Katie Shilton

Dr. Katie Shilton

Katie Shilton

Associate Professor & Doctoral Program Director
Office: 
Patuxent Building, Room 1109-F
Telephone: 
(301) 405-3777

I lead the Ethics & Values in Design (EViD) Lab at the UMD iSchool. I'm also active in the CASCIIPAC and DCIC research centers. In addition to my research pursuits, I teach courses in information policy, information and technology ethics, and digital curation.

Focus

My research focuses on ethics and policy for the design of information technologies, systems, and collections.

Current Research Interests

  • Social and ethical implications of emerging technologies
  • Information policy
  • Information ethics
  • Social values and technology design

Education

  • B.A. from Oberlin College
  • Master of Library and Information Science from UCLA
  • Ph.D. in Information Studies from UCLA.

Recognition

  • Google Faculty Award
  • NSF CAREER award

CHS: Large: Collaborative Research: Pervasive Data Ethics for Computational Research

Investigator:

The increasing scope and scale of pervasive data about people has enabled fundamentally new computational research. Simultaneously, changes in scale, scope, speed, and depth of data availability require reconsideration of the ethical calculus for computational research.

CCE STEM: Standard: Collaborative: The Development of Ethical Cultures in Computer Security Research

Principal Investigator: Katie Shilton
Investigator:

Computer security researchers navigate ethical dilemmas about how to use big data and shared networked resources to discover vulnerabilities; how to safely expose vulnerabilities; and how to best ensure that vulnerabilities are fixed.

III:Small:Safely Searching Among Sensitive Content

Principal Investigator: Douglas W. Oard, Katie Shilton
Investigator:

Today's search engines are designed principally to help people find what they want to see. Paradoxically, the fact that search engines do this well means that there are many collections that can't be searched.

CAREER: Finding Levers for Privacy and Security by Design in Mobile Development

Principal Investigator: Katie Shilton
Investigator:

Mobile data are one of the fastest emerging forms of personal data. Ensuring the privacy and security of these data are critical challenges for the mobile device ecosystem. Mobile applications are easy to build and distribute, and can collect a large variety of sensitive personal data.

CCE STEM: Finding Practices that Cultivate Ethical Computing in Mobile and Wearable Application Research & Development

Principal Investigator: Katie Shilton
Investigator: Susan Winter

Adam Porter, Elizabeth Blake, Alexander Robert Jonas, Audrey Tetteh, Devin Ellis, Jonathan Wilkenfeld

This project will study academic and commercial software research and development (R&D) to discover factors that encourage discussion and action on ethical challenges.

Finding Levers for Privacy and Security by Design in MobileDevelopment

Principal Investigator: Katie Shilton
Investigator:

Privacy and data security in mobile applications are necessary for information collection but oftentimes expensive and difficult to implement. This project seeks to study developers’ practices that encourage privacy and security in design and build tools to encourage such practices.

The Development of Ethical Cultures in Computer Security Research

Principal Investigator: Katie Shilton
Investigator:

Computer security researchers must navigate ethical dilemmas about how to use big data and shared networked resources to discover vulnerabilities; how to safely expose these problems; and how to best ensure that critical vulnerabilities are fixed.

Collaborative Research: Pervasive Data Ethics for Computational Research (PERVADE)

Principal Investigator: Katie Shilton, Jessica Vitak
Investigator: Sarah Gilbert

Increasingly pervasive data about people enables fundamentally new computational research. Simultaneously, changes in scale, scope, speed, and depth of data availability require reconsideration of ethics for computational research. Much work addressing ethics for big and pervasive data proceeds from first principles, applying traditional tenets of research ethics to computational data research.