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.
PhD, University of California, Los Angeles
Office: 4121H Hornbake Building, South Wing
Social and ethical implications of emerging technologies; information policy; social values and technology design
New information technology calls for new information ethics in defining how digital personal data will be collected, organized and shared. This is a new challenge for archivists, digital curators and information specialists. The iSchool is dedicated to creating information professionals that maintain our values of accessibility and equity while also ensuring personal privacy and preservation.
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.