Cryptographic tools for authenticating the provenance of web-based information are a promising approach to increasing trust in online news and information. However, making these tools’ technical assurances sufficiently usable for news consumers is essential to realizing their potential. We conduct an online study with 160 participants to investigate how the presentation (visual vs. textual) and location (on a news article page or a third-party site) of the provenance information affects news consumers’ perception of the content’s credibility and trustworthiness, as well as the usability of the tool itself. We find that although the visual presentation of provenance information is more challenging to adopt than its text-based counterpart, this approach leads its users to put more faith in the credibility and trustworthiness of digital news, especially when situated internally to the news article.

With the pervasive and evolving use of tracking and AI to make inferences about online platform users, it has become imperative for adolescents—a key demographic using such platforms—to develop a deep understanding of these practices to protect their privacy. Traditionally, K-12 cybersecurity education has largely been confined to extracurricular activities, limiting underrepresented students’ access. To resolve this shortcoming, we partnered with a rural-identifying middle school to deliver AI-related privacy education in classrooms. Using Design-Based Research methodology, we identified students’ AI-related privacy learning needs and developed six education modules. This paper focuses on the design, classroom implementation, and evaluation of module #2, covering the privacy threats of Tracking and Pervasive Personalization (TaPP). Student assessment outcomes show they developed transferable foundational knowledge of the privacy implications of tracking and personalization after participating in the TaPP module. Our findings demonstrate the benefits of integrating AI-related privacy education into existing K-12 curricula.

Analyzing data and creating effective visualizations often requires extensive domain expertise. For users with less experience, it can be difficult to know how to get started with exploratory data analysis (EDA) and how to approach the code. Chatbots can reduce the gap between analysis outcomes and user expectations by leveraging multi-turn conversations to provide a more natural interface between the user and computer-agent. To inform the design of future visual EDA chatbots, we conduct a survey and interview study with ten potential users. Our results suggest that users want a visual EDA chatbot that can make exploratory data analysis easier, while also augmenting their knowledge of visualization and analysis techniques. Between the initial survey and post-interview questionnaire, we saw increased optimism overall for the usefulness and anticipated analytic ease of visual EDA chatbots. Based on these results, we identify four key design guidelines: future visual EDA chatbots should (1) understand the user’s data and intent, (2) respond with useful visualizations, (3) leverage the history of the visualizations and data, and (4) produce verifiable and shareable analysis processes.

Research on smart home monitoring for older adults has predominantly focused on systems whose data and alerts are directed towards family members, caregivers, or healthcare providers. Older adults have expressed interest in engaging with these systems by seeing and using their data, but they are often limited to a passive role as subjects of monitoring. This paper presents qualitative results of a longitudinal smart home project with older adults living independently in the community. Based on interviews conducted throughout the 2.5-year study with 12 participants, we report on their lived experiences of having the monitoring system in their homes and on how they reflected on the data collected by the system. The results show how participants were able to extract meaningful information from the monitoring data without finding the system invasive or intrusive. Specifically, older adults exhibited interest in data that they found indicative of living an active lifestyle, such as time spent outside the home. Drawing from critical literature on active aging, we discuss implications for incorporating peer comparisons to support reflection on personal health data without reinforcing a deficit narrative of aging.

Americans' trust in news is declining, and authenticity and transparency challenges in digital publishing contexts pose unique challenges to the ability to effectively gratify their information-seeking needs via online media. Cryptographic technologies and web-based provenance indicators have the potential to enhance the trustworthiness and transparency of digital communication, but better understandings of news consumers practices and needs are required to develop practical tools. Through a representative online survey of 400 digital news consumers and 19 follow-up interviews, we investigate how users authenticate and assign trust to news content, and identify specific needs pertaining to news transparency and authentication that could be met by digital news authentication tools. While many users currently rely on political ideology to assess news trustworthiness, we find that users of all political orientations see value in independent provenance and authentication tools for digital news.

People share photos on Social Networks Sites, but at the same time want to keep some photo content private. This tension between sharing and privacy has led researchers to try to solve this problem, but without considering users’ needs. To fill this gap, we present a novel interface that expands privacy options beyond recipient-control (R). Our system can also flag sensitive content (C) and obfuscate (O) it (RCO). We then describe the results of a two-step experiment that compares RCO with two alternative interfaces - (R) which mimics existing SNS privacy options by providing recipient control, and a system that in addition to recipient control also flags sensitive content (RC). Results suggest RC performs worse than R regarding perceived privacy risks, willingness to share, and user experience. However, RCO, which provides obfuscation options, restores these metrics to the same levels as R. We conclude by providing insights on system implementation.

