Social engineering attacks are successful due to the exploitative nature of human psychology. Although security solutions, such as 2FA, aim to reduce the severity of attacks, these approaches tend to be insufficient considering sophisticated phishing attacks. In the present paper, we investigate how the design of the 2FA method may influence the likelihood of a login to a malicious website. Through an online experiment with N=94 participants, we show that contrary to common assumptions, warning designs prompting to proceed with login might have a contradicting effect. In contrast, designs that prompt users to abort the login have minimal desired effects. Moreover, we identify that involvement in login activity and confidence in the decision made had further significant effects on the likelihood of login. Our exploratory results contribute to the knowledge of susceptibility to phishing attacks and potential misconceptions about the effects of opinionated design in the context of 2FA.

In this chapter, we present the pedagogical possibilities of AI as well as the challenges it poses in education. AI is not merely a new technological tool but represents a fundamental shift in how students interact with knowledge, assignments, and learning environments. As educators, we must navigate questions of academic integrity, skill development, and pedagogical alignment, as AI tools are increasingly becoming part of learning and assessment practices. We consider how AI can support learning and possibly replace traditional methods; however, concerns about overreliance, misinformation, and the erosion of critical thinking remain. We share examples based on examination instances, honesty statements, and our observations on the impact of these tools on the learning experiences of students at Karlstad University and Jönköping University. These insights stem from our recent experiences, as well as students’ reflections and behaviors. Finally, we share insights and takeaways for the future use of AI in teaching and assessment, emphasizing the importance of transparent communication, clear boundaries, and a pedagogical focus on learning outcomes.

Introduction: Students experiencing poor wellbeing in elementary school can suffer lifelong consequences, including low self-esteem or depression. Understanding how to increase student wellbeing through information-based approaches is therefore important. While previous research has explored wellbeing frameworks, this study uniquely investigates the intersection of elementary school wellbeing with Internet of Things (IoT) implementation potential.

Method: We present the first comprehensive requirements analysis gathered from both staff and students for improving wellbeing in an elementary school in rural Sweden, with the aim of implementing IoT solutions. We collected qualitative data through individual interviews and workshops with 25 staff members and a survey from 464 students. We analyzed the data in an inductively and deductively way, using the Konu and Rimpelä’s wellbeing framework.

Results: Our novel findings reveal alignment between staff and student perspectives across the framework’s categories: having, loving, being and health. One example is the importance of motivation in each learning situation and creating a foundation for good social relations among the students. The requirements related to the health category received the least attention, reflecting less focus on individual student circumstances.

Discussion: This study contributes new knowledge by detailing wellbeing needs for elementary school and relating them to data-driven innovation, such as IoT, for gathering both objective and subjective information. We also acknowledge that this creates additional demands on current solutions and raises significant privacy concerns in school environments. Future research will incorporate expert IoT knowledge and develop prototype solution based on these identified requirements.

Dark patterns (deceptive designs that intend to trick technology users into doing something they did not originally intend) are considered a threat to the well-functioning digital market and harmful to consumers. So far, much attention has been given to ‘traditional’ dark patterns, relying on the weaknesses of human cognition. Various classifications of dark patterns have been proposed to aid the recognition and regulation of the phenomena. Nevertheless, little attention has been given to artificial intelligence’s (AI) role in dark patterns and how it might affect consumers’ experience and the market. The present chapter addresses this gap through the analysis of hypothetical scenarios of AI-empowered dark patterns and the adverse effects they may generate, particularly on consumers’ experience.

FemTech — i.e., mobile technologies for female health and well-being — is a rapidly growing industry. Marketed as tools of women’sempowerment, these mHealth applications not only bear risks sim-ilar to other mHealth and “dataveillance” apps, but also introduceunique, often exploitative, risks to user privacy and individualrights (education, work, fundamental), self-identity and mentalhealth (self-concept, self-esteem, personality), self-actualizationand physical health (socioeconomic freedoms, personal control,health decisions). In this paper, we draw attention to the potentialnegative implications and discuss privacy risks resulting from thecurrent design of FemTech apps. We argue that a holistic approachexamining and informing FemTech app design is necessary to makewomen’s empowerment the primary and true outcome for the users.We suggest drawing on the theories of intersectionality and contex-tual integrity to analyze and improve the design in FemTech, andwe would like to invite HCI researchers to further discuss this andother ideas, understandings, and potential solutions. (3) (PDF) Assessing and Combatting the Negative Effects of FemTech Dataveillance.

