The integration of robotics in agriculture presents promising solutions to challenges such as labour shortages and increasing global food demand. However, existing visions of agriculture robots often prioritize technological and business needs over workers’. In this paper, we explicitly investigate farm workers’ perspectives on robots, particularly regarding privacy, inclusivity, and safety, three critical dimensions of agricultural HRI. Through a thematic analysis of semi-structured interviews, we: 1) outline how privacy, safety and inclusivity issues manifest within modern picking-farms; 2) reveal worker attitudes and concerns about the adoption of robots; and 3) articulate a set of worker-centered requirements and alternative visions for robotic systems deployed in farm settings. Some of these visions open the door to the development of new systems and HRI research. For example, workers’ visions included robots for enhancing workplace inclusivity and solidarity, training, workplace accountability, reducing workplace accidents and responding to emergencies, as well as privacy-sensitive robots. We conclude with actionable recommendations for designers and policymakers. By centering worker perspectives, this study contributes to ongoing discussions in human-centered robotics, participatory HRI, and the future of work in agriculture.

Deceptive techniques known as dark patterns specifically target online users. Children are particularly vulnerable as they might lack the skills to recognise and resist these deceptive attempts. To be effective, interventions to forewarn and forearm should build on a comprehensive understanding of children’s existing mental models. To this end, we carried out a study with 11- to 12-year-old Scottish children to reveal their mental models of dark patterns. They were acutely aware of online deception, referring to deployers as being ‘up to no good.’ Yet, they were overly vigilant and construed worst-case outcomes, with even a benign warning triggering suspicion. We recommend that rather than focusing on specific instances of dark patterns in awareness raising, interventions should prioritise improving children’s understanding of the characteristics of, and the motivations behind, deceptive online techniques. By so doing, we can help them to develop a more robust defence against these deceptive practices.

Abstract Online tracking is complex and users find it challenging to protect themselves from it. While the academic community has extensively studied systems and users for tracking practices, the link between the data protection regulations, websites’ practices of presenting privacy-enhancing technologies (PETs), and how users learn about PETs and practice them is not clear. This paper takes a multidimensional approach to find such a link. We conduct a study to evaluate the 100 top EU websites, where we find that information about PETs is provided far beyond the cookie notice. We also find that opting-out from privacy settings is not as easy as opting-in and becomes even more difficult (if not impossible) when the user decides to opt-out of previously accepted privacy settings. In addition, we conduct an online survey with 614 participants across three countries (UK, France, Germany) to gain a broad understanding of users’ tracking protection practices. We find that users mostly learn about PETs for tracking protection via their own research or with the help of family and friends. We find a disparity between what websites offer as tracking protection and the ways individuals report to do so. Observing such a disparity sheds light on why current policies and practices are ineffective in supporting the use of PETs by users.

The steady reports of privacy invasions online paints a picture of the Internet growing into a more dangerous place. This is supported by reports of the potential scale for online harms facilitated by the mass deployment of online technology and by the data-intensive web. While Internet users often express concern about privacy, some report taking actions to protect their privacy online. We investigate the methods and technologies that individuals employ to protect their privacy online. We conduct two studies, of N=180 and N=907, to elicit individuals' use of privacy methods, within the US, the UK and Germany. We find that non-technology methods are among the most used methods in the three countries. We identify distinct groupings of privacy methods usage in a cluster map. The map shows that together with non-technology methods of privacy protection, simple PETs that are integrated in services, form the most used cluster, whereas more advanced PETs form a different, least used cluster. We further investigate user perception and reasoning for mostly using one set of PETs, in a third study with N=183 participants. We do not find a difference in perceived competency in protecting privacy online between advanced and simpler PETs users. We compare use perceptions between advanced and simpler PETs and report on user reasoning for not using advanced PETs, as well as support needed for potential use. This paper contributes to privacy research by eliciting use and perception of use across 43 privacy methods, including 26 PETs across three countries and provides a map of PETs usage. The cluster map provides a systematic and reliable point of reference for future user-centric investigations across PETs. Overall, this research provides a broad understanding of use and perceptions across a collection of PETs, and can lead to future research for scaling use of PETs.

Abstract Privacy and sharing are believed to share a dynamic and dialectical tension, where individuals have competing needs to be both open and closed in contact with others [8]. Online, technology can impact this dynamic process [68]. Indeed, a number of researchers observed that users’ stated privacy attitude do not match their behavior [2, 3, 23, 30, 64, 81]. In these studies privacy attitude is compared with behavior via a number of concepts related to privacy. While it is known in psychology that attitudes are multidimensional constructs [10, 15, 76], the question arises whether the user ambivalence with regards to privacy is due to different or contradictory cognitive and affective components of privacy and sharing attitude. We conducted an empirical study to investigate the difference between privacy attitude and sharing attitude. A US sample ofN= 60 MTurk workers was assigned to two groups and asked to describe in a 250-word free-form response what [privacy/sharing] online means for them. Responses were coded in quantitative content analysis. The presence and frequency of codes were compared across conditions. Emotions and relationships to other parties were evaluated as predictors for a discriminative logistic regression classifying both attitudes. We found that privacy and sharing attitude differ significantly across a number of the extracted codes. Participants in privacy attitude were significantly more likely to express fear and significantly less likely to express happiness. For sharing attitude the reverse is true. We found that a discriminant logistic regression on a tone analysis of the participants’ responses offers excellent discrimination between privacy and sharing attitude. We cross-validated this classifier with another sample ofN′ = 54. The observed differences contribute an understanding of user states in privacy (and sharing) situations online and has implications for both privacy research and practice.