This article explores the emergence of standards and regulation associated with the provision of Closed Circuit Television (CCTV) surveillance systems in the United Kingdom. It argues that despite the intrusive and controlling nature of CCTV technology there is limited formal intervention in the form of legislation, governing its introduction and use. Instead government has sought to influence the regulation of the technology indirectly through its ability to shape and govern policy networks in the policy arena. In doing so, (...) it is argued here, that government remains the dominant actor in the policy process. (shrink)

The COVID‐19 pandemic has infected millions around the world. Governments initially responded by requiring businesses to close and citizens to self‐isolate, as well as funding vaccine research and implementing a range of technologies to monitor and limit the spread of the disease. This article considers the use of smartphone metadata and Bluetooth applications for public health surveillance purposes in relation to COVID‐19. It undertakes ethical analysis of these measures, particularly in relation to collective moral responsibility, considering whether citizens (...) ought, or should be compelled, to comply with government measures. (shrink)

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' (...) CL. This study addresses the key concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions. (shrink)

At the most mundane level, CCTV observes bodies, and as such attaches great importance to the specific features of the human body. At the same time, however, bodies tend to disappear, as they are represented electronically by the camera monitors and, in the case of image recording, by the computer systems processing data. The roles of bodies(either as targets of surveillance or as translations into flows of disembodied information), however, are not unimportant or inconsequential, but may in fact give rise (...) to a number of tangible ethical dilemmas. Firstly, the virtual representation of the embodied actor is not a neutral, unproblematic process. Body representation techniques such as CCTV produce constructions of the subject that involve judgmental, discriminatory processes of categorisation and are based on asymmetrical relations between observers and observed. Secondly, the `data doubles' are not inconsequential: the representations of the body produced by CCTV can have palpable consequences for the embodied self and its life chances. The widespread use of CCTV could therefore give rise to individual as well as social issues, and possibly in a different manner than previous surveillance technologies. This fact signals the need for(re-)conceptualisations of moral values (such as privacy) applicable to the case of CCTV which take into account the importance of bodily protections. (shrink)

Public video surveillance tends to be discussed in either utopian or dystopian terms: proponents maintain that camera surveillance is the perfect tool in the fight against crime, while critics argue that the use of security cameras is central to the development of a panoptic, Orwellian surveillance society. This paper provides an alternative, more nuanced view. On the basis of an empirical case study, the paper explores how camera surveillance applications do not simply augment surveillance capacities, but rather have to deal (...) with considerable uncertainties in the process of producing a continuous, effective, all‐seeing gaze. The case study shows that the actions of human operators and the operation of camera technologies each place limits on the execution of electronic visual surveillance, instead of efficiently enhancing the powers of the surveilling gaze. The analysis suggests that the effects of video surveillance are rather ambivalent and uncertain, thus showing that public camera systems are not simply beneficial or malign. (shrink)

The COVID-19 pandemic and its related policies (e.g., stay at home and social distancing orders) have increased people’s use of digital technology, such as social media. Researchers have, in turn, utilized artificial intelligence to analyze social media data for public health surveillance. For example, through machine learning and natural language processing, they have monitored social media data to examine public knowledge and behavior. This paper explores the ethical considerations of using artificial intelligence to monitor social media to understand (...) the public’s perspectives and behaviors surrounding COVID-19, including potential risks and benefits of an AI-driven approach. Importantly, investigators and ethics committees have a role in ensuring that researchers adhere to ethical principles of respect for persons, beneficence, and justice in a way that moves science forward while ensuring public safety and confidence in the process. (shrink)

COVID-19 has necessitated inquiry into the capacity of technology to build learning communities to solve problems beyond proximal boundaries. Platforms like Zoom offer pathways for communication and content-delivery, but little stimulus for collective online outcomes (projects/learning-objects/discussion forums). We aim to examine how monetized platforms fit within Marcuse’s technological rationality and its capacity to exercise social control. This owes to dominance of aspects of technology related to providing content rather than how we direct agency towards using it. Such (...) control is reminiscent of influence exercised by portals like television and radio in the mid-1900’s. We suggest Habermas’ communicative rationality using technology can foster critical thinking in online education. We often assume technology is the basis for change in classrooms. As Marcuse says, this enables technology to exact control upon us, and fragment outcomes obtained from using it to learn, warranting creation of new tools. Integrating bottom-up ways of using technology into existing frameworks can mitigate fragmentation of the public sphere resulting from industrialized online education. Fragmentation becomes pervasive with migrating classes online. We provide a framework/design to better encourage critical reflection in online learning communities during unprecedented times such as the era of COVID-19. (shrink)

Around the world, many schools were closed as one of the measures to contain the spread of the COVID-19 pandemic. School closure brought about important challenges to the students' learning process. This context requires strong self-regulatory competences and agency for autonomous learning. Moreover, online remote learning was the main alternative response to classroom learning, which increased the inequalities between students with and without access to technological resources or for those with low digital literacy. All (...) considered, to level the playing field for students without digital resources, there is an urgent need to promote self-regulatory competences through offline intervention solutions. The current paper describes a project with this purpose, using radio broadcasting and letters to reach elementary students without digital resources. Moreover, potential reach and participants' perspectives of the project implementation are presented and discussed. The project draws on a prior evidence-based story-tool intervention grounded on a self-regulated learning framework. The original intervention was set previous to the COVID-19 pandemic and was implemented in the classroom context (N= 1,103 students). Once the schools had been closed down, the mode of intervention was adapted with the collaboration of the community. Alternative solutions were developed as follows: (i) story chapters were read on the radio and students received to their homes a printed script, prompting reflection, and suggesting related activities; (ii) students were provided with the story-tool to read autonomously and received letters from the main characters of the story which included, for example, suggestions for activities and reflection. These two alternative modes of intervention delivery potentially reached 394 elementary students, including students with digital resources. Interviews conducted with a group of students were provided information about the positive aspects of these two modes of intervention delivery, perceived learning (e.g., planning), constraints, and suggestions to improve the project. The current work is likely to merit attention from researchers and educational practitioners, given the need to use offline alternatives to provide support for students without digital resources to engage in autonomous learning during the pandemic period. This project may also be used as an alternative or a complementary solution to online modality. (shrink)

