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Vipera: Blending Visual and LLM-Driven Guidance for Systematic Auditing of Text-to-Image Generative AI

Despite their increasing capabilities, text-to-image generative AI systems are known to produce biased, offensive, and otherwise problematic outputs. While recent advancements have supported testing and auditing of generative AI, existing auditing methods still face challenges in supporting effective exploration of th…

Yanwei Huang et al.Hong Kong University of Science and Technology

Of Secrets and Seedphrases: Conceptual misunderstandings and security challenges for seed phrase management among cryptocurrency users

Cryptocurrency adoption has surged dramatically, with over 500 million global users. Despite the appeal of self-custodial wallets, which grant users control over their assets, these users often struggle with the complexities of securing seed phrases, leading to substantial financial losses. This paper investigates the…

Farida Eleshin et al.Carnegie Mellon University

To Self-persuade or Be Persuaded: Examining Interventions for Users' Privacy Setting Selection

User adoption of security and privacy (S&P) best practices remains low, despite sustained efforts by researchers and practitioners. Social influence is a proven method for guiding user S&P behavior, though most work has focused on studying peer influence, which is only possible with a known social graph. In a study of…

Kimi Wenzel et al.Carnegie Mellon University

Understanding Challenges for Developers to Create Accurate Privacy Nutrition Labels

Apple announced the introduction of app privacy details to their App Store in December 2020, marking the first ever real-world, large-scale deployment of the privacy nutrition label concept, which had been introduced by researchers over a decade earlier. The Apple labels are created by app developers, who self-report…

Tianshi Li et al.Carnegie Mellon University

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Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance

Ensuring effective public understanding of algorithmic decisions that are powered by machine learning techniques has become an urgent task with the increasing deployment of AI systems into our society. In this work, we present a concrete step toward this goal by redesigning confusion matrices for binary classification…

Hong Shen et al.Carnegie Mellon University

Interpreting and Explaining AI

`I Can't Even Buy Apples If I Don't Use Mobile Pay?': When Mobile Payments Become Infrastructural in China

Despite slow adoption in the West, mobile payments are the de facto solution for hundreds of millions of users in China for everything from paying bills to riding buses, from sending virtual ``Red Packets'' to buying money market funds. In this paper, we use the theoretical lens of infrastructure to study users' inter…

Hong Shen et al.Carnegie Mellon University

Social Support, Donation, and Money

How Developers Talk about Personal Data and What It Means for User Privacy: A Case Study of a Developer Forum on Reddit

While online developer forums are major resources of knowledge for application developers, their roles in promoting better privacy practices remain under explored. In this paper, we conducted a qualitative analysis of a sample of 207 threads (4772 unique posts) mentioning different forms of personal data from the /r/a…

Tianshi Li et al.Carnegie Mellon University

Privacy and Security

I'm All Eyes and Ears: Exploring Effective Locators for Privacy Awareness in IoT Scenarios

With the proliferation of IoT devices, there are growing concerns about being sensed or monitored by these devices unawares, especially in places perceived as private. We explore the design space of IoT locators to help people physically find nearby IoT devices. We first conducted a survey to understand people's willi…

Yunpeng Song et al.Xi'an Jiaotong University

Normal and Easy: Account Sharing Practices in the Workplace

Work is being digitized across all sectors, and digital account sharing has become common in the workplace. In this paper, we conduct a qualitative and quantitative study of digital account sharing practices in the workplace. Across two surveys, we examine the sharing process at work, probing what accounts people shar…

Yunpeng Song et al.Xi'an Jiaotong University

Workplaces

Evolving the Ecosystem of Personal Behavioral Data

Everyday, people generate lots of personal data. Driven by the increasing use of online services and widespread adoption of smartphones (owned by 68% of U.S. residents; Anderson, 2015), personal data take many forms, including communications (e.g., e-mail, SMS, Facebook), plans and coordination (e.g., calendars, TripI…

Jason Wiese et al.University of Utah

Panel: Voice Assistants, UX Design and Research

In this panel, we discuss the challenges that are faced by HCI practitioners and researchers as they study how voice assistants (VA) are used on a daily basis. Voice has become a widespread and commercially viable interaction mechanism with the introduction of VAs such as Amazon's Alexa, Apple's Siri, the Google Assis…

Jofish Kaye et al.Mozilla

Breaking! A Typology of Security and Privacy News and How It’s Shared

News coverage of security and privacy (S&P) events is pervasive and may affect the salience of S&P threats to the public. To better understand this coverage and its effects, we asked: What types of S&P news come into people’s awareness? How do people hear about and share this news? Over two years, we recruited 1999 pa…

