PheNoM takes advantage of technology with smartphone applications and a small device that fits over the smartphone camera to analyze blood samples. A critical component of success of PheNoM devices and biometrics will be to understand their fit into relevant social contexts, including those of patients and medical providers, concerned consumers, and existing bio-medical institutions.
Ph.D. in Information Studies, UCLA
BA, Oberlin College
4121H Hornbake Building, South Wing
Katie Shilton is an Associate Professor at College of Information Studies and leads the Ethics & Values in Design (EViD) Lab at the UMD iSchool. She is also active in the CASCI, IPAC and DCIC research centers. Her research explores ethics and policy for the design of information collections, systems and technologies. Her work has been supported by a Google Faculty Award and multiple awards from the U.S. National Science Foundation, including an NSF CAREER award. She teaches courses in information policy, information and technology ethics, and digital curation.
User values such as privacy, accessibility, and fairness
Implementation of values in information technologies
Ethical innovation: ensuring that consideration of moral questions and user values are first-order concerns during design of emerging technologies
- INST610-Information Ethics
- Policy & Ethics for Digital Curation
Recent Publications & Products
Shilton, K., Burke, J.A., claffy, k.c., & Zhang, L. (In Press). Anticipating Policy and Social Implications of Named Data Networking. Communications of the ACM.
Shilton, K. & Anderson, S. (2016). Blended, not Bossy: Ethics Roles, Responsibilities, and Expertise in Design. Interacting With Computers. (Special issue on Co-Constructing Meaning: Ethics Matter(s) in Design Research).
Martin, K. & Shilton, K. (2016). Putting Mobile Application Privacy in Context: An Empirical Study of Consumer Privacy Expectations for Mobile Devices. The Information Society, 32(3).
Vitak, J., Shilton, K., and Ashktorab, Z. (2016). Beyond the Belmont Principles: Ethical Challenges, Practices, and Beliefs in the Online Data Research Community. Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2016), San Francisco, CA: ACM.
Named Data Networking (NDN) aims to redesign the architecture of the Internet, producing not only technical advances, but social impacts on privacy, intellectual property, law enforcement, governance, and political economy.
This project studies academic and commercial software research and development (R&D) to discover factors that encourage discussion and action on ethical challenges.
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.
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.
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.