The outbreak of COVID-19 had a profound impact on the practice of university leadership in China. This study employs a case study as the research method, interviewing five Heads of the Departments from the Z University in China to examine the challenges to leadership in Chinese universities during the COVID-19 pandemic and explores effective countermeasures. Research findings reveal that the challenges they faced manifested in the government's closed management requirements and the students' demands for freedom of entry (...) and exit, the dynamic and flexible disciplinary development and the rigid teaching evaluation, and big data-enabled governance and the habit of human experience-oriented management. In response to these challenges, this study proposes suggestions for the Z University leaders in the post-pandemic era: establishing rules and regulations with a relaxed degree, tolerating ambiguity in online teaching, improving the ability of intelligent technology, and taking opportunities to learn. (shrink)

This study explores how China’s education responses to COVID-19 from a perspective of policy analysis. Specifically, it involves building an educational policy system for COVID-19 to examine educational governance framework, school management and teaching, policies for teachers during the epidemic. The education policy during the epidemic has achieved positive results. Those results aim to ensure the physical and mental health of teachers and students, ensure the supply of epidemic prevention materials and educational resources, ensure the quality of students' (...) learning, and enhance the application ability of teachers' teaching technology. The process of policy changes and effects of policy implementation have been examined to analyze how China’s education responses to COVID-19. The characteristics and experience of China's education policy in response to the epidemic concentrate on forming a governance system under the centralized and unified leadership of the Communist Party of China, building a pattern in which families and schools cooperate closely to promote the smooth development of education and teaching, transforming from an emergency substitute during the crisis into an important motivation to promote the transformation of education paradigm, and paying great attention to remote and poor areas and disadvantaged student groups. (shrink)

The summer semester had just begun at Austrian and German universities when Covid-19 was declared a global pandemic by the World Health Organization. Thus, in March 2020, all universities closed their campuses, switching to distance learning within the span of about a single day. How did lecturers handle the situation? Were they still able to turn the situation into a positive one? What were the main obstacles with this difficult situation, and where there conditions which helped them (...) to overcome the new challenges? These are research questions of the present survey with a sample of 1,152 lecturers at universities in Austria and Germany. The survey focuses on the lecturers’ appraisals of the novel situation as challenging or threatful. These appraisals are important for approaching a situation or shying away from it. However, how well a person adjusts to a novel situation is also influenced by personal and environmental resources which help to overcome the situation. The present survey focused on four possible sources of influence: internal assessments of the situation determining it to be threatening and/or challenging, personal resources, attitudes, and support by the organization. It was investigated to which degree these sources of influence could contribute to the lecturers’ satisfaction with their teaching processes. A multiple regression with three criterion variables describing university lecturers’ perceived satisfaction with distance teaching was carried out. Predictor variables were the lecturers’ appraisals of challenge and threat, perceived support by the university and sense of belonging to the university, temporal resources, proficiency in using digital technologies, length of teaching experience, and gender. Lecturers were mostly satisfied with their teaching activities. Together with the perception of a low threat potential, challenge appraisals contributed strongest to satisfaction. In comparison, assessments of actual personal resources, skills in the use of digital technologies, teaching experience, and temporal resources were important but contributed less to satisfaction than challenge appraisals. It seems that lecturers were only able to use these resources when the technological resources were available and when the lecturers were confident in their technical abilities. (shrink)

As the development of artificial intelligence technology, the deep-learning -based Virtual Reality technology, and DL technology are applied in human-computer interaction, and their impacts on modern film and TV works production and audience psychology are analyzed. In film and TV production, audiences have a higher demand for the verisimilitude and immersion of the works, especially in film production. Based on this, a 2D image recognition system for human body motions and a 3D recognition system for human body motions (...) based on the convolutional neural network algorithm of DL are proposed, and an analysis framework is established. The proposed systems are simulated on practical and professional datasets, respectively. The results show that the algorithm's computing performance in 2D image recognition is 7–9 times higher than that of the Open Pose method. It runs at 44.3 ms in 3D motion recognition, significantly lower than the Open Pose method's 794.5 and 138.7 ms. Although the detection accuracy has dropped by 2.4%, it is more efficient and convenient without limitations of scenarios in practical applications. The AI-based VR and DL enriches and expands the role and application of computer graphics in film and TV production using HCI technology theoretically and practically. (shrink)

This article considers the question of whether it is meaningful to speak of privacy rights in public spaces, and the possibility of such rights framing the basis for regulating or restricting the use of surveillance technologies such as closed circuit television (CCTV). In particular, it responds to a recent article by Jesper Ryberg that suggests that there is little difference between being watched by private individuals and CCTV cameras, and instead argues that state surveillance is qualitatively different from (...) (and more problematic than) surveillance by ‘lonely old ladies’. (shrink)

Surveillance is a core function of all public health systems. Responses to the COVID-19 pandemic have deployed traditional public health surveillance responses, such as contact tracing and quarantine, and extended these responses with the use of varied technologies, such as the use of smartphone location data, data networks, ankle bracelets, drones, and big data analysis. Applying Foucault’s (1979) notion of the panopticon, with its twin focus on surveillance and self-regulation, as the preeminent form of social control in modern societies, (...) we examine the increasing levels of surveillance enacted during this pandemic and how people have participated in, and extended, this surveillance, self-regulation, and social control through the use of digital media. Consideration is given to how such surveillance may serve public health needs and/or political interests and whether the rapid deployment of these extensive surveillance mechanisms risks normalizing these measures so that they become more acceptable and then entrenched post-COVID-19. (shrink)

