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This chapter, based on a sociological approach, addresses the ethical issues of surveillance research from the perspective of the profound transformations that science and innovation are undergoing, as part of a broader shift from modern to post-modern society, affecting also other major social institutions (such as government, religion, family, and public administration). The change occurring in the science and technology system is characterised by diminishing authority, uncertainty about internal mechanisms and standards, and a declining and increasingly difficult access to resources. Such changes, also related to globalisation and new digital technologies, have transformed the way research is conducted and disseminated. Research is now more open and its results more easily accessible to citizens.

Scientific research is also put under increased public scrutiny, while, at the same time, public distrust and disaffection towards science is rising. In such a context, it is more important than ever to make sure that research activities are not compromised by fraudulent and unethical practices. The legitimate expectations of citizens to enjoy their rights, including the ability to protect their private sphere, are growing. Scientific and technological development is deeply interrelated with the widespread awareness of these rights and the possibility of exercising them, but it produces also new risks, while a widespread sense of insecurity increases. The digital revolution, while improving people’s quality of life, offers at the same time new opportunities for crime and terrorism, which in turn has produced a demand to strengthen security systems through increasingly advanced and intrusive surveillance technologies. Misconduct in the field of surveillance may not only undermine the quality of research, but also further impair society’s trust in research and science as well as in the State and its institutions.

Work-life flexibility policies (e.g., flextime, telework, part-time, right-to-disconnect, and leaves) are increasingly important to employers as productivity and well-being strategies. However, policies have not lived up to their potential. In this chapter, the authors argue for increased research attention to implementation and work-life intersectionality considerations influencing effectiveness. Drawing on a typology that conceptualizes flexibility policies as offering employees control across five dimensions of the work role boundary (temporal, spatial, size, permeability, and continuity), the authors develop a model identifying the multilevel moderators and mechanisms of boundary control shaping relationships between using flexibility and work and home performance. Next, the authors review this model with an intersectional lens. The authors direct scholars’ attention to growing workforce diversity and increased variation in flexibility policy experiences, particularly for individuals with higher work-life intersectionality, which is defined as having multiple intersecting identities (e.g., gender, caregiving, and race), that are stigmatized, and link to having less access to and/or benefits from societal resources to support managing the work-life interface in a social context. Such an intersectional focus would address the important need to shift work-life and flexibility research from variable to person-centered approaches. The authors identify six research considerations on work-life intersectionality in order to illuminate how traditionally assumed work-life relationships need to be revisited to address growing variation in: access, needs, and preferences for work-life flexibility; work and nonwork experiences; and benefits from using flexibility policies. The authors hope that this chapter will spur a conversation on how the work-life interface and flexibility policy processes and outcomes may increasingly differ for individuals with higher work-life intersectionality compared to those with lower work-life intersectionality in the context of organizational and social systems that may perpetuate growing work-life and job inequality.

Building on work that explores the relationship between individual beliefs and ability to recognize discrimination (e.g., Kaiser and Major, 2006), we examine how an adherence to beliefs about gender essentialism, gender egalitarianism, and meritocracy shape one’s interpretation of an illegal act of sexual harassment involving a male supervisor and female subordinate. We also consider whether the role of the gendered culture of engineering (Faulkner, 2009) matters for this relationship. Specifically, we conducted an online survey-experiment asking individuals to report their beliefs about gender and meritocracy and subsequently to evaluate a fictitious but illegal act of sexual harassment in one of two university research settings: an engineering department, a male-dominated setting whose culture is documented as being unwelcoming to women (Hatmaker, 2013; Seron, Silbey, Cech, and Rubineau, 2018), and an ambiguous research setting. We find evidence that the stronger one’s adherence to gender egalitarian beliefs, the greater one’s ability to detect inappropriate behavior and sexual harassment while gender essentialist beliefs play no role in their detection. The stronger one’s adherence to merit beliefs, the less likely they are to view an illegal interaction as either inappropriate or as sexual harassment. We account for respondent knowledge of sexual harassment and their socio-demographic characteristics, finding that the former is more often associated with the detection of inappropriate behavior and sexual harassment at work. We close with a discussion of the transferability of results and policy implications of our findings.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

Professional associations mark an important step in the development of any profession. Research Management and Administration (RMA) as a profession is still emerging across Europe, thus the relevance of RMA associations is pertinent. These associations operate either specifically at the transnational or international levels or have certain activities linked to both levels. The theory of social constructivism from the field of international relations will be applied in this analysis with a goal to add additional insights on the topic. The results confirm that RMA associations have an outstanding role in enforcing the internationalised culture of their members, however, members in return can also exert influence on their association. Members are also aware that the association is providing a platform for collective actions in policymaking at national, transnational, and international levels. However, time plays a crucial role in social learning for identity and interest formation, as well as in recognizing the role of RMA associations in corporate agency.

Innovation in a decentralized blockchain infrastructure can be used by medicine as a prerequisite for the exchange of patient data. Developments in the medical device industry that support the technology of the internet of things and wireless sensor networks also facilitate the examination of patient medical records that no longer require visits to the practice of doctors or hospitals which in some cases takes in a considerable time. Not to mention the consideration of traffic congestion and busy routine in the work. Patients can check their healthcare concerns using only sensors such as e-Health Sensor Shield Platform which then sends recording results through the transmission line to the data lakes. However, this patient’s medical record data is very confidential and may only be accessed by certain parties only. This required the design of the concept of security in the transmission of data so that the data does not leak to parties who are not eligible. This paper attempts to provide an overview of the concept of using encryption with an asymmetric key for securing data from sensors to data lakes before forwarding to a decentralized, interconnected blockchain infrastructure.

The growth in cryptomarkets has reinvigorated the research on illicit drug distribution due to the availability of large-scale data. This data has enabled researchers to ask new and detailed questions about how participants in these markets trust each other enough for the market not to collapse. This question deserves more attention because it has become a taken-for-granted notion that repeated transactions and social categories create trust. Whether online or on the street, economic exchanges under illegality are more uncertain than transactions in the legal economy. This puts higher demands on trust, as there is less information and the stakes are higher. In this chapter, the author presents definitions, typologies, and disciplinary contributions to the study of trust and examine how it has been operationalised in a sample of 13 peer-reviewed articles. These articles focus on three dimensions of trust: process-based trust that derives from repeated transactions with known partners; character-based trust measured by the networked reputation scores; and institutional-based trust in the platform and its administrators. In practice, the trust bases are intertwined. Drawing on the broader social science literature on trust, a mesolevel operationalisation that centres on networked reputation scores as embedded in processes and institutions can draw the research together in a multidisciplinary framework.

This first chapter explores the basic foundation of corporate ethics: the human person in all its dignity and mystery, its corporeality and emotionality, and its cognitive and volitive capacities of moral development. Four fundamental characteristics of the human person, namely individuality, sociality, immanence, and transcendence, will be examined for their potential to understand, live, experience, and witness corporate ethics and morals. We explore the profound meaning and mystery of human personhood invoking several philosophies of the good and human dignity as exposed by Aristotle and Thomas Aquinas in the West, by the doctrine of Dharma in the East as expounded by Gautama Buddha, Mahabharata, and Bhagavad Gita, and by Prophets Confucius and Tao, in the East. Several contemporary cases of great human personhood are analyzed: for example, Peace Nobel Laureate Nelson Mandela from South Africa (1993) and Peace Nobel Laureate Liu Xiaobo from China (2017) – cases of human abuse that turned into triumphs of human dignity.