A large number of photos shared online often contain private user information, which can cause serious privacy breaches when viewed by unauthorized users. Thus, there is a need for more efficient privacy control that requires automatic detection of users' private photos. However, the automatic detection of users' private photos is a challenging task, since different users may have different privacy concerns and a generalized one-size-fits-all approach for private photo detection would not be suitable for most users. User-specific detection of private photos should, therefore, be investigated. Furthermore, for effective privacy control, the exact sensitive regions in private photos need to be pinpointed, so that sensitive content can be protected via different privacy control methods. In this paper, we propose a novel system, AutoPri, to enable automatic and user-specific content-based photo privacy control in online social networks. We collect a large dataset of 31, 566 private and public photos from real-world users and present important observations on photo privacy concerns. Our system can automatically detect private photos in a user-specific manner using a detection model based on a multimodal variational autoencoder and pinpoint sensitive regions in private photos with an explainable deep learning-based approach. Our evaluations show that AutoPri can effectively determine user-specific private photos with high accuracy (94.32%) and pinpoint exact sensitive regions in them to enable effective privacy control in user-centered online social networks.

In online question and answer (Q&A) communities, people ask questions and share answers at all levels of topic sensitivity. Identity options within these communities range from anonymity to real name. The amount of engagement, and the quality of engagement on Q&A sites may differ depending on the identity options available. In this paper, we investigate the relationship between the amount of engagement, the quality of engagement, and different types of identity by analyzing three Q&A sites with different identity policies. We find that highly sensitive questions are more likely to be asked anonymously. Furthermore, allowing anonymity does not affect answer quality and only has a weak, negative indirect effect on engagement. On the other hand, anonymity leads to more trolling. We suggest online communities provide a way for users to ask highly sensitive questions anonymously and pair this with moderation mechanisms to reduce trolling

Determining which photos are sensitive is difficult. Although emerging computer vision systems can label content items, previous attempts to distinguish private or sensitive content fall short. There is no human-centered taxonomy that describes what content is sensitive or how sharing preferences for content differs across recipients. To fill this gap, we introduce a new sensitive content elicitation method which surmounts limitations of previous approaches, and, using this new method, collected sensitive content from 116 participants. We also recorded participants' sharing preferences with 20 recipient groups. Next, we conducted a card sort to surface user-defined categories of sensitive content. Using data from these studies, we generated a taxonomy that identifies 28 categories of sensitive content. We also establish how sharing preferences for content differs across groups of recipients. This taxonomy can serve as a framework for understanding photo privacy, which can, in turn, inform new photo privacy protection mechanisms.

Timely detection of an individual’s stress level has the potential to improve stress management, thereby reducing the risk of adverse health consequences that may arise due to mismanagement of stress. Recent advances in wearable sensing have resulted in multiple approaches to detect and monitor stress with varying levels of accuracy. The most accurate methods, however, rely on clinical-grade sensors to measure physiological signals; they are often bulky, custom made, and expensive, hence limiting their adoption by researchers and the general public. In this article, we explore the viability of commercially available off-the-shelf sensors for stress monitoring. The idea is to be able to use cheap, nonclinical sensors to capture physiological signals and make inferences about the wearer’s stress level based on that data. We describe a system involving a popular off-the-shelf heart rate monitor, the Polar H7; we evaluated our system with 26 participants in both a controlled lab setting with three well-validated stress-inducing stimuli and in free-living field conditions. Our analysis shows that using the off-the-shelf sensor alone, we were able to detect stressful events with an F 1-score of up to 0.87 in the lab and 0.66 in the field, on par with clinical-grade sensors.