More and more schools begin to design simulation technology based on virtual imaging technology and virtual reality in their course contents. In particular, among these technical courses, there is a need to first strengthen the Film and Television Production education in higher institutions. This article aims to study the impact of VRT, VR, and Internet of things technology on FTP courses and audience psychology in higher institutions under the era of intelligent multimedia. How to use emerging VR technology to promote (...) the psychological wellbeing of students or patients has become a new research direction, the exploration of which has a far-reaching significance for the applications of the related technologies. First, the principle and applications of VR and IoT technology are described. Thereon, the deep learning -based training model is used to analyze the postproduction of VR-based Sand Table game, and the function and effect of the designed game model are discussed. Subsequently, VR-based Sand Play Therapy is applied to mentally ill patients to obtain its therapeutic effect. The results show that the designed VR-based Sand Table game model can be used to treat mentally ill patients and alleviate their negative psychological states. Meanwhile, the Test Anxiety Scale scores prove the significant therapeutic effect of the designed game model on the mental problems of patients. Therefore, VR-based psychological SPT can be applied in the stress relief of students and the treatment of mentally ill patients, as well as alleviate their mental health problems. This research provides a new direction and some theoretical support for the application field of VR technology. (shrink)

The novel coronavirus disease is regarded as one of the most imminent disease outbreaks which threaten public health on various levels worldwide. Because of the unpredictable outbreak nature and the virus’s pandemic intensity, people are experiencing depression, anxiety, and other strain reactions. The response to prevent and control the new coronavirus pneumonia has reached a crucial point. Therefore, it is essential—for safety and prevention purposes—to promptly predict and forecast the virus outbreak in the course of this troublesome time to have (...) control over its mortality. Recently, deep learning models are playing essential roles in handling time-series data in different applications. This paper presents a comparative study of two deep learning methods to forecast the confirmed cases and death cases of COVID-19. Long short-term memory and gated recurrent unit have been applied on time-series data in three countries: Egypt, Saudi Arabia, and Kuwait, from 1/5/2020 to 6/12/2020. The results show that LSTM has achieved the best performance in confirmed cases in the three countries, and GRU has achieved the best performance in death cases in Egypt and Kuwait. (shrink)

Due to restrictions against the COVID-19 pandemic, spectators were not allowed to attend soccer matches at the end of the 2019/2020 season. Previous studies suggest that the absence of a home crowd changes the home field advantage in terms of match outcomes, offensive performance, and referee decisions. However, because of the small sample sizes, these changes may be random rather than meaningful. To test this, we created 1,000,000 randomized samples from the previous four seasons with the exact same (...) number of matches played behind closed doors in Europe’s four most elite soccer leagues at the end of the 2019/2020 season. We found that across countries, performance indices and referee decisions indeed changed to the detriment of the home team beyond the level of chance. However, this overall pattern could be ascribed to specific countries. Most importantly, the proportion of points won by the home teams declined significantly only in Germany, which was accompanied by a meaningful increase in the proportion of goals scored by the away teams and the proportion of yellow cards given to the home teams. We conclude that the home field advantage may indeed be lost when spectators are absent. However, in future studies, more detailed behavioral analyses are needed to determine the robustness and the behavioral determinants of this phenomenon across leagues and countries. (shrink)

The closure of schools as a result of COVID-19 has been a critical global incident from which to rethink how education works in all our countries. Among the many changes generated by this crisis, all teaching became mediated by digital technologies. This paper intends to analyze the activities carried out during this time through digital technologies and the conceptions of teaching and learning that they reflect. We designed a Likert-type online questionnaire to measure the frequency of teaching activities. (...) It was answered by 1,403 teachers from Spain. The proposed activities varied depending on the learning promoted, the learning outcomes, the type of assessment to which the activities were directed, and the presence of cooperative activities. The major result of this study was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favoring verbal and attitudinal learning. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified four teaching profiles depending on the frequency and type of digital technologies use: Passive, Active, Reproductive, and Interpretative. The variable that produced the most consistent differences was previous digital technologies use These results show that Information and Communication Technologies uses are reproductive rather than constructive, which impedes effective digital technologies integration into the curriculum so that students gain 21st-century competencies. (shrink)

ABSTRACT The advent of Covid-19, a new and highly contagious form of Corona virus, in late 2019 cast a harsh light on human vulnerabilities and on the provocations (and opportunities) facing humanity. Although many of the more drastic measures applied within educational settings have since ceased to apply, at least for the time being, we are not yet ‘past Covid’: many of the challenges that are discussed here still exist. As we faced unprecedented disruption to economies, societies and (...) education systems, the global health pandemic drew attention to existing inequalities and presented a clear picture of steps required for addressing the education of close to one billion students whose learning was hampered due to school closures. The magnitude of this challenge was and still is starkly manifest with the digital divide on the African continen. Democratization of education has been perceived to include facilitation of both formal and epistemic access (including allocation of new technologies for teaching and learning), reconceptualization of knowledge, truth and learning, recognition of ‘other standpoints for knowledge’ and ‘very different knowledge registers,’ recovery of ‘lost knowledge resources’ and connection of ‘multiple ways of knowing,’ and respectful engagement ‘with indigenous and local knowledges,’ idea that merit critical interrogation. (shrink)

Due to the epidemic, many offline educational institutions and even schools have begun to seek new teaching methods, and online teaching has become an important teaching method in this situation. Online teaching refers to the teaching mode in which teachers teach online through the Internet and students learn in online classrooms. Online teaching can reduce crowd contact between students and prevent the spread of the epidemic. However, due to the virtual nature of the Internet and the immaturity of the (...) online teaching system, the current online teaching method cannot be accepted by the majority of teachers and students. Therefore, this paper conducts a satisfaction survey on the psychological acceptance ability of students under the online teaching organization of English majors, aiming to understand the actual psychological burden brought by online teaching to students. The content of the questionnaire includes students' satisfaction with courses and teaching, satisfaction with teacher-student interaction, satisfaction with platforms and resources, satisfaction with teaching performance, and overall satisfaction. The survey results show that students' satisfaction with courses is generally above 4 points, while their satisfaction with teaching is generally lower, ranging from 3.65 to 3.94 points. Students' satisfaction with teacher-student interaction is not very high, around 3.75. Students' satisfaction with the teaching platform is higher than that of teachers, with a score of 4.05 or more. In terms of students' satisfaction with teaching performance, male students' satisfaction is above 4.45 points, while female students' satisfaction is 4.35 points. For overall satisfaction, male students scored above 4.45, while female students scored 4.35. Since the satisfaction in all aspects is higher than 3 points, it can be seen that most English majors are quite satisfied with the online teaching. (shrink)

