photo of Jane smiling

As a Human-Computer Interaction researcher, I design and build social computing systems (e.g., social media, workplace software) that are grounded in affirmative consent, an idea that a person or a system must ask for, and earn, enthusiastic approval before interacting with an individual. The key idea behind my research agenda is that communication and process for obtaining consent is inseparable from addressing a wide range of socio-technical problems. Specifically, technologies enable or exacerbate two classes of problems that negatively impact society. The first is interpersonal harm people cause one another, such as technology-mediated abuse and online harassment. The second is institutional exploitation of users, especially with the rise of AI, such as companies’ invasive tracking and inferences of user information. Both are closely related to people’s consent (e.g., "Do I decide to interact with this user?", "Do I opt into giving companies my data?"). Thus, consent is an important concept to define when it comes to software and policy design.

My research defines theoretical properties of affirmative consent (affirmative consent is voluntary, informed, revertible, specific, and unburdensome) and provides design ideas on how to encode them into software (CHI 2021). Based on the ideas, I build systems to ensure people's consent boundaries are protected during interactions—especially in contexts where individuals need to make high-risk decisions, such as navigating abuse of power in workplace settings (CHI 2024 LBW, ongoing work). In another line of work, I focus on users' consent in the context of companies' business interests and profits. Because many tech companies profit from users' data without their affirmative consent, I design interfaces to help users make more informed and less burdensome data-related consent decisions (CHI 2023, CHI 2024). I also study how users perceive social media’s business models, which are a basis for companies’ power (ongoing work).

I am a Ph.D. candidate at the University of Michigan School of Information and the Department of Computer Science & Engineering, where I am advised by Professor Kentaro Toyama. I am a Meta Research PhD Fellow (selected on my fourth try) and a University of Michigan Barbour Scholar, and was also named an EECS Rising Star. My PhD research gave practical help to founders of new social media, and my internship research impacted Meta's privacy strategy. I also co-wrote a grant proposal with Professor Florian Schaub (grant PI) that led to winning an unrestricted gift ($75,000) from Google. I am on the academic job market for 2024-2025.

  • Below is a list of recent updates, which admittedly focuses on good news. I think it's important to share bad news as well, to normalize vulnerabilities, rejections, and failures. While it's far from perfect, you can glimpse more of my honest thoughts on this page.
  • 05/21/2024: Relieved and happy to say we successfully hosted the panel on PhD advising at CHI! Other updates -- I'll be traveling in June to attend CSST. I was also selected to attend the Heidelberg Laureate Forum.
  • 03/01/2024: Excited that a panel proposal and a Late-Breaking Work—both related to improving advising relationships between PhD students and faculty—are accepted to CHI 2024! The panel is with Kentaro Toyama, Himanshu Zade, Pamela Wisniewski, and Steve Oney, and the LBW is with Kentaro. A big thank you to Kentaro for mentoring and collaborating with me on both! Please come to the hybrid panel (updates coming soon) and find me at the poster session (I'm attending in-person)! 😊
  • 02/24/2024: This week, I visited Hyejin Youn's group at Northwestern's Kellogg School of Management to give a presentation. The visit experience was thought-provoking, especially as I switched from Business to HCI/Information/CS. I genuinely enjoyed meeting researchers in the group—many thanks for the invite, Professor Youn!

Selected First Author Publications

Full Papers
Less is Not More: Improving Findability and Actionability of Privacy Controls for Online Behavioral Advertising
Jane Im, Ruiyi Wang, Weikun Lyu, Nick Cook, Hana Habib, Lorrie Cranor, Nikola Banovic, Florian Schaub
CHI 2023
Covered by The Wall Street Journal (The article is behind a paywall, but UMSI also wrote about it here.)
Invited by FTC to present to policymakers at PrivacyCon 2024

Yes: Affirmative Consent as a Theoretical Framework for Understanding and Imagining Social Platforms
Jane Im, Jill Dimond, Melody Berton, Una Lee, Katherine Mustelier, Mark Ackerman, Eric Gilbert
CHI 2021
Best Paper Honorable Mention
I want to give a shoutout to the incredible Una Lee. This work builds on and could not have existed without Una's impactful work on consentful technologies. Una introduced the term "consentful technology"—which inspired many people, including me.
pdf - project website: (over 1,300 people visited since Feb. 2022) - CHI slides - talk

Extended Abstracts
Understanding How to Design a Social Computing System That Helps PhD Students Collectively Navigate Mistreatment or Abuse in Advising Relationships
Jane Im, Kentaro Toyama
CHI 2024 Extended Abstract (Late-Breaking Work)
pdf - talk

Improving Advising Relationships Between PhD Students and Faculty in Human-Computer Interaction
Jane Im, Himanshu Zade, Steve Oney, Pamela Wisniewski, Kentaro Toyama
CHI 2024 Extended Abstract (Panel Proposal)

Selected Co-Authored Publications
I mentored the lead author for the following work.

"I know even if you don't tell me": Understanding Users' Privacy Preferences Regarding AI-based Inferences of Sensitive Information for Personalization
Sumit Asthana, Jane Im, Zhe Chen, Nikola Banovic
CHI 2024

See all publications/projects

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