About
34
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Introduction
I advocate for including the human factor in the design of computer and AI technologies. Through qualitative and quantitative methods, I inform the design of future technologies. Since 2018, I have studied privacy and security techs directed at software developers to evaluate, design, and build tools that can assist software devs in building privacy-friendly and secure systems. Recently, I have started exploring how to make AI technologies that respect individuals, societies, and our future.
Skills and Expertise
Publications
Publications (34)
We analyse Stack Overflow (SO) to understand challenges and confusions developers face while dealing with privacy-related topics. We apply topic modelling techniques to 1,733 privacy-related questions to identify topics and then qualitatively analyse a random sample of 315 privacy-related questions. Identified topics include privacy policies, priva...
Advertising networks enable developers to create revenue, but using them potentially impacts user privacy and requires developers to make legal decisions. To understand what privacy information ad networks give developers, we did a walkthrough of four popular ad network guidance pages with a senior Android developer by looking at the privacy-relate...
Software development teams are responsible for making and implementing software design decisions that directly impact end-user privacy, a challenging task to do well. Privacy Champions—people who strongly care about advocating privacy—play a useful role in supporting privacy-respecting development cultures. To understand their motivations, challeng...
Reliably recruiting participants who have programming skills is an ongoing challenge for empirical studies involving software development technologies, often leading to the use of crowdsourcing platforms and computer science (CS) students. In this work, we use five existing survey instruments to explore the programming skills, privacy and security...
Many guidelines for responsible AI have been suggested to help AI practitioners in the development of ethical and responsible AI systems. However, these guidelines are often neither grounded in regulation nor usable by different roles, from developers to decision makers. To bridge this gap, we developed a four-step method to generate a list of resp...
Calls for engagement with the public in Artificial Intelligence (AI) research, development, and governance are increasing, leading to the use of surveys to capture people's values, perceptions, and experiences related to AI. In this paper, we critically examine the state of human participant surveys associated with these topics. Through both a refl...
This chapter explores the principles and frameworks of human-centered Artificial Intelligence (AI), specifically focusing on user modeling, adaptation, and personalization. It introduces a four-dimensional framework comprising paradigms, actors, values, and levels of realization that should be considered in the design of human-centered AI systems....
To improve the development of responsible AI systems, developers are increasingly utilizing tools such as checklists or guideline cards to ensure fairness, transparency, and sustainability. However, these tools face two main challenges. First, they are static and are not meant to keep pace with the latest responsible AI literature and international...
In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use different terminology to discuss similar topics, all of this work is ultimately aimed at developing AI that benefits humanity while being grounded in human rights and ethics,...
As Artificial Intelligence (AI) continues to advance rapidly, it becomes increasingly important to consider AI's ethical and societal implications. In this paper, we present a bottom-up mapping of the current state of research in Human-Centered Responsible AI (HCR-AI) by thematically reviewing and analyzing 27 CHI research papers and 19 toolkits fr...
While the literature on permissions from the end-user perspective is rich, there is a lack of empirical research on why developers request permissions, their conceptualization of permissions, and how their perspectives compare with end-users' perspectives. Our study aims to address these gaps using a mixed-methods approach. Through interviews with...
To make privacy a first-class citizen in software, we argue for equipping developers with usable and responsibly-designed tools, as well as providing support from organizations, educators, and regulators. We discuss the challenges with the successful integration of privacy features and propose solutions for stakeholders to help developers perform p...
Health data is considered to be sensitive and personal; both governments and software platforms have enacted specific measures to protect it. Consumer apps that collect health data are becoming more popular, but raise new privacy concerns as they collect unnecessary data, share it with third parties, and track users. However, developers of these ap...
To make privacy a first-class citizen in software, we argue for equipping developers with usable tools, as well as providing support from organizations, educators, and regulators. We discuss the challenges with the successful integration of privacy features and propose solutions for stakeholders to help developers perform privacy-related tasks.
Privacy tasks can be challenging for developers, resulting in privacy frameworks and guidelines from the research community which are designed to assist developers in considering privacy features and applying privacy enhancing technologies in early stages of
software development. However, how developers engage
with privacy design strategies is not...
Mobile apps enable ad networks to collect and track users. App developers are given "configurations" on these platforms to limit data collection and adhere to privacy regulations; however, the prevalence of apps that violate privacy regulations because of third parties, including ad networks, begs the question of how developers work through these c...
Mobile apps enable ad networks to collect and track users. App developers are given “configurations” on these platforms to limit data collection and adhere to privacy regulations; however, the prevalence of apps that violate privacy regulations because of third parties, including ad networks, begs the question of how developers work through these c...
Privacy tasks can be challenging for developers, resulting in privacy frameworks and guidelines from the research community which are designed to assist developers in considering privacy features and applying privacy enhancing technologies in early stages of software development. However, how developers engage with privacy design strategies is not...
Mobile application (app) developers are often ill-equipped to understand the privacy implications of their products and services, especially with the common practice of using third-party libraries to provide critical functionality. To add to the complexity, most mobile applications interact with the "cloud"---not only the platform provider's ecosys...
Developers struggle to program securely. Prior works have reviewed the methods used to run user-studies with developers, systematized the ancestry of security API usabil-ity recommendations, and proposed research agendas to help understand developers' knowledge, attitudes towards security and priorities. In contrast we study the research to date an...
Mobile application (app) developers are often ill-equipped to understand the privacy implications of their products and services, especially with the common practice of using third-party libraries to provide critical functionality. To add to the complexity, most mobile applications interact with the "cloud"-not only the platform provider's ecosyste...
The security attitudes and approaches of software developers have a large impact on the software they produce, yet we know very little about how and when these views are constructed. This paper investigates the security and privacy (S&P) perceptions, experiences, and practices of current Computer Science students at the graduate and undergraduate l...
The security attitudes and approaches of software developers have a large impact on the software they produce, yet we know very little about how and when these views are constructed. This paper investigates the security and privacy (S&P) perceptions, experiences, and practices of current Computer Science students at the graduate and undergraduate l...
Static analysis tools (SATs) have the potential to assist developers in finding and fixing vulnerabilities in the early stages of software development requiring them to be able to understand and act on tools’ notifications. To understand how helpful such SAT guidance is to developers, we ran an online experiment (N=132) where participants were show...
The security attitudes and approaches of software developers have a large impact on the software they produce, yet we know very little about how and when these views are constructed. This paper investigates the security and privacy (S&P) perceptions, experiences, and practices of current Computer Science students at the graduate and undergraduate l...
Anyone can learn to code and build software these days. But the intricate and convoluted nature of computer security means that not anyone can write proper secure code. The goal of this research is to help average software developers build secure software with little understanding of security by investigating the security and privacy perceptions, e...