Since the outbreak of COVID-19, governments have turned their attention to digital contact tracing. In many countries, public debate has focused on the risks this technology poses to privacy, with advocates and experts sounding alarm bells about surveillance and mission creep reminiscent of the post 9/11 era. Yet, when Apple and Google launched their contact tracing API in April 2020, some of the world’s leading privacy experts applauded this initiative for its privacy-preserving technical specifications. In an interesting twist, the (...) tech giants came to be portrayed as greater champions of privacy than some democratic governments. This article proposes to view the Apple/Google API in terms of a broader phenomenon whereby tech corporations are encroaching into ever new spheres of social life. From this perspective, the advantage these actors have accrued in the sphere of the production of digital goods provides them with access to the spheres of health and medicine, and more worrisome, to the sphere of politics. These sphere transgressions raise numerous risks that are not captured by the focus on privacy harms. Namely, a crowding out of essential spherical expertise, new dependencies on corporate actors for the delivery of essential, public goods, the shaping of public policy by non-representative, private actors and ultimately, the accumulation of decision-making power across multiple spheres. While privacy is certainly an important value, its centrality in the debate on digital contact tracing may blind us to these broader societal harms and unwittingly pave the way for ever more sphere transgressions. (shrink)

COVID-19, the most severe public health problem to occur in the past 10 years, has greatly impacted people's mental health. Colleges in China have reopened, and how to prevent college students from suffering secondary damage due to school reopening remains elusive. This cross-sectional study was aimed to evaluate the psychological impact of COVID-19 after school reopening and explore via machine learning the factors that influence anxiety and depression among students. Among the 478 valid online questionnaires collected between (...) September 14th and September 20th, 74 showed symptoms of anxiety, and 155 showed symptoms of depression. Descriptive analysis of basic personal characteristics indicated that students at a higher grade, having relatives or friends who have been infected, fearing being infected, and having a pessimistic attitude to COVID-19 easily experience anxiety or depression. The Synthetic Minority Oversampling Technique was utilized to counteract the imbalance of retrieved data. The Akaike Information Criterion and multivariate logistic regression were performed to explore significant influence factors. The results indicate that exercise frequency, alcohol use, school reopening, having relatives or friends who have been infected, self-quarantine, quarantine of classmates, taking temperature routinely, wearing masks routinely, sleep quality, retaining holiday, availability of package delivery, take-out availability, lockdown restriction, several areas in school closed due to COVID-19, living conditions in the school, taking the final examinations after school reopening, and the degree to which family economic status is influenced by COVID-19 are the primary influence factors for anxiety or depression. To evaluate the effect of our model, we used 5-fold cross-validation, and the average area under the curve values of the receiver operating characteristic curves of anxiety and depression on the test set reached 0.885 and 0.806, respectively. To conclude, we examined the presence of anxiety and depression symptoms among Chinese college students after school reopening and explored many factors influencing students' mental health, providing reasonable school management suggestions. (shrink)

What are the main learning difficulties or advantages encountered by students with learning disabilities within e-environments? As a result of the Covid-19 emergency, e-learning is being increasingly used to support students’ learning processes. A number of countries closed their schools altogether, so face-to-face lessons were and have been replaced by distance lessons. A search of current literature via Scopus, Eric and Google Scholar electronic databases was conducted according to Prisma Guidelines. Other sources of literature (...) were also considered, starting from the references in the full text of the articles consulted. We used the following search keywords: “LDs” combined with the “AND/OR” Boolean operator and “e-learning platforms,” “well-being,” “psychological factors,” “emotional distress,” and “self-regulation.” One body of literature highlights the lack of inclusive accessibility standards and a lack of attention to specific tools for addressing LDs, which causes students to develop high levels of stress/anxiety and emotional distress, in addition to low levels of well-being, self-esteem and self-efficacy. Another area of literature looks at how students can develop high levels of self-regulation and emotional awareness, as well as high levels of inclusion. Results are discussed in terms of the promotion of e-learning that focuses on the psychological well-being of students and teachers use of technological tools. (shrink)

Debates about effective responses to the COVID-19 pandemic have emphasized the paramount importance of digital tracing technology in suppressing the disease. So far, discussions about the ethics of this technology have focused on privacy concerns, efficacy, and uptake. However, important issues regarding power imbalances and vulnerability also warrant attention. As demonstrated in other forms of digital surveillance, vulnerable subpopulations pay a higher price for surveillance measures. There is reason to worry that some types of COVID-19 technology might lead (...) to the employment of disproportionate profiling, policing, and criminalization of marginalized groups. It is, thus, of crucial importance to interrogate vulnerability in COVID-19 apps and ensure that the development, implementation, and data use of this surveillance technology avoids exacerbating vulnerability and the risk of harm to surveilled subpopulations, while maintaining the benefits of data collection across the whole population. This paper outlines the major challenges and a set of values that should be taken into account when implementing disease surveillance technology in the pandemic response. (shrink)

One of the many drastic changes caused by Covid-19 was the quick implementation of distance learning which represented a great technological challenge to many teachers and students. In fact, Italy ranks 24th amongst the 27-EU member countries in digital competitiveness which testifies to the significant delays and gaps in basic digital skills amongst the population. Based on the difficulties encountered in organizing distance learning, we assumed that teachers' perceived stress increased. Given that transversal skills can be associated (...) with this relationship, we hypothesized that among these skills, self-efficacy mediated the relationship between the difficulties in organizing distance learning and perceived stress. Since we targeted teachers from Italy and other European countries, we also hypothesized that this mediator effect would be different for both samples. Our sample was composed of a total of 366 primary/middle school teachers of which 86% female. After doing a mediation analyses with Process, Hayes' Model 4, we confirmed H1 but not H2: resulting in a partial mediation effect of self-efficacy for each individual group of teachers. Since difficulties of distance learning can affect the perception of stress, we believe that the promotion of transversal skills, such as self-efficacy, can better equip teachers when facing stressful situations. (shrink)

The increasing number of quick response code mobile payment users heralds the coming of a cashless society. However, the extent to which the coronavirus disease 2019 pandemic accelerated the adoption of QR code mobile payment has not been sufficiently researched. Based on social learning theory, this study models how external interaction with the environment has affected the internal appraisal and behavioral intention to adopt QR code mobile payment during COVID-19. Empirical results from 248 respondents revealed that perceived severity (...) and social influence positively affected the perception of utilitarian and health benefits of respondents, which in turn influenced the behavioral intention to use the QR code mobile payment. The theoretical contribution and managerial implications of this study are also discussed. (shrink)