Abstract Virtual Private Networks (VPNs) can help people protect their privacy. Despite this, VPNs are not widely used among the public. In this survey study about the adoption and usage of VPNs, we investigate people’s motivation to use VPNs and the barriers they encounter in adopting them. Using data from 90 technologically savvy participants, we find that while nearly all (98%; 88) of the participants have knowledge about what VPNs are, less than half (42%; 37) have ever used VPNs primarily as a privacy-enhancing technology. Of these, 18% (7) abandoned using VPNs while 81% (30) continue to use them to protect their privacy online. In a qualitative analysis of survey responses, we find that people who adopt and continue to use VPNs for privacy purposes are primarily motivated by emotional considerations, including the strong desire to protect their privacy online, wide fear of surveillance and data tracking not only from Internet service providers (ISPs) but also governments and Internet corporations such as Facebook and Google. In contrast, people who are mainly motivated by practical considerations are more likely to abandon VPNs, especially once their practical need no longer exists. These people cite their access to alternative technologies and the effort required to use a VPN as reasons for abandonment. We discuss implications of these findings and provide suggestions on how to maximize adoption of privacy-enhancing technologies such as VPNs, focusing on how to align them with people’s interests and privacy risk evaluation.

Pervasive photo sharing in online social media platforms can cause unintended privacy violations when elements of an image reveal sensitive information. Prior studies have identified image obfuscation methods (e.g., blurring) to enhance privacy, but many of these methods adversely affect viewers' satisfaction with the photo, which may cause people to avoid using them. In this paper, we study the novel hypothesis that it may be possible to restore viewers' satisfaction by 'boosting' or enhancing the aesthetics of an obscured image, thereby compensating for the negative effects of a privacy transform. Using a between-subjects online experiment, we studied the effects of three artistic transformations on images that had objects obscured using three popular obfuscation methods validated by prior research. Our findings suggest that using artistic transformations can mitigate some negative effects of obfuscation methods, but more exploration is needed to retain viewer satisfaction.

With the rise of digital photography and social networking, people are sharing personal photos online at an unprecedented rate. In addition to their main subject matter, photographs often capture various incidental information that could harm people's privacy. While blurring and other image filters may help obscure private content, they also often affect the utility and aesthetics of the photos, which is important since images shared in social media are mainly for human consumption. Existing studies of privacy-enhancing image filters either primarily focus on obscuring faces, or do not systematically study how filters affect image utility. To understand the trade-offs when obscuring various sensitive aspects of images, we study eleven filters applied to obfuscate twenty different objects and attributes, and evaluate how effectively they protect privacy and preserve image quality for human viewers.

Chronic disease is one of the most pressing health challenges facing the United States (and an increasing set of other countries). The onset or progression of diseases like obesity, diabetes, and metabolic disorder are strongly related to eating behavior, and scientists are still trying to fully understand the complex mixture of diet, exercise, genetics, sociocultural context, and physical environment that lead to these diseases. Health science, however, has no effective means for automatically measuring eating behavior in free-living conditions. The Auracle aims to be a wearable earpiece that detects eating behavior, to be fielded by health-science researchers in their efforts to study eating behavior and ultimately to develop interventions useful to individuals striving to address chronic disease related to eating.

The privacy control models of current Online Social Networks (OSNs) are biased towards the content owners' policy settings. Additionally, those privacy policy settings are too coarse-grained to allow users to control access to individual portions of information that is related to them. Especially, in a shared photo in OSNs, there can exist multiple Personally Identifiable Information (PII) items belonging to a user appearing in the photo, which can compromise the privacy of the user if viewed by others. However, current OSNs do not provide users any means to control access to their individual PII items. As a result, there exists a gap between the level of control that current OSNs can provide to their users and the privacy expectations of the users. In this paper, we propose an approach to facilitate collaborative control of individual PII items for photo sharing over OSNs, where we shift our focus from entire photo level control to the control of individual PII items within shared photos. We formulate a PII-based multiparty access control model to fulfill the need for collaborative access control of PII items, along with a policy specification scheme and a policy enforcement mechanism. We also discuss a proof-of-concept prototype of our approach as part of an application in Facebook and provide system evaluation and usability study of our methodology.

Current collaborative photo privacy protection solutions can be categorized into two approaches: controlling the recipient, which restricts certain viewers' access to the photo, and controlling the content, which protects all or part of the photo from being viewed. Focusing on the latter approach, we introduce privacy-enhancing obfuscations for photos and conduct an online experiment with 271 participants to evaluate their effectiveness against human recognition and how they affect the viewing experience. Results indicate the two most common obfuscations, blurring and pixelating, are ineffective. On the other hand, inpainting, which removes an object or person entirely, and avatar, which replaces content with a graphical representation are effective. From a viewer experience perspective, blurring, pixelating, inpainting, and avatar are preferable. Based on these results, we suggest inpainting and avatar may be useful as privacy-enhancing technologies for photos, because they are both effective at increasing privacy for elements of a photo and provide a good viewer experience.

