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While research on digital dangers has been growing, studies on their respective solutions and justice responses have not kept pace. The agathokakological nature of technology demands that we pay attention to not only harms associated with interconnectivity, but also the potential for technology to counter offenses and “do good.” This chapter discusses technology as both a weapon and a shield when it comes to violence against women and girls in public spaces and private places. First, we review the complex and varied manifestations of technological gender violence, ranging from the use of technology to exploit, harass, stalk, and otherwise harm women and girls in communal spaces, to offenses that occur behind closed doors. Second, we discuss justice-related responses, underscoring how women and girls have “flipped the script” when their needs are not met. By developing innovative ways to respond to the wrongs committed against them and creating alternate systems that offer a voice, victims/survivors have repurposed technology to redress harms and unite in solidarity with others in an ongoing quest for justice.

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.

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.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

Large-scale data analytics have raised a number of ethical concerns. Many of these were introduced in a seminal paper by boyd and Crawford and have been developed since by others (boyd & Crawford, 2012; Lagoze, 2014; Martin, 2015; Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016). One such concern which is frequently recognised but under-analysed is the focus on correlation of data rather than on the causative relationship between data and results. Advocates of this approach dismiss the need for an understanding of causation, holding instead that the correlation of data is sufficient to meet our needs. In crude terms, this position holds that we no longer need to know why X+Y=Z. Merely acknowledging that the pattern exists is enough.

In this chapter, the author explores the ethical implications and challenges surrounding a focus on correlation over causation. In particular, the author focusses on questions of legitimacy of data collection, the embedding of persistent bias, and the implications of future predictions. Such concerns are vital for understanding the ethical implications of, for example, the collection and use of ‘big data’ or the covert access to ‘secondary’ information ostensibly ‘publicly available’. The author’s conclusion is that by failing to consider causation, the short-term benefits of speed and cost may be countered by ethically problematic scenarios in both the short and long term.

Reality breakdowns generate reflexivity and awareness of the constructed nature of social reality. These pivotal moments can motivate institutional inhabitants to either modify their social worlds or reaffirm the status quo. Thus, reality breakdowns are the initial points at which actors can conceive of new possibilities for institutional arrangements and initiate change processes to realize them. Studying reality breakdowns enables scholars to understand not just how institutional change occurs, but also why it does or does not do so. In this paper, we investigate how institutional inhabitants responded to a reality breakdown that occurred during our ethnography of collegial governance in a large North American university that was undergoing a strategic change initiative. Our findings suggest that there is a consequential process following reality breakdowns whereby institutional inhabitants construct the severity of these events. In our context, institutional inhabitants first attempted to restore order to their social world by reaffirming the status quo; when their efforts failed, they began to formulate alternative possibilities. Simultaneously, they engaged in a distributed sensemaking process whereby they diminished and reoriented necessary changes, ultimately inhibiting the formulation of these new possibilities. Our findings confirm reality breakdowns and institutional awareness as potential drivers of institutional change and complicate our understanding of antecedent microprocesses that may forestall the initiation of change efforts.

Divestitures and other forms of organizational separation are not commonly associated with continuity and ongoing collaboration in inter-organizational relationships. Instead, separation is often equated with terminating relationships and gaining independence. Here, the authors argue that achieving separation does not require terminating relationships and that ongoing collaboration between separating entities may actually contribute to successful separation. The authors base this argument on the assertion that the objective of organizational separation is to achieve organizational autonomy for all entities involved and that separating entities can enable each other’s development of autonomy while remaining interdependent. The authors also discuss how collaborative separation may contribute to a range of benefits, as well as why it may nevertheless fail to emerge in practice. In this respect, the authors consider the relevance of ethical perspectives and emotional dynamics related to feelings of (dis)respect, (dis)trust, pride and shame. The authors conclude by discussing activities that may contribute to, and undermine, effective collaborative separation.

This chapter examines how implementation of SDG solutions can be improved through adaptive strategies. Many so-called blueprint strategies are inflexible during implementation and underestimate the importance fitting general goals and plans to shifting local needs and contexts. The chapter emphasizes the importance of identifying the specific types of dynamic challenges that will prompt the need for adaptation when implementing sustainability strategies. Adaptive cocreation provides a valuable framework for overcoming traps of various sorts that may block implementation. The problem-driven iterative adaptation (PDIA) model is introduced as one approach to adaptation. PDIA is particularly valuable for achieving bottom-up integration of SDGs and projects. Finally, the chapter considers the importance of social learning as a strategy for collaborative adaptation.

This chapter explores the norms and assumptions that frame and sustain international drug policy and the international drug control regime. Drug policy is conceptualised as a ‘policy fiasco’ that persists despite extensive evidence of goal failure. The absence of effective monitoring and evaluation, impact assessment, stakeholder participation and mainstreaming of rights-based approaches, conflict sensitivity and gender sensitivity is emphasised, substantiating the argument that drug policy is a case study of ‘institutional path dependence’. Drug policy has repeatedly missed targets for achievement of a ‘drug free world’. This is explained through reference to the counterproductive and ‘unintended consequences’ of a drug policy approach of criminalisation. The impacts of drug policy enforcement are shown to be negative, pernicious and disproportionately born by the poor, by vulnerable communities and those subject to discrimination on account of race, gender and class.