The COVID-19 pandemic at the beginning of 2020 has changed the conventional learning mode for most students at schools all over the world, and the e-learning at home has become a new trend. Taking Chinese college students as the research subject and drawing on the stimulus–organism–response model, this paper examines the relationship between the peer referent, perceived closeness, and perceived control and the learning engagement. Using data from 377 college students who have used e-learning, this (...) study shows that perceived closeness, perceived control, and peer referents in e-learning have a positive effect on the self-efficacy and well-being of students, thus improving students’ enthusiasm for learning. Our intent is to assist researchers, instructors, designers, and others in identifying effective methods to conceptualize and measure student engagement in e-learning. (shrink)

The Covid-19 pandemic that entered our lives suddenly in 2020 compelled higher education systems throughout the world to transfer to online learning, including online evaluation. A severe problem of online evaluation is that it enables various technological possibilities that facilitate students' unethical behaviors. The research aimed to investigate these behaviors, as well as the reasons for their appearance, as practiced in exams held for the first time during the Covid-19 pandemic, and to elicit students' and lecturers' perceptions (...) of students' academic dishonesty during this period. The sample included 81 students and 50 lecturers from several Israeli colleges and universities. The findings expand extant knowledge on academic dishonesty, identifying significant differences between the perceptions of students and lecturers concerning attitudes towards online exams and the reasons for dishonest behaviors. The findings among the students also indicate that younger students and Arab students tended to cheat more in online exams. Moreover, the findings indicated a lack of mutual trust between students and lecturers with regard to academic dishonesty, a deep distrust that will probably continue even after the Covid-19 crisis. This last finding should be a cause of concern for higher education policy-makers, affecting future policies for improving lecturer-student relations, especially during crises. Recommendations are proposed for addressing academic dishonesty in exams in general and during the pandemic in particular. (shrink)

The 2019 Pandemic has forced students to take online classes, increasing their stress levels and negatively impacting their academic performance. This issue urges the development of a mechanism to make online learning more effective in this nerve-racking time. Therefore, the present study has integrated the task technology fit model and the DeLone and McLean Model of Information Systems Success to address the stated issue. The data were collected from 330 and 326 students of top-ranked public and private universities of (...) Punjab, respectively. The theoretical framework was analyzed with the help of structural equation modeling using Analysis of Moment Structures. The findings indicate that overall quality positively predicts performance through the mediating role of user satisfaction and TTF. The overall quality also positively elevates performance through the mediating role of user satisfaction and actual usage of the system. Moreover, perceived usefulness proved to be a moderator between overall quality and user satisfaction. Finally, the expected practical and theoretical implications have also been discussed. (shrink)

The COVID-19 pandemic has forced higher education institutions to shift their teaching activities from traditional face-to-face to online learning. This brings a great challenge to the creativity training of vocational college students, who not only learn theoretical knowledge but also cultivate technical skills. Therefore, it is very important to explore the influencing factors of online learning on students’ creativity during the epidemic. By relying on the related literature review, an extensive model is developed by integrating the expectation (...) confirmation model, technology task fit model, and the technology acceptance model to illustrate key factors that influence creativity. Based on the proposed model, theory-based hypotheses are tested through structural equation modeling employing empirical data gathered through a survey questionnaire of 229 students from different vocational colleges in China. In addition, to extend the analysis results, this paper performs a comparative analysis based on gender. The findings demonstrate that perceived ease of use and perceived usefulness significantly influence knowledge sharing; knowledge sharing significantly affects creativity. However, there is no substantial relationship between perceived usefulness and attitude, and no relationship between attitude and knowledge sharing. Moreover, a multi-group comparison shows that there is a significant gender difference between perceived ease of use and attitude. Based on the findings, theoretical and practical implications are discussed. (shrink)

ABSTRACT Data from digital technologies are increasingly integrated in public health research. In April of 2020, we interviewed a subset of participants who completed a survey approximately one month earlier. Using the survey, we contacted and interviewed participants who had expressed their willingness or unwillingness to share digital data for use in public health. We followed a directed content analysis approach for the analysis of the interview data. Among participants who had reported being unwilling to share data, concerns about privacy, (...) confidentiality, and the purpose of the research were cited. During the interviews, 76.9% of the participants who had who had previously indicated that they were unwilling to share their data, expressed willingness to share data in order to assist with COVID-19 prevention. Our results contribute to our understanding of people’s perspectives on sharing personal data and of the way their perspectives can vary as a function of potential uses of their personal information. (shrink)

Containing the spread of pandemic transmission tends to go hand in hand with a surveillance regime that tracks movement, transmission and those who contract the virus or disease. An enduring legacy of the COVID-19 crisis will be the incremental development of surveillance technologies, ostensibly purposed to identify the threat and spread of a pandemic, giving birth to what amounts to the pandemic surveillance state. Whether this is seen as an undesirable outcome depends very much on the field of expertise (...) and the relevant slant. Health professionals and epidemiologists favor more surveillance; privacy and data security advocates fear a further denuding of protections. This paper examines the dangers of such technologies and efforts to seek a middle ground on app technologies designed to protect privacy. Such designs may, in time, seem more hopeful than actual. (shrink)

Mobile phone-based applications (apps) can promote faster targeted actions to control COVID-19. However, digital contact tracing systems raise concerns about data security, system effectiveness, and their potential to normalise privacy-invasive surveillance technologies. In the absence of mandates, public uptake depends on the acceptability and perceived legitimacy of using technologies that log interactions between individuals to build public health capacity. We report on six online deliberative workshops convened in New South Wales to consider the appropriateness of using the COVIDSafe app (...) to enhance Australian contact tracing systems. All groups took the position (by majority) that the protections enacted in the app design and supporting legislation were appropriate. This support is contingent on several system attributes including: the voluntariness of the COVIDSafe app; that the system relies on proximity rather than location tracking; and, that data access is restricted to local public health practitioners undertaking contact tracing. Despite sustained scepticism in media coverage, there was an underlying willingness to trust Australian governing institutions such that in principle acceptance of the new contact tracing technology was easy to obtain. However, tensions between the need to prove system effectiveness through operational transparency and requirements for privacy protections could be limiting public uptake. Our study shows that informed citizens are willing to trade their privacy for common goods such as COVID-19 suppression. But low case numbers and cautionary public discourses can make trustworthiness difficult to establish because some will only do so when it can be demonstrated that the benefits justify the costs to individuals. (shrink)