Journalistic work is increasingly conducted using cooperative technologies. But while journalists need security and privacy just like professionals in sectors like health and education, constrained finances and missing legal requirements cause journalists to rely mostly on third-party platforms for their professional communications. In this study, we analyze how journalists manage professional collaborations across myriad tasks and contexts, with a focus on how their security and privacy concerns may shape these behaviors. We find that journalists' relatively open information-sharing practices may reflect the strength of their informal intra-organizational networks, rather than their organizational commitment per se. Moreover, while journalists' like many workers' manage their security and privacy concerns by avoiding sensitive communications via certain channels, the physical shrinking newsrooms of is reducing opportunities for the face-to-face communications journalists rely on for secure, private, professional exchange. Journalists' self-censorship on collaborative platforms therefore warrants particular attention given journalism's essential role in the public sphere.

Abstract Millions of apps available to smartphone owners request various permissions to resources on the devices including sensitive data such as location and contact information. Disabling permissions for sensitive resources could improve privacy but can also impact the usability of apps in ways users may not be able to predict. We study an efficient approach that ascertains the impact of disabling permissions on the usability of apps through large-scale, crowdsourced user testing with the ultimate goal of making recommendations to users about which permissions can be disabled for improved privacy without sacrificing usability. We replicate and significantly extend previous analysis that showed the promise of a crowdsourcing approach where crowd workers test and report back on various configurations of an app. Through a large, between-subjects user experiment, our work provides insight into the impact of removing permissions within and across different apps (our participants tested three apps: Facebook Messenger (N=218), Instagram (N=227), and Twitter (N=110)). We study the impact of removing various permissions within and across apps, and we discover that it is possible to increase user privacy by disabling app permissions while also maintaining app usability.

We describe the primary ways researchers can determine the size of a sample of research participants, present the benefits and drawbacks of each of those methods, and focus on improving one method that could be useful to the CHI community: local standards. To determine local standards for sample size within the CHI community, we conducted an analysis of all manuscripts published at CHI2014. We find that sample size for manuscripts published at CHI ranges from 1 -- 916,000 and the most common sample size is 12. We also find that sample size differs based on factors such as study setting and type of methodology employed. The outcome of this paper is an overview of the various ways sample size may be determined and an analysis of local standards for sample size within the CHI community. These contributions may be useful to researchers planning studies and reviewers evaluating the validity of results.

Abstract A free and open press is a critical piece of the civil-society infrastructure that supports both established and emerging democracies. However, as the professional activities of reporting and publishing are increasingly conducted by digital means, computer security and privacy risks threaten free and independent journalism around the globe. Through interviews with 15 practicing journalists and 14 organizational stakeholders (supervising editors and technologists), we reveal the distinct - and sometimes conflicting-computer security concerns and priorities of different stakeholder groups within journalistic institutions, as well as unique issues in journalism compared to other types of organizations. As these concerns have not been deeply studied by those designing computer security practices or technologies that may benefit journalism, this research offers insight into some of the practical and cultural constraints that can limit the computer security and privacy practices of the journalism community as a whole. Based on these findings, we suggest paths for future research and development that can bridge these gaps through new tools and practices.

In this paper we describe the design evolution of a novel technology that collects and displays presence information to be used in the homes of older adults. The first two iterations, the Ambient Plant and Presence Clock, were designed for higher socio-economic status (SES) older adults, whereas the Check-In Tree was designed for low SES older adults. We describe how feedback from older adult participants drove our design decisions, and give an in-depth account of how the Check-In Tree evolved from concept to a final design ready for in situ deployment.

People increasingly rely on mobile phones for storing sensitive information and credentials for access to services. Because these devices are vulnerable to theft, security of this data is put at higher risk - once the attacker is in physical possession of the device, recovering these credentials and

This tutorial presents a human-centered view of the state-of-the-art of wearable computing. Considering scientific and industrial aspects, it provides key definitions in the domain, goes through practical applications and use case scenarios, and concludes with quality factors and best design practices. An interactive component will aid participants to apply the theoretical concepts presented.

