About us

The Digital Due Process Clinic provides high-quality, pro bono services to people struggling with automated scoring systems. Based at Cornell University, the program brings together multidisciplinary teams of students who work on real-world problems under the supervision of experienced faculty.

Why Digital Due Process?

Automated scoring systems play an increasingly important role in ordering our lives. Obtaining a loan, renting an apartment, ranking in web search results, or making the shortlist for a job: all of these activities depend on judgments generated through a range of computational techniques like data analytics and predictive algorithms.

Problems do occur when things go wrong and people feel misrepresented by these systems. For example, what recourse does a person have when:

Cassidy McGovern (left) and Clinical Fellow Ranjit Singh

In all these cases, the affected parties struggle to obtain what legal scholars call “due process,” i.e. the right not to be judged arbitrarily and to appeal an automated judgment. When systems are complex, proprietary, and opaque and legal recourse is impractical or limited, a special kind of expertise is needed to represent one’s interests.

The Digital Due Process Clinic aims to fill this gap by gathering a multidisciplinary group of students under the supervision of experienced faculty and engaging them in research, advocacy, and outreach, using the tools of humanists, technologists, and social scientists.

The 2022 Cohort

Photo of Aadi Kulkarni

Aadi Kulkarni

Student Researcher

Photo of Joanna

Joanna Moon

Student Researcher

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Kerry Wong

Student Researcher

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Kuunemuebari Mini

Student Researcher

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Nabiha Qureshi

Student Researcher

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Noor-E-Jehan Umar

Student Researcher

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Vicki Xie

Student Researcher

Project: Humans of AI

The 2021 Cohort

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Carson Crane

Student Researcher

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Christopher Chandra

Student Researcher

Grace Cala

Student Researcher

Photo of Hannah Dominguez

Hannah Dominguez

Student Researcher

Photo of Sam Tesfaye

Sam Tesfaye

Student Researcher

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Stephen Yang

Student Researcher

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Valerie Kong

Student Researcher

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Michael Tyrrell

Summer Research Fellow

Project: Everyday Ecologies of Scoring: An Exploratory Map

The (Inaugural) 2020 Cohort

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Amy Eng

Student Researcher

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Annika Pinch

Student Researcher

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Cassidy McGovern

Student Researcher

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Ciarra Lee

Student Researcher

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Kyra Wisniewski

Student Researcher

Headshot of Deana Gonzales

Deana Gonzales

Student Researcher

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Emma Li

Student Researcher

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Sterling Williams-Ceci

Student Researcher

Project: Documenting the Lived Experiences of Data Subjects

The Team

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Chris Hesselbein

Graduate Teaching Fellow

Malte Ziewitz

Director; PI

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Yue Zhao

Graduate Research Fellow

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Carson Crane

Undergraduate Research Assistant

Interested in joining us? Applications for the next spring cohort will open in October 2022. If you are thinking about a summer project or an independent study, please send a one-page outline to dueprocess@cornell.edu.


Ngai Keung Chan, Graduate Summer Fellow, 2020 (now: Chinese University of Hong Kong)
Ranjit Singh, Clinical Research Fellow, 2019–2020 (now: Data & Society Research Institute)
Kyla Chasalow, Undergraduate RA, 2019–2020 (now: Oxford M.Sc. Statistics)
August Chang, Student Researcher, 2020 (now: Chicago M.A. Anthropology)
Divyansha Sehgal, Student Researcher, 2019 (now: Deutsche Bank)

Learning objectives

The Digital Due Process Clinic is a setting in which students:

  • assume primary responsibility for deliverables and client matters
  • provide excellent support and representation to those affected by automated scoring systems
  • develop key digital advocacy skills, including interviewing, counseling, fact investigation, drafting, negotiation, and, in some cases, technological support
  • engage in reflective practice, showing the ability to evaluate past performances and continually improve future performances through planning
  • collaborate with other clinic students, clinic supervisors, and community partners


The Digital Due Process Clinic is generously supported by a National Science Foundation CAREER award and the Department of Science & Technology Studies at Cornell University.

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