Nowadays, the whole world is facing a pandemic situation in the form of coronavirus diseases. In connection with the spread of COVID-19 confirmed cases and deaths, various researchers have analysed the impact of temperature and humidity on the spread of coronavirus. In this paper, a deep transfer learning-based exhaustive analysis is performed by evaluating the influence of different weather factors, including temperature, sunlight hours, and humidity. To perform all the experiments, two data sets are used: one is (...) taken from Kaggle consists of official COVID-19 case reports and another data set is related to weather. Moreover, COVID-19 data are also tested and validated using deep transfer learning models. From the experimental results, it is shown that the temperature, the wind speed, and the sunlight hours make a significant impact on COVID-19 cases and deaths. However, it is shown that the humidity does not affect coronavirus cases significantly. It is concluded that the convolutional neural network performs better than the competitive model. (shrink)

We explore multi-scale relations in artificial intelligence (AI) use in order to identify difficulties with coordinating relations between users, machine learning (ML) processes, and “sociobuilt contexts”—specifically in terms of their applications to medical technologies and decisions. We begin by analyzing a recent COVID-19 machine learning case study in order to present the difficulty of traversing the detailed causal topography of “sociobuilt contexts.” We propose that the adequate representation of the interactions between social and built processes that occur (...) on many scales ought to drive interdisciplinary approaches for ML modification. Next, we describe ML algorithm development as a process that is partly dependent on methodological stabilization for reliability and partly on coordinating relations. In the coordination between user, ML process, and sociobuilt contexts, we propose that new methods can be explored that promote the inclusion of patients and communities for the purpose of cross-checking portions of the ML process. Finally, we suggest that the advantages of responsible innovation emerge through the iterative entanglement of ethical, methodological, and ontological considerations within the broader conceptual infrastructure of epistemic responsibility. (shrink)

The spread of the COVID-19 pandemic quickly necessitated digital learning, which bore challenges for all pupils but especially for groups disadvantaged in a virtual classroom. As some studies indicate persistent differences between boys and girls in use of technologies and related skills, the aim of this study was to investigate gender differences in the digital learning environment students faced in spring 2020. Previous studies investigating gender differences in digital learning largely used biological sex as the only (...) indicator of gender. This study includes both biological sex and gender role self-concept in order to investigate the role of gender in different components of this stereotyped domain in a more differentiated way. A total of 19,190 Austrian secondary school students participated in an online study in April 2020 and answered questions regarding their competence beliefs, intrinsic value, engagement, and perceived teacher support in digital learning during the pandemic-induced school closures. Results showed higher perceived teacher support, intrinsic value, and learning engagement among girls than boys, while no significant sex differences were found in competence beliefs regarding digital learning. Furthermore, our results indicated clear benefits of an androgynous gender role self-concept for all studied components of digital learning. Implications of the findings for theory and practice are discussed. (shrink)

Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work (...) of Gilbert Simondon, with its critique of Norbert Wiener‘s first-order cybernetics, offers a precursor to the conception of second-order cybernetics (as endorsed byFrancisco Varela, Humberto Maturana, and Ricardo B. Uribe) and, specifically, its autopoietic treatment of information. It has been argued by those such as Frank Pasquale that neuro-inferential deep learning systems premised on predictive patterning, suchas AlphaGo Zero, have a veiled logic and, thus, are ̳black boxes‘. In detailing a philosophical-historical approach to demystify predictive patterning/processing and the logic of such deep learning algorithms, this paper attempts to shine a light on such systems and their inner workingsàla Simondon. (shrink)

With the rapid growth of informatics systems’ technology in this modern age, the Internet of Things (IoT) has become more valuable and vital to everyday life in many ways. IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. IoT (...) systems have several security limitations due to their disreputability characteristics, like dynamic communication between IoT devices. The dynamic communications resulted from the limited resources of these devices, such as their data storage and processing units. Recently, many attempts have been made to develop intelligent models to protect IoT networks against DDoS attacks. The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. The intrusion detection evaluation dataset (CICIDS2017) is used to provide more realistic detection. The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. The performance of the models is quite effective as they obtain an accuracy rate of around 99.00%, except for the CNN model, which achieves an accuracy of 98.82%. The CNN-BiLSTM achieves the best accuracy of 99.76% and precision of 98.90%. (shrink)

Nowadays, higher education worldwide is affected by the COVID-19 pandemic. It has affected students’ attendance in the universities and causes universities to close down in more than 190 countries. On the other hand, novice engineers studied only a few lectures related to highway engineering. Their lectures have included very little knowledge about asphalt pavement construction as highway engineering consists of many areas that are not studied in detail during their studying years subject to their traditional education. Due to all (...) mentioned, a new drive to promote online learning paves the way to evaluate our future approach to curriculum development and delivery of educational materials for engineering courses. However, experts can offer solutions to these problems using their past experience. Hence, a system that allows experts to share their experience with other engineers after completing a project is needed. Nevertheless, the web-based expert system for maintaining flexible pavement problems in tropical regions designed in this study is a novel concept. Prior to developing this system, the need for such a system was determined through literature review and validated through a questionnaire survey. Experts were interviewed, and a questionnaire survey was conducted to construct the knowledge base of the system. Knowledge was presented as rules and coded in software through PHP programming. Web pages that support the user interface were designed using a framework that consists of CSS, HTML, and J-Query. Furthermore, the system was tested by an array of users engaged in highway engineering, namely, experts, teaching experts, novice engineers, and students. The mean values of the overall system evaluation performed by 20 users using a five-point Likert scale were 4, 4.5, 3.75, 4.25, 5, 4, and 3.5. Expert and user satisfaction prove the effectiveness of the proposed system. (shrink)

Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, (...) this article argues, are not just a quantitative expansion of epidemiology’s scope, but a qualitative extension of its analytical traditions. Digital epidemiology is enabled by deep and digital phenotyping, the large-scale re-purposing of any data scraped from the digital exhaust of human behaviour and social interaction. This technological innovation is in need of critical examination, as it poses a significant epistemic shift to the production of pathological knowledge. This article offers a critical revision of the key literature in this budding field to underline the extent to which digital epidemiology is envisioned to redefine the classification and understanding of disease from the ground up. Utilising analytical tools from science and technology studies, the article demonstrates the disruptive expectations built into this expansion of epidemiological surveillance. Given the sweeping claims and the radical visions articulated in the field, the article develops a tentative critique of what I call a fantasy of pathological omniscience; a vision of how data-driven engineering seeks to capture and resolve illness in the world, past, present and future. (shrink)

Providing high-quality education for students with emergent proficiency in the language of instruction (referred to here as multilingual students) presents a challenge to inclusion for educational systems the world over. In Austria, a new German language support model was implemented in the school year 2018/19 which provides language support in separate classrooms up to 20 h a week. Since its implementation, the model has been strongly criticized for excluding multilingual students from the mainstream classroom, which is argued to reinforce the (...) educational disadvantages that they face. The study presented here provides unprecedented qualitative insight into how schooling for students within the so-called German language support classes (GLSC) was organized during the COVID-19 pandemic. It builds on results of a previous large-scale quantitative study (n= 3,400 teachers), which was conducted during the first lockdown (spring 2020) and indicated a high risk of exclusion for marginalized students, especially for multilingual students in GLSC. To gain deeper insights into the situation of these students during school closures, 37 teachers who work in these classes at both primary and lower-secondary schools in Vienna were interviewed, of which 18 interviews were considered for analysis. The interviews focus on the situation during the first and second school closures in the city of Vienna. A thematic analysis of the interview data reveals teachers’ perceptions of aspects which harmed or promoted inclusion for students in GLSC during these periods of school closure. Teachers’ perceptions of the most harming factors for students included strong language barriers between teachers and students, restricted access to technical equipment and supportive learning spaces, and low parental engagement. A development that promoted inclusion of these students was the option to allow them to come to school during the second school closure. Since existing studies on the schooling of students during school closures have hardly addressed the situation of students in GLSC, this study contributes to closing this research gap. (shrink)

Turkey and many countries, the school has closed, or partially or completely due to covid 19 pandemic. Schools remained closed until a certain time in Turkey. Afterwards, its opening has been postponed until certain dates. In the second half of 2019-2020 and in the first and second half of 2020-2021, students were mostly deprived of face-to-face education. This study, which aims to describe the problems experienced by RE teachers in the learning-teaching process during the epidemic period, (...) was designed according to a case study, one of the qualitative research methods. The study group consists of 8 RE teachers, four of them male and four female. The data collection tool is a semi-structured interview form. The data were subjected to content analysis, and NVIVO 12 program was used. RE teachers experienced problems regarding technique, absenteeism, pre-lesson preparation, learning environment, teaching methods, motivation, communication, time and measurement-evaluation. Although these negative situations have occurred, it can be said that teachers are willing to use the gains in distance education with normalization and aim to take learning out of the classroom in this way. It can be suggested to researchers to study the concepts of classroom privacy and digital world ethics within the framework of education. Improving the technology use competencies of RE teachers can also be suggested to the relevant institutions. (shrink)

In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts (...) at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice. (shrink)

The ongoing coronavirus 2019 pandemic caused by the severe acute respiratory syndrome coronavirus 2 has resulted in a severe ramification on the global healthcare system, principally because of its easy transmission and the extended period of the virus survival on contaminated surfaces. With the advances in computer-aided diagnosis and artificial intelligence, this paper presents the application of deep learning and adversarial network for the automatic identification of COVID-19 pneumonia in computed tomography scans of the lungs. The complexity (...) and time limitation of the reverse transcription-polymerase chain reaction swab test makes it disadvantageous to depend solely on as COVID-19’s central diagnostic mechanism. Since CT imaging systems are of low cost and widely available, we demonstrate that the drawback of the RT-PCR can be alleviated with a faster, automated, and reduced contact diagnostic process via the use of a neural network model for the classification of infected and noninfected CT scans. In our proposed model, we explore the benefit of transfer learning as a means of resolving the problem of inadequate dataset and the importance of semisupervised generative adversarial network for the extraction of well-mapped features and generation of image data. Our experimental evaluation indicates that the proposed semisupervised model achieves reliable classification, taking advantage of the reflective loss distance between the real data sample space and the generated data. (shrink)

This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within “e-learning in higher education.” E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of (...) the field. These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published in the Web of Science database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning. This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis. (shrink)

Online learning is becoming a commonplace in different settings starting from elementary, secondary and higher levels of education. Different educational institutions use different communication tools to promote learning because the expansive nature of the Internet and the accessibility of technology have generated a surge in the demand for web-based teaching and learning across the nations (Chaney, 2010). The online teaching and learning have become a necessity for education around the globe during COVID 19-pandemic. There are (...) several challenges which are faced during online classes because the students must have strong self-motivation skills and be very disciplined to achieve the desired learning results. This paper presents and analyzes the data on the benefits and challenges of online teaching at South East European University (SEEU) during COVID 19 pandemic. The participants of the study are students of the BA level majoring in English Language and Literature and German Language and Literature at SEEU in Tetovo, North Macedonia. To answer the research questions, we have used a student questionnaire, interviews, and student reflection papers written during the online courses. Overall, the research indicates that benefits of online coursework outweigh the challenges that students face during the online classes. From a safety perspective, this study emphasizes the need to consider the impact of online teaching on student motivation and the paper raises important questions about how to best support students enrolled in online courses. Further research is needed in order to better evaluate the benefits, challenges, and useful strategies of successful students enrolled in online courses. (shrink)

The COVID-19 pandemic may have left many of us needing closeness with others more than we have before. Three contexts in which we may especially need this closeness are (1) when we must triage and some but not all will benefit, (2) when families may be separated from loved ones who have COVID-19, and (3) when people for any reason experience shame. In this article I examine sources of present, harmful emotional distancing. I suggest how we might do (...) better in each of these contexts due to what the COVID-19 pandemic can teach us. (shrink)