In-home technologies can support older adults' activities of daily living, provide physical safety and security, and connect elders to family and friends. They facilitate aging in place while reducing caregiver burden. One of older adults' primary concerns about in-home technologies is their potential to reduce human contact, particularly from cherished caregivers. In this exploratory in situ study, we provided an ecosystem of networked monitoring technologies to six older adults and their caregivers. We analyzed the amount and content of communication between them. The amount of noncomputer-mediated communication did not decrease through the 6-week study. The content of communication coalesced into four themes: communication about the technologies, communication facilitated by technologies, intrusiveness of technologies, and fun and playfulness with the technologies. Results suggest that in-home technologies, designed with sensitivity to older adults' primary motivations, have the potential to shape and tailor important relationships in later life.

OBJECTIVE: To assess patients' desire for granular level privacy control over which personal health information should be shared, with whom, and for what purpose; and whether these preferences vary based on sensitivity of health information. MATERIALS AND METHODS: A card task for matching health information with providers, questionnaire, and interview with 30 patients whose health information is stored in an electronic medical record system. Most patients' records contained sensitive health information. RESULTS: No patients reported that they would prefer to share all information stored in an electronic medical record (EMR) with all potential recipients. Sharing preferences varied by type of information (EMR data element) and recipient (eg, primary care provider), and overall sharing preferences varied by participant. Patients with and without sensitive records preferred less sharing of sensitive versus less-sensitive information. DISCUSSION: Patients expressed sharing preferences consistent with a desire for granular privacy control over which health information should be shared with whom and expressed differences in sharing preferences for sensitive versus less-sensitive EMR data. The pattern of results may be used by designers to generate privacy-preserving EMR systems including interfaces for patients to express privacy and sharing preferences. CONCLUSIONS: To maintain the level of privacy afforded by medical records and to achieve alignment with patients' preferences, patients should have granular privacy control over information contained in their EMR.

This paper describes the results of an experimental study in which older adult participants interacted with three monitoring technologies designed to support their ability to age in place in their own home - a camera, a stationary robot, and a mobile robot. The aim of our study was to evaluate users' perceptions of privacy and their tendencies to engage in privacy enhancing behaviors (PEBs) by comparing the three conditions. We found that privacy concerns lead older adults to change their behavior in a home environment while being monitored by cameras or embodied robots. We expected participants to engage in more PEBs when they interacted with a mobile robot, which provided embodied cues of ongoing monitoring; surprisingly, we found the opposite to be true - the camera was the condition in which participants performed more PEBs. We describe the results of quantitative and qualitative analyses of our survey, interview, and observational data and discuss the implications of our study for human-robot interaction, the study of privacy and technology, and the design of assistive robots for monitoring older adults.

Eight hour contextual observations have been conducted in the homes of 5 low socioeconomic status (SES) urban-dwelling older adults. The purpose of the observations was to understand the daily needs and challenges of older adults in order to design appropriate technology that can allow older adults to age-in-place (age at home). The long term goal of the study is to develop a suite of age-in-place technologies tailored to the lifestyle needs of low SES urban and rural-dwelling older adults. This paper presents initial findings and discusses how this ongoing research will be used to inform the design of future age-in-place technologies.

Online creative collaboration (peer production) has enabled the creation of Wikipedia and open source software (OSS), and is rapidly expanding to encompass new domains, such as video, music, and animation. But what are the underlying principles allowing online creative collaboration to succeed, and how well do they transfer from one domain to another? In this paper, we address these questions by comparing and contrasting online, collaborative animated movies, called collabs, with OSS projects. First, we use qualitative methods to solicit potential success factors from collab participants. Then, we test these predictions by quantitatively analyzing a data set of nearly 900 collabs. Finally, we compare and contrast our results with the literature on OSS development and propose broader theoretical implications. Our findings offer a starting point for a systematic research agenda seeking to unlock the potential of online creative collaboration.

Online creative collaboration projects are started every day, but many fail to produce new artifacts of value. In this poster, we address the question of why some of these projects succeed and others fail. Our quantitative analysis of 892 online collaborative animation projects, or "collabs," indicates that the early presence of organizational and structural elements, particularly those of a technical nature, can predict successful completion.

Despite increased knowledge about how Information and Communications Technologies (ICTs) are used to support religious and spiritual practices, designers know little about how to design technologies for faith-related purposes. Our research suggests incorporating sacred imagery into techno-spiritual applications can be useful in guiding development. We illustrate this through the design and evaluation of a mobile phone application developed to support Islamic prayer practices. Our contribution is to show how religious imagery can be used in the design of applications that go beyond the provision of functionality to connect people to the experience of religion.