Course Overview

The class is a seminar course on human-centered privacy design and systems. In this class, we will explore the topic of designing and developing privacy-aware digital systems by providing an overview of technical, design, and legal perspectives. Students will learn theoretical frameworks of privacy, privacy design principles, privacy laws, and privacy-enhancing technologies. We will also cover user research methods that are useful for designing and evaluating digital systems that are aware of and respectful to users’ privacy preferences, informed by their lived experiences. In the latter part of this course, we will discuss special topics in human-centered privacy design and system building, including the privacy implications of emerging technologies (e.g., LLM, XR), inclusive privacy design challenges, and engineering support for privacy by design.

Learning Objectives

Privacy issues are becoming a primary concern in the increasingly connected and data-intensive world. This course aims to equip students with the skills and knowledge to manage privacy issues responsibly as researchers and practitioners. Specifically, by taking this course, you are expected to gain:

  • Systematic and human-centered approaches to analyzing privacy challenges in digital systems and emerging technologies.
  • A skill set for proposing practical solutions to privacy challenges using a combination of human-centered design and technical system building.
  • The ability to appreciate, critique, and conduct research at the intersection of HCI and privacy.

Administrivia

Classroom: Richards Hall 228
Time: Monday 6:00-9:20pm
Instructor: Tianshi Li
Office: 177 Huntington Ave, 505
Office Hours: Wednesday 1-2pm

Grading

  • 30% Class Participation
  • 20% Reading Commentaries
  • 10% Discussion Lead (Schedule sheet)
  • 10% DP Assignment
  • 30% Individual project, including
    • 5% Initial idea description
    • 10% Project proposal presentation
    • 15% Final presentation (if you work on an original research project) or literature review manuscript (if you work on a literature review project)

Schedule

Note: The class schedule is tentative and subject to change! Please check the online schedule frequently.

Week Topic Date Reading List Note
Week 1 Introduction 09/08 N/A Discussion lead bidding due on Sept 12
Week 2 Key concepts in privacy 09/15 Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks (CHI 2024)

PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action (NeurIPS 2024)
 
Week 3 Foundations of human-centered privacy 09/22 “My Data Just Goes Everywhere:” User Mental Models of the Internet and Implications for Privacy and Security (SOUPS 2015)

Expectation and purpose: understanding users’ mental models of mobile app privacy through crowdsourcing (UbiComp 2012)
 
Week 4 Privacy and Compliance 09/29 Toggles, Dollar Signs, and Triangles: How to (In)Effectively Convey Privacy Choices with Icons and Link Texts (CHI 2021)

Honesty is the Best Policy: On the Accuracy of Apple Privacy Labels Compared to Apps’ Privacy Policies (PETS 2024)
 
Week 5 Privacy Design Principles 10/06 “I’m not convinced that they don’t collect more than is necessary”: User-Controlled Data Minimization Design in Search Engines (USENIX Security 2024)

Automating Contextual Privacy Policies: Design and Evaluation of a Production Tool for Digital Consumer Privacy Awareness (CHI 2022)
DP assignment released on Oct 6

Initial idea description due on Oct 6
Week 6 USA: Indigenous Peoples Day, no classes 10/13 N/A  
Week 7 Project proposal 10/20 N/A Remote participation
Week 8 Privacy-Enhancing Technologies 10/27 “I need a better description’’: An Investigation Into User Expectations For Differential Privacy (CCS 2021)

Don’t Look at the Data! How Differential Privacy Reconfigures the Practices of Data Science (CHI 2023)
DP assignment due on Oct 29 (Wednesday)
Week 9 AI Privacy (LLM) 11/03 Rescriber: Smaller-LLM-Powered User-Led Data Minimization for LLM-Based Chatbots (CHI 2025)

Granular Privacy Control for Geolocation with Vision Language Models (EMNLP 2024)
 
Week 10 AI Privacy (Agent) 11/10 Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory (ICLR 2024)

When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs (USENIX Security 2025)

Searching for Privacy Risks in LLM Agents via Simulation
 
Week 11 Inclusive Privacy 11/17 “If sighted people know, I should be able to know:” Privacy Perceptions of Bystanders with Visual Impairments around Camera-based Technology (USENIX Security 2023)

Beyond “Vulnerable Populations”: A Unified Understanding of Vulnerability From A Socio-Ecological Perspective (CSCW 2025)
 
Week 12 Designers and developers 11/24 How Developers Talk About Personal Data and What It Means for User Privacy: A Case Study of a Developer Forum on Reddit (CSCW 2021)

Farsight: Fostering Responsible AI Awareness During AI Application Prototyping (CHI 2024)
 
Week 13 Final project presentation 12/01 N/A  

Further readings