The Dark Patterns Tip Line is led by a team of designers, academic researchers, legal experts, policy specialists, and advocacy-minded individuals.
We came together to collect dark patterns to better understand how technology is exploiting people. Our ultimate vision is to leverage this data to combat manipulative practices online through policy reform.
We have grounded this work by highlighting examples from people’s lived experiences so we can best showcase how dark patterns lead to every day human harms.
The submissions will be populated and used in a research and academic capacity with students, fellows, and faculty who will be managing the governance and data use. Sharing a dark pattern you have spotted helps us learn more about interfaces and designs that people consider to be manipulative or unfair. We may use your submission to the Dark Patterns Tip Line platform as part of research, or to illustrate and explain dark patterns to the public, the media and policymakers. All submissions are reviewed prior to being posted to the website; submissions may be rejected due to quality or clarity issues, or if they are duplicates of existing postings. We will edit your submission for clarity, and in some cases, we will combine submissions that feature the same dark pattern. Published submissions illustrate a single example from a single company, although we may in fact receive multiple submissions featuring that example/company.
When you submit a tip, you agree that we may use, share and make public your screenshot(s) and other information you share (except for your email address). We publish tips anonymously and will make efforts to remove any personal information, but please don’t submit screenshots that contain information you wouldn’t want to be made public. If you decide to share your email address with us, we may contact you to ask for more information.
We Ground Our Work In Human-Centered Perspectives.
Perspectives of everyday people is missing from dense, legal, and wonky conversations about dark patterns. This project is powered by research with individuals who suffered dark pattern-instigated harms.
We Collaborate Across Teams And Functions.
People across industries are working together to better understand how dark patterns hurt people. Our team includes designers, academic researchers, legal experts, students, community members, policy specialists, and advocacy-minded individuals.
We Value Both Qualitative And Quantitative Data To Create Impact.
The Dark Patterns Tip Line was founded to serve as a crowdsourcing platform where people submit dark patterns they’ve encountered. The data collected is supplemented with qualitative analysis via one-on-one interviews to better understand the human impact of these malicious tactics.
Director, Digital Civil Society Lab at Stanford Center on Philanthropy and Civil Society
Privacy and Data Policy Fellow, Stanford Institute for Human-Centered Artificial Intelligence
Professor of Computer Science, Stanford University Associate Director, Stanford Institute for Human-Centered Artificial Intelligence
Program Manager, Digital Civil Society Lab at Stanford Center on Philanthropy and Civil Society
Research Assistant, Stanford Institute for Human-Centered Artificial Intelligence
The DPTL launched in May 2021 as an experiment, supported by Rita Allen Foundation, AccessNow, Consumer Reports, EFF, and PEN America. That experiment yielded hundreds of submissions. The Digital Lab at Consumer Reports helped incubate the site during this experimental phase. In July, 2021 the site moved to DCSL to become a permanent resource for teaching and learning about deceptive design in digital systems.
DCSL is grateful to the inaugural community partners who made the site possible. We thank Stephanie T. Nguyen, who led the vision and execution of the project and those individuals who contributed time to help with the website strategy and launch of this project — in alphabetical order by last name: Matt Bailey, Harry Brignull, Jennifer Brody, Sage Cheng, Amira Dhalla, Dennis Jen, Arunesh Mathur, Katie McInnis, Jasmine McNealy, Shirin Mori and Ben Moskowitz.