Special Topics in Information

In this class students will continue research projects from INFO 217A. HCI research. The class includes weekly one-on-one meetings with each project team. Students will read literature related to their project assigned by the instructor and continue their projects. The final deliverable for the class will be a full conference or journal paper.

Biosensory computing is the multidisciplinary study and development of systems and practices that sense, represent, communicate, and interpret biological signals from the body.

Biosignals are expansive in scope, and can enable a diverse range of biosensory computing applications. They can include physiological (e.g., ECG/PPG, EDA, EEG) and kinesthetic signals (e.g., accelerometry, eye gaze, facial expressions). Many inferences can be drawn about the person from these signals, including their activities, emotional and mental states, health, and even their identities, intentions, memories, and thoughts.

While generated by the person, biosensory data have important characteristics that distinguish them from other types of user-generated data. They are intimate yet leakable, precise yet ambiguous, familiar yet unverifiable, and have limited controllability. Therefore, responsible stewardship of biosensory data must be in place before the full potential of biosensory computing can be realized.

This multidisciplinary course will explore the intellectual foundations and research advances in biosensory computing. We will survey the range of biosensing modalities and technologies, study temporal and spectral data analysis and visualization techniques, interrogate the designs of novel biosensing applications, and tackle issues of user privacy and research ethics. Students signing up for the 3-unit option will continue in the second half of the semester with a student-led research project.

Our world is rife with misinformation. This is a course about misinformation and “calling bullshit” — spotting, dissecting, and publicly refuting — false claims, but also inferences based on quantitative, statistical, and computational analysis of data. Spotting misinformation; causal fallacies; statistical traps; data visualization; big data; interpreting scientific claims; fake news and social media; refutation techniques. Prior math or statistics background unnecessary.

Peoples and communities around the world will be confronting the challenges of climate change, ecosystem degradation, and biodiversity loss for many decades to come. This course will explore the different ways in which the informatics and computing field can contribute to our individual and collective efforts to mitigate and adapt to the effects of climate change.

Through readings and discussions, students will critically engage with foundational and leading-edge perspectives on diverse topics such as systems thinking for sustainable computing, sustainability in/through design, collapse informatics, fighting climate misinformation and climate anxiety, as well as how knowledge and tools from the fields of machine learning, human-computer interaction, web3, IoT, and remote sensing are being applied to novel solutions in many different settings.

Student-led projects will research the information needs and information seeking behaviors of individuals and communities, both now and into the future, and design information tools and resources to support them in their efforts of climate mitigation, adaptation, advocacy, and education.

The Future of Cybersecurity Working Group (FCWG) assembles students, researchers, and faculty from across the campus with a shared interest in security. We read and discuss the current cybersecurity scholarship and workshop projects related to cybersecurity. Our goal is to support critical inquiry into security and explore how it relates to political science, law, economics, the military, and intelligence gathering. Students are required to participate in weekly sessions, present short papers on the readings, and write response pieces.

This course will explore what HCI knowledge and methods can bring to the study, design, and evaluation of AI systems with a particular emphasis on the human, social, and ethical impact of those systems. Students will read papers and engage in discussions around the three main components of a human-centered design process as it relates to an AI system:

1. needs assessment,
2. design and development, and
3. evaluation.

Following these three main design phases, students will learn what needs assessment might look like for designing AI systems, how those systems might be prototyped, and what HCI methods for real-world evaluation can teach us about evaluating AI systems in their context of use. The course will also discuss challenges that are unique to AI systems, such as understanding and communicating technical capabilities and recognizing and recovering from errors.

Guest lectures will be given by experts in AI ethics (e.g., Timnit Gebru) and fairness, accountability, and transparency in AI systems (e.g., Motahhare Eslami).

For this course, we are going to tackle one of the world’s biggest challenges (voted on by the students). We will organize as an innovation lab tasked with developing new products and so as to better understand the principles, process, and outputs of interaction design. The goal will be to be able to apply the concepts and frameworks we cover in class to a real problem space.

Students will be responsible for developing a robust prototype over the final few weeks of the course. They will also write a reflection on the prototype development process, drawing on the theoretical concepts covered in the course. On the last day of class, students will present their work to a panel of industry experts for feedback.