People typically enhance their online personas by sharing favourable personal information. Nevertheless, sharing of unfavourable information about oneself still occurs and is essential in some online contexts (e.g. allowing negative reviews). It remains unclear why people reveal potentially damaging information. We conducted an online experiment ((Formula presented.)) to explore the effects of feedback properties and individual characteristics on online information sharing in two contexts (social and socioeconomic) where personal ratings are essential. We allowed users to conceal their personal rating if it dropped below a threshold. The context was the primary determinant of the threshold users chose. Control availability and feedback content triggered additional considerations and caused some users to change their (non)disclosure choices. However, many users relied on their priors (experience, assumptions) rather than on new information. Our findings show how people may fail to identify the impact of nondisclosure, which may signal undesirable information to others. These findings challenge the reliance on holding users solely accountable for their ‘informedness’ vis-à-vis disclosure of their personal information.

Intelligent Transportation Systems (ITS) are on the rise, yet the knowledge about privacy preferences by different types of drivers in this context needs to be improved. This paper presents survey-based research (N = 528) focusing on preferences of drivers from South Africa and the Nordic countries for data processing and sharing by ITS, including future vehicular ad hoc networks. Our results indicate regionally framed drivers' privacy attitudes and behaviours. South African participants have higher privacy concerns and risk perception. However, their preferences to share location data with police, family and friends, emergency services, and insurance companies are higher. Moreover, the region significantly affects preferences for transparency and control and sharing frequency, as well as willingness to pay for privacy, which are higher among the South Africans. We discuss how our results on factors, including region, impacting drivers' privacy preferences can contribute to the design of usable privacy and identity management for ITS.

Increasing dependency on digital technologies introduces queries related to well-being–when and how digital technology poses a threat, or when it is the most appreciated by users? People have some expectations before using technology, which sometimes may be met, but there might be a mismatch at other times. Nevertheless, the digitalization of services advances and companies modify existing or produce new technologies that do not satisfy users' demands, putting their well-being at risk. Through an empirical inquiry, the present research explores experiences with technologies to shed more light on the main factors that enrich or diminish technology value and influence well-being. Exploiting the circumstances created by the COVID-19 pandemic that fast-forwarded technology use and development, an online inquiry was conducted to assess positive and negative experiences of technologies, focusing on the contexts of work, learning, entertainment, information-seeking, and health. The findings from 578 participants indicate that depending on the role of technologybeing a substitute for certain activities or an opportunity to perform them differently–consequences on well-being can more or less follow expectations. The results are discussed in the context of past research and practical implications for, e.g. technology design or managerial changes that could help overcome users' current challenges.

In most parts of the world, minors' access to education is guaranteed, resulting in most of their time being spent in the school building. Similarly, school staff spend a relatively long time in the same building. This unique setting requires both groups to stay inside the school walls throughout the working days, which might negatively affect their well-being. Studies show that low indoor air quality might negatively affect well-being. Moreover, school staff and students mention other problems, such as worrisome declining students' attendance, motivation, social relations, safety, stress, and pressure, among others. Technological solutions, such as IoT-based systems, might be one way to tackle the well-being issue at schools. However, most of the existing solutions focus on the quality of the indoor environment, disregarding the needs and pains of school inhabitants. In the current article, we present an investigation of how IoT-based solutions could extend beyond solely environment-measuring tools and fulfill the needs of school inhabitants. Through an interview study with eleven IoT experts guided by user (school inhabitants) requirements identified in the previous research, we assess functional and non-functional system requirements that such systems should build on. These are discussed against the five-layer IoT architecture model. Moreover, the study identifies barriers and benefits of IoT-based solutions, which are discussed in the context of existing scientific and legal frameworks. The exploratory findings presented in the paper could be used as a guide for decision-makers at schools to ensure that the students' and staff's well-being is maintained, as well as by IoT suppliers to produce holistic or compatible solutions that could be easily integrated into the unique contexts of school.

Consenting to digital services' privacy policies is standard practice. It often occurs at the early stage of interactions with a given service—during the sign-up process. Still, the most common way of acquiring consent from users is through their acknowledgment of policies by ticking a box. Consequently, users consent, mostly blindly, as they are unlikely to review the full text of policies. The current article presents research investigating factors that may impact user interaction with privacy policies, focusing on the underresearched topic of affective states (valence and arousal). The results of an online experiment (N=88) indicate that privacy policy design can elicit specific affective responses and, when accounting for some characteristics of individuals (e.g., personality traits), it can influence users' attitudes and behaviors. Particularly, the findings show that privacy awareness and willingness to disclose information might be impacted. Additionally, the analysis of collected data suggests significant associations between some personality traits and affective states, as well as a strong relationship between privacy concerns and willingness to disclose information, contradicting the concept of privacy paradox, often discussed in the privacy literature. Moreover, the results of our qualitative inquiry, where the study respondents had a chance to elaborate on their decisions to agree or disagree with the privacy policy by answering an open-ended question, confirm the quantitative findings, and reveal some of the users needs considering the sign-up process.