The article entitled “Post-COVID-19: Education and Thai Society in Digital Era” has two objectives: 1) to study digital technology 2) to study the living life in Thailand in the digital era after COVID-19 pandemics. According to the study, it was found that the new digitized service is a service process on digital platforms such as ordering food, hailing a taxi, and online trading. It is a service called via smartphone. The information is used digitally. Public relations, digital marketing, (...) and living in cyberspace play an increasingly digital role. People have communication skills, use Line, Facebook, social media, have tools to search for knowledge, learn and improve themselves. People in the new era of life have a new way of life therefore there is social life in the cyber world. There should be ethics, attitudes, values, and click-on images that are linked to digital use. For a good time life, It is important to have digital intelligence (Digital Quotient) to live after post-COVID19, the digital era. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Live Like Nobody Is Watching: Relational Autonomy in the Age of Artificial Intelligence Health Monitoring by Anita HoTina Nguyen (bio)Live Like Nobody Is Watching: Relational Autonomy in the Age of Artificial Intelligence Health Monitoring by Anita Ho New York: Oxford University Press, 2023As the reach of artificial intelligence (AI)- and machine learning (ML)-enabled technologies continues to expand in the healthcare field, bioethicists have examined the ethical issues (...) that come as a result of using these technologies. In this ethical assessment, most bioethicists, myself included, have discussed how AI/ML violates the ethical principle of autonomy. The commonly cited definition of autonomy comes from Beauchamp and Childress's Principles of Biomedical Ethics (2019), where autonomy is the right of the individual to make decisions for themselves. However, autonomy regarding AI/ML in healthcare has not been or is rarely discussed from the feminist perspective. In Live Like Nobody Is Watching: Relational Autonomy in the Age of Artificial Intelligence Health Monitoring (further referred to as Live Like Nobody Is Watching), Anita Ho, in addition to other points, argues that AI for health monitoring needs to be examined through a relational autonomy lens. Not only is this perspective innovative but it also shows how a predominantly male field has shaped the narrative surrounding AI/ML. In this review, I provide a brief overview of the chapters, explore Ho's arguments for relational autonomy, and discuss future applications of this work.Live Like Nobody Is Watching begins with a preface where the readers are introduced to a real-life scenario. Ho describes a friend's experience of [End Page 101] debating with themself whether to use surveillance for their mother with early-stage dementia who claims someone has been moving her things. This sets up the rest of the book in which questions of should these technologies be used and in what context are they appropriate are debated using relational autonomy. The introduction serves as a brief primer to AI (ML and deep learning) and its role in healthcare followed by a layout of the subsequent chapters. Chapter 1 connects health monitoring AI with relational autonomy, where Ho suggests that the liberal view of autonomy is not appropriate for health monitoring technologies. This is due to the fact that the patient populations using these technologies are reliant, to various degrees, on social relationships. In chapters 2, 3, and 4, Ho addresses how health-monitoring AI requires relational autonomy through use cases concerning home-health monitoring, direct-to-consumer monitoring, and AI monitoring for medication adherence. Throughout these chapters, Ho discusses the claimed benefits of these AI/ML interventions and cautions about the ethical challenges, such as health inequities and testimonial injustice, that can arise with these technologies. Finally, chapter 5 serves as the conclusion, where Ho ultimately argues that health-monitoring AI should be viewed through relational autonomy instead of the traditional view, and she advocates for dialogic engagement (including bringing patients/patients' families into the conversation). The narrative goes full circle with the events in the preface being addressed in the epilogue, where the friend decided to incorporate a smart frame device that would allow them to have video calls with their mother. However, the friend is still grappling with the idea of surveillance given an incident in which another dementia resident accidentally wandered into their mother's room. To this, Ho ends the book by proposing better lighting in the hallways rather than immediately turning to the next high-tech innovation.Ho presents several arguments throughout the book but emphasizes the main argument that relational autonomy should be practiced over the traditional, liberal view of autonomy. Ho discusses the three elements of socio-relational autonomy (using Catriona Mackenzie's work): self-governance, self-determination, and self-authorization. Components of the traditional bioethical view of autonomy are seen in these three elements, with the process of informed consent being closely tied to the concept of autonomy. Under the traditional view, an autonomous individual should have decision-making capacity and be able to make a decision based on the information provided to them without coercion. In the informed consent process, patients should be provided adequate information along with... (shrink)

In most European countries, the first wave of the COVID-19 pandemic led to the imposition of physical distancing rules, resulting in a drastic and sudden reduction of real-life social interactions. Even people not directly affected by the virus itself were impacted in their physical and/or mental health, as well as in their financial security, by governmental lockdown measures. We investigated whether the combination of these events had changed people's appraisal of social scenes by testing 241 participants recruited mainly in (...) Italy, Austria, and Germany in an online, preregistered study conducted about 50 days after the beginning of the COVID-19 outbreak in Europe. Images depicting individuals alone, in small groups, and in large groups were rated in terms of valence, arousal, and perceived physical distance. Pre-pandemic normative ratings were obtained from a validated database. Several self-report measures were also taken, and condensed into four factors through factor analysis. All images were rated as more arousing compared to the pre-pandemic period, and the greater the decrease in real-life physical interactions reported by participants, the higher the ratings of arousal. As expected, only images depicting large gatherings of people were rated less positively during, compared to before, the pandemic. These ratings of valence were, however, moderated by a factor that included participants' number of days in isolation, relationship closeness, and perceived COVID-19 threat. Higher scores on this factor were associated with more positive ratings of images of individuals alone and in small groups, suggesting an increased appreciation of safer social situations, such as intimate and small-group contacts. The same factor was inversely related to the perceived physical distance between individuals in images of small and large groups, suggesting an impact of lockdown measures and contagion-related worries on the representation of interpersonal space. These findings point to rapid and compelling psychological and social consequences of the lockdown measures imposed during the COVID-19 pandemic on the perception of social groups. Further studies should assess the long-term impact of such events as typical everyday life is restored. (shrink)