Crowdsourcing Privacy Design Critique: An Empirical Evaluation of Framing Effects

When designed incorrectly, information systems can thwart people’s expectations of privacy. An emerging technique for evaluating systems during the development stage is the crowdsourcing design critique, in which design evaluations are sourced using crowdsourcing platforms. However, we know that information framing has a serious effect on decision-making and can steer design critiques in one way or another. We investigate how the framing of design cases can influence the outcomes of privacy design critiques. Specifically, we test whether -˜Personas’, a central User-Centered Design tool for describing users, can inspire empathy in users while criticizing privacy designs. In an experiment on Amazon Mechanical Turk workers (n=456), we show that describing design cases by using personas causes intrusive designs to be criticized more harshly. We discuss how our results can be used to enhance privacy-by-design processes and encourage user-centered privacy engineering

Designing a Serious Game: Teaching Developers to Embed Privacy into Software Systems

Software applications continue to challenge user privacy when users interact with them. Privacy practices (e.g. Data Minimisation (DM), Privacy by Design (PbD) or General Data Protection Regulation (GDPR)) and related "privacy engineering" methodologies exist and provide clear instructions for developers to implement privacy into software systems they develop that preserve user privacy. However, those practices and methodologies are not yet a common practice in the software development community. There has been no previous research focused on developing "educational" interventions such as serious games to enhance software developers' coding behaviour. Therefore, this research proposes a game design framework as an educational tool for software developers to improve (secure) coding behaviour, so they can develop privacy-preserving software applications that people can use. The elements of the proposed framework were incorporated into a gaming application scenario that enhances the software developers' coding behaviour through their motivation. The proposed work not only enables the development of privacy-preserving software systems but also helping the software development community to put privacy guidelines and engineering methodologies into practice.Comment:

Retrospective Privacy: Managing Longitudinal Privacy in Online Social Networks

Online social networks provide access to the user’s information for long periods of time after the information’s initial publication. In this paper, we investigate the relation between information aging and its sharing preferences on Facebook. Our findings are based on a survey of 193 Facebook users, in which we asked users to specify their sharing preferences and intentions towards posts that were published in different periods of time (from the time of the survey and up to 24 months prior to the time of the survey.) Our results show that willingness to share significantly drops with the time passed since publishing the post. The occurrence of life changes, such as graduating from college or moving to a new town, is correlated with a further decrease in the willingness to share. We discuss our findings by relating it to information aging theories and privacy theories. Finally, we use our results to reflect on privacy mechanisms for long-term usage of online social networks, such as expiry date for content and historical information reviewing processes

When it is ok to give the Robot Less: Children’s Fairness Intuitions Towards Robots

Children develop intuitions about fairness relatively early in development. While we know that children believe other humans care about distributional fairness, considerably less is known about whether they believe other agents, such as robots, do as well. In two experiments (N = 273) we investigated 4- to 9-year-old children’s intuitions about whether robots would be upset about unfair treatment as human children. Children were told about a scenario in which resources were being split between a human child and a target recipient: either another child or a robot across two conditions. The target recipient (either child or robot) received less than another child. They were then asked to evaluate how fair the distribution was, and whether the target recipient would be upset. Both Experiment 1 and 2 used the same design, but Experiment 2 also included a video demonstrating the robot’s mechanistic “robotic” movements. Our results show that children thought it was more fair to share unequally when the disadvantaged recipient was a robot rather than a child (Experiment 1 and 2). Furthermore, children thought that the child would be more upset than the robot (Experiment 2). Finally, we found that this tendency to treat these two conditions differently became stronger with age (Experiment 2). These results suggest that young children treat robots and children similarly in resource allocation tasks, but increasingly differentiate them with age. Specifically, children evaluate inequality as less unfair when the target recipient is a robot, and think that robots will be less angry about inequality

Privacy In Context: Critically Engaging With Theory To Guide Privacy Research And Design

Privacy has been a key research theme in the CSCW and HCI communities, but the term is often used in an ad hoc and fragmented way. This is likely due to the fact that privacy is a complex and multi-faceted concept. This one-day workshop will facilitate discourse around key privacy theories and frameworks that can inform privacy research with the goal of producing guidelines for privacy researchers on how and when to incorporate which theories into various aspects of their empirical privacy research. This will lay the groundwork to move the privacy field forward

Analyzing User Engagement with TikTok's Short Format Video Recommendations using Data Donations

Short-format videos have exploded on platforms like TikTok, Instagram, and YouTube. Despite this, the research community lacks large-scale empirical studies into how people engage with short-format videos and the role of recommendation systems that offer endless streams of such content. In this work, we analyze user engagement on TikTok using data we collect via a data donation system that allows TikTok users to donate their data. We recruited 347 TikTok users and collected 9.2M TikTok video recommendations they received. By analyzing user engagement, we find that the average daily usage time increases over the users’ lifetime while the user attention remains stable at around 45%. We also find that users like more videos uploaded by people they follow than those recommended by people they do not follow. Our study offers valuable insights into how users engage with short-format videos on TikTok and lessons learned from designing a data donation system.Organisation & Governanc

Invasive Fungal Diseases in Hospitalized Patients with COVID-19 in Israel: A Multicenter Cohort Study

Highly variable estimates of COVID-19-associated fungal diseases (IFDs) have been reported. We aimed to determine the incidence of clinically important fungal diseases in hospitalized COVID-19 patients during the first year of the pandemic. We performed a multicenter survey of IFDs among patients hospitalized with COVID-19 in 13 hospitals in Israel between February 2020 and May 2021. COVID-19-associated pulmonary mold disease (PMD) and invasive candidiasis (IC) were defined using ECMM/ISHAM and EORTC/MSG criteria, respectively. Overall rates of IC and PMD among patients with critical COVID-19 were 10.86 and 10.20 per 1000 admissions, respectively, with significant variability among medical centers. PMD rates were significantly lower in centers where galactomannan was a send-out test versus centers with on-site testing (p = 0.035). The 30-day mortality rate was 67.5% for IC and 57.5% for PMD. Treatment with an echinocandin for IC or an extended-spectrum azole for PMD was associated with significantly lower mortality rates (adjusted hazard ratio [95% confidence interval], 0.26 [0.07–0.91] and 0.23 [0.093–0.57], respectively). In this multicenter national survey, variable rates of PMD were associated with on-site galactomannan testing, suggesting under-detection in sites lacking this capacity. COVID-19-related IFDs were associated with high mortality rates, which were reduced with appropriate antifungal therapy