• Publications
  • Influence
Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction
TLDR
This work descriptively survey users for how they perceive and reason about fairness in algorithmic decision making and proposes a framework to understand why people perceive certain features as fair or unfair to be used in algorithms.
Hackers vs. Testers: A Comparison of Software Vulnerability Discovery Processes
TLDR
A semi-structured interview study with both testers and hackers, focusing on how each group finds vulnerabilities, how they develop their skills, and the challenges they face, suggests that hackers and testers follow similar processes, but get different results due largely to differing experiences.
How Well Do My Results Generalize? Comparing Security and Privacy Survey Results from MTurk, Web, and Telephone Samples
TLDR
These findings lend tempered support for the generalizability of prior crowdsourced security and privacy user studies; provide context to more accurately interpret the results of such studies; and suggest rich directions for future work to mitigate experience- rather than demographic-related sample biases.
How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt
TLDR
This work surveys over 4,500 Americans to evaluate the effect of both accuracy and privacy concerns on reported willingness to install COVID19 contact tracing apps and quantitatively model how the amount of public health benefit, amount of individual benefit, and degree of privacy risk in a hypothetical contact tracing app may influence American's willingness to installed.
A Summary of Survey Methodology Best Practices for Security and Privacy Researchers
TLDR
A set of essential guidelines for conducting self-report usability studies distilled from prior work in survey methodology and related fields is presented.
I Think They're Trying to Tell Me Something: Advice Sources and Selection for Digital Security
TLDR
Interviews of a demographically broad pool of users resulted in several interesting findings, including that negative-security events portrayed in well-crafted fictional narratives with relatable characters may be effective teaching tools for both digital-and physical-security behaviors.
Exploring User Perceptions of Discrimination in Online Targeted Advertising
TLDR
Future policy documents should explicitly address discrimination in targeted advertising, no matter its origin, as a significant user concern, and corporate responses that blame the algorithmic nature of the ad ecosystem may not be helpful for addressing public concerns.
Ethics Emerging: the Story of Privacy and Security Perceptions in Virtual Reality
TLDR
This paper presents the first work on VR security and privacy perceptions: a mixed-methods study involving semi-structured interviews with 20 VR users and developers, a survey of VR privacy policies, and an ethics co-design study with VR developers.
Where is the Digital Divide?: A Survey of Security, Privacy, and Socioeconomics
TLDR
It is found that, contrary to prior assumptions, people with lower educational attainment report equal or fewer incidents as more educated people, and that users' experiences are significantly correlated with their advice sources, regardless of SES or resources.
A Comprehensive Quality Evaluation of Security and Privacy Advice on the Web
TLDR
A large-scale, user-driven measurement study is conducted to identify 374 unique recommended behaviors contained within 1,264 documents of online security and privacy advice, and suggests a crisis of advice prioritization.
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