of AI, to understand the basis for contemporary, global ethical perspectives (including non-Western and feminist perspectives) and the factors that have influenced the design, development, and deployment of AI-based systems. Students then explore the societal dimensions of the ethics and values of AI. Finally, students explore the technical dimensions of the ethics and values of AI, including design considerations such as fairness, accountability, transparency, power, and agency. Students who perform well in this class will be positioned to take on a leadership role within their organizations and will be able to help guide and steer the design, development, and deployment of AI-based systems in ways that benefit users, other stakeholders, their organizations, and society. The knowledge and skill gained through this course will benefit students throughout their careers, and society as a whole will benefit from ensuring that studenrs are prepared to consider the important ethical dimensions of their work.

This course examines the U.S. communication policy in light of domestic and international structural, economic and technological changes. We will investigate how notions of control, access and expression have changed during the 20th and the 21st centuries, examining communication policies and regulation against a backdrop of technological innovation. The definitions and controversies around what constitutes the public interest intersect with policies for specific media systems including broadcasting, cablecasting, the Internet and social media, among others. The cultural ramifications of communication systems in terms of their impacts on people and on speech are a related domain we will address. At the current moment, issues around privacy, large tech companies and their role in contemporary life, the limits and authority of regulation, and of course social media,AI and ‘big data’ dominate many political and research agendas. Our goal will be to understand the backgrounds and foundations that bring us to these concerns and to frame them in critical ways.