Markets exert such a ubiquitous force on our daily lives that it can be easy to disregard it, as a fish does water. At the same time, perhaps no other social concept has attracted such a wide range of views, beliefs and critiques, ranging from the idea of markets as self-organizing mechanisms to maximize welfare and happiness, to the idea of markets as a wide-ranging and destructive global force.

This seminar engages with both foundational and contemporary readings across fields such as information economics, social theory, science and technology studies, and information science to contextualize modern developments in markets and marketplaces in the history of economic thought and information. While the course pays attention to classic texts, the goal is to connect ongoing developments in markets and market design to long-standing lines of scholarship across different fields, and to place current developments in their deeper historical context.

This course examines markets as a socially and technologically produced artifact in its own right. Topics include examining the role of markets as information-processing technologies, as social and economic coordination, how markets are maintained and constructed, and concepts of fairness associated with markets and market allocation. The course ends with an examination of digital markets, blockchain technologies and ongoing concerns with digital antitrust and platform power.

In the dynamic and interdisciplinary world where MIMS graduates operate, the ability to consult, pitch, and communicate effectively is paramount. While technological details come and go, these skills remain central to fulfilling interactions with various types of stakeholders, including colleagues, leadership, clients, customers, subject matter experts, as well as one’s broader network on social media. In this world increasingly driven by digital transformation and interdepartmental and cross-functional collaboration, mastering the art of impactful communication becomes not just an advantage, but a necessity.

This course delves into this interdisciplinary nexus with the goal of providing practical and applicable knowledge and techniques, emphasizing the invaluable skill of articulating complex technological concepts to a diverse audience. The course, then, is designed to equip students with the tools and strategies to bridge gaps, influence decisions, and drive innovation through the power of effective communication, including in the creation of one’s own voice and branding.

Focusing on real-world scenarios and practical exercises, students will cultivate both technical and non-technical abilities essential for tech professionals and leaders. The final presentation acts as a summative opportunity to amalgamate core concepts and techniques acquired throughout the program. Projects are built around real-world scenarios and case studies. The course emphasizes enhancing students’ presentation, strategic, and organizational skills, paving the way for their success in the ever-evolving consulting landscape.

Privacy counseling and compliance is a rapidly growing and increasingly important function, both within companies and throughout the legal profession. The task is becoming evermore complex as companies grapple with adherence to new legislation and regulation, as well as local and international standards and norms. This interdisciplinary course seeks to help prepare students for this changing ethical, legal, and regulatory landscape. The academic perspective will be grounded in a real world examination of compliance challenges which will be presented by leading privacy professionals including in-house legal and compliance experts.

This seminar will discuss topics of current interest in the multi-disciplinary field of ubiquitous sensing. The format will include paper discussions, invited lectures from both within and outside the class, and short written assignments. Students will also be responsible for presenting during at least one class session, either on their own research and ideas or on a selected set of papers relevant to the course topic.

This course takes a multi-disciplinary approach to explore the possibilities and limitations of ubiquitous sensing technologies for physiological and contextual data. We will survey the intellectual foundations and research advances in ubiquitous computing, biosensory computing, and affective computing, with applications ranging from brain-computer interfaces to health and wellness, social computing to cybersecurity. We will cover temporal and spectral analysis techniques for sensor data. We will examine data stewardship issues such as data ownership, privacy, and research ethics. Students signing up for the 3-unit option will continue in the second half of the semester with a student-led research project.

How do you create a concise and compelling User Experience portfolio? Applying the principles of effective storytelling to make a complex project quickly comprehensible is key. Your portfolio case studies should articulate the initial problem, synopsize the design process, explain the key decisions that moved the project forward, and highlight why the solution was appropriate. This course will include talks by several UX hiring managers who will discuss what they look for in portfolios and common mistakes to avoid.

Students should come to the course with a completed project to use as the basis for their case study; they will finish with a completed case study and repeatable process. Although this class focuses on UX, students from related fields who are expected to share examples and outcomes of past projects during the interview process (data science, product management, etc.) are welcome to join.