Sauvik Das et al.Georgia Institute of Technology

Paper Title	Authors	Research Topics
Vipera: Blending Visual and LLM-Driven Guidance for Systematic Auditing of Text-to-Image Generative AI Despite their increasing capabilities, text-to-image generative AI systems are known to produce biased, offensive, and otherwise problematic outputs. While recent advancements have supported testing and auditing of generative AI, existing auditing methods still face challenges in supporting effective exploration of th…	YH Yanwei Huang et al.Hong Kong University of Science and Technology
Of Secrets and Seedphrases: Conceptual misunderstandings and security challenges for seed phrase management among cryptocurrency users Cryptocurrency adoption has surged dramatically, with over 500 million global users. Despite the appeal of self-custodial wallets, which grant users control over their assets, these users often struggle with the complexities of securing seed phrases, leading to substantial financial losses. This paper investigates the…	FE Farida Eleshin et al.Carnegie Mellon University
To Self-persuade or Be Persuaded: Examining Interventions for Users' Privacy Setting Selection User adoption of security and privacy (S&P) best practices remains low, despite sustained efforts by researchers and practitioners. Social influence is a proven method for guiding user S&P behavior, though most work has focused on studying peer influence, which is only possible with a known social graph. In a study of…	KW Kimi Wenzel et al.Carnegie Mellon University
emoji_events Understanding Challenges for Developers to Create Accurate Privacy Nutrition Labels Apple announced the introduction of app privacy details to their App Store in December 2020, marking the first ever real-world, large-scale deployment of the privacy nutrition label concept, which had been introduced by researchers over a decade earlier. The Apple labels are created by app developers, who self-report…	TL Tianshi Li et al.Carnegie Mellon University
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance Ensuring effective public understanding of algorithmic decisions that are powered by machine learning techniques has become an urgent task with the increasing deployment of AI systems into our society. In this work, we present a concrete step toward this goal by redesigning confusion matrices for binary classification…	HS Hong Shen et al.Carnegie Mellon University	Interpreting and Explaining AI
`I Can't Even Buy Apples If I Don't Use Mobile Pay?': When Mobile Payments Become Infrastructural in China Despite slow adoption in the West, mobile payments are the de facto solution for hundreds of millions of users in China for everything from paying bills to riding buses, from sending virtual ``Red Packets'' to buying money market funds. In this paper, we use the theoretical lens of infrastructure to study users' inter…	HS Hong Shen et al.Carnegie Mellon University	Social Support, Donation, and Money
How Developers Talk about Personal Data and What It Means for User Privacy: A Case Study of a Developer Forum on Reddit While online developer forums are major resources of knowledge for application developers, their roles in promoting better privacy practices remain under explored. In this paper, we conducted a qualitative analysis of a sample of 207 threads (4772 unique posts) mentioning different forms of personal data from the /r/a…	TL Tianshi Li et al.Carnegie Mellon University	Privacy and Security
I'm All Eyes and Ears: Exploring Effective Locators for Privacy Awareness in IoT Scenarios With the proliferation of IoT devices, there are growing concerns about being sensed or monitored by these devices unawares, especially in places perceived as private. We explore the design space of IoT locators to help people physically find nearby IoT devices. We first conducted a survey to understand people's willi…	YS Yunpeng Song et al.Xi'an Jiaotong University
Normal and Easy: Account Sharing Practices in the Workplace Work is being digitized across all sectors, and digital account sharing has become common in the workplace. In this paper, we conduct a qualitative and quantitative study of digital account sharing practices in the workplace. Across two surveys, we examine the sharing process at work, probing what accounts people shar…	YS Yunpeng Song et al.Xi'an Jiaotong University	Workplaces
Evolving the Ecosystem of Personal Behavioral Data Everyday, people generate lots of personal data. Driven by the increasing use of online services and widespread adoption of smartphones (owned by 68% of U.S. residents; Anderson, 2015), personal data take many forms, including communications (e.g., e-mail, SMS, Facebook), plans and coordination (e.g., calendars, TripI…	JW Jason Wiese et al.University of Utah
Panel: Voice Assistants, UX Design and Research In this panel, we discuss the challenges that are faced by HCI practitioners and researchers as they study how voice assistants (VA) are used on a daily basis. Voice has become a widespread and commercially viable interaction mechanism with the introduction of VAs such as Amazon's Alexa, Apple's Siri, the Google Assis…	JK Jofish Kaye et al.Mozilla
Breaking! A Typology of Security and Privacy News and How It’s Shared News coverage of security and privacy (S&P) events is pervasive and may affect the salience of S&P threats to the public. To better understand this coverage and its effects, we asked: What types of S&P news come into people’s awareness? How do people hear about and share this news? Over two years, we recruited 1999 pa…	SD Sauvik Das et al.Georgia Institute of Technology