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Perpetrators of technology-facilitated gender-based violence are taking advantage of increasingly automated and sophisticated privacy-invasive tools to carry out their abuse. Whether this be monitoring movements through stalkerware, using drones to nonconsensually film or harass, or manipulating and distributing intimate images online such as deepfakes and creepshots, invasions of privacy have become a significant form of gender-based violence. Accordingly, our normative and legal concepts of privacy must evolve to counter the harms arising from this misuse of new technology. Canada's Supreme Court recently addressed technology-facilitated violations of privacy in the context of voyeurism in R v Jarvis (2019) . The discussion of privacy in this decision appears to be a good first step toward a more equitable conceptualization of privacy protection. Building on existing privacy theories, this chapter examines what the reasoning in Jarvis might mean for “reasonable expectations of privacy” in other areas of law, and how this concept might be interpreted in response to gender-based technology-facilitated violence. The authors argue the courts in Canada and elsewhere must take the analysis in Jarvis further to fully realize a notion of privacy that protects the autonomy, dignity, and liberty of all.

This article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.

The author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.

After presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

As a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.

The paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

The paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.

This research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.

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.

This paper aims to interpret the multidimensional Asian American identity of immigrant Indians in terms of pan-ethnicity, gender and religion.

The social construction and experience of race in the US and the intersection of multiethnic Asian American identity with race, gender and religion will be used in critically commenting on the interview of primary ethnic identity of Indian Americans including the pan-ethnic identity of Indians in the US as Asian Americans, the Mar Thoma Church community, the second-generation Patel family's union formation in terms of gender identity.

The future directives include Asian American Movement (AAM) which is trying to incorporate Indians as pan-ethnic identity assimilation and the process of holding American identity as primary identification of Indians.

Policy recommendations are that the US Census Bureau should include Indian Americans as separate ethnic identity for Indian immigrants like the Chinese Americans. USCIS (US Citizenship and Immigration Services) should reform policies to include the wives of H-4 visa holders. The Department of Homeland Security (DHS) should provide secure living environment for Indian immigrants. The US Department of Labor should provide equal opportunities for women in their immigration policies.

This paper will critically analyze the interview results of primary ethnic identity and justify the hypotheses of Asian American identity of Indians, whether (1) they merge with the American identity as part of cultural assimilation or (2) retain their Asian identity beyond Americanized identity or (3) go beyond both American and Asian identity to restate their Indian ethnicity.

The purpose of this paper is to examine whether the impact of persistent racial bias, discrimination and racial violence is facilitated by otherwise well-intentioned individuals who fail to act or intercede. Utilizing the aversive racism framework, the need to move beyond awareness raising to facilitate behavioral changes is discussed. Examining the unique lens provided by the aversive racism framework and existing research, the bystander effect provides important insights on recent acts of racial violence such as the murder of Mr. George Floyd. Some promise is shown by the work on effective bystander behavior training and highlights the need for shared responsibility in preventing the outcomes of racial violence and discrimination to create meaningful and long-lasting social change.

This paper uses literature based on the aversive racism framework together with the literature on the bystander effect to understand the factors, conditions and consequences for lack of intervention when the victim is African American. This paper also provides evidence and theory-based recommendations for strategies to change passive bystanders into active allies.

The use of the aversive racism framework provides a powerful lens to help explain the inconsistencies in the bystander effect based on the race of the victim. The implications for intervention models point to the need for behavioral and competency-based approaches that have been shown to provide meaningful change.

Several different approaches to address incidents of racial aggression and violence have been developed in the past. However, given the principles of aversive racism, a unique approach that considers the inconsistencies between self-perceptions and actions is needed. This sets a new agenda for future research and meaningful behavioral intervention programs that seek to equip bystanders to intercede in the future.

The need to address and provide effective strategies to reduce the incidence of racial aggression and violence have wide-ranging benefits for individuals, communities and society.

By connecting the aversive racism framework to the bystander effect, the need for different models for developing responsive and active bystanders can be more effectively outlined.

Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpose of this research is to explore the perceptions of the UK digital contact tracing app in the Black, Asian and Minority Ethnic (BAME) community in Leicester and how this can affect its deployment and implementation.

Data was collected through virtual focus groups in Leicester, UK. A total of 28 participants were recruited for the study. All participants are members of the BAME community, and data was thematically analysed with NVivo 11.

A majority of the participants were unwilling to download and use the app owing to legal and ethical concerns. A minority were willing to use the app based on the need to protect public health. There was a general understanding that lack of uptake will negatively affect the fight against COVID-19 in BAME communities and an acknowledgement of the need for the government to rebuild trust through transparency and development of regulatory safeguards to enhance privacy and prevent misuse.

To the best of the authors’ knowledge, the research makes original contributions being the first robust study conducted to explore perceptions of marginalised communities, particularly BAME which may be adversely impacted by the deployment of the app. By exploring community-based perceptions, this study further contributes to the emerging citizens’ perceptions on digital contact tracing which is crucial to the effectiveness and the development of an efficient, community-specific response to public attitudes towards the app. The findings can also help the development of responsible innovation approaches that balances the competing interests of digital health interventions with the needs and expectations of the BAME community in the UK.

Digital technologies, and the affordances they provide, can shape institutional processes in significant ways. In the last decade, social media and other digital platforms have redefined civic engagement by enabling new ways of connecting, collaborating, and mobilizing. In this article, we examine how technological affordances can both enable and hinder institutional processes through visibilization – which we define as the enactment of technological features to foreground and give voice to particular perspectives and discourses while silencing others. We study such dynamics by examining #SchauHin, an activist campaign initiated in Germany to shine a spotlight on experiences of daily racism. Our findings show how actors and counter-actors differentially leveraged the technological features of two digital platforms to shape the campaign. Our study has implications for understanding the role of digital technologies in institutional processes as well as the interplay between affordances and visibility in efforts to deinstitutionalize discriminatory practices and institutions.

This paper aims to contribute to understandings of the dynamics of marketplace exclusion and explore the benefits of a performative approach to knowledge production.

Interactive documentary theatre is used to explore the pressing issue of marketplace exclusion in a deprived UK city. The authors present a series of three vignettes taken from the performance to explore the embodied and dialogical nature of performative knowledge production.

The performative mode of knowledge production has a series of advantages over the more traditional research approaches used in marketing. It is arguably more authentic, embodied and collaborative. However, this mode of research also has its challenges particularly in the interpretation and presentation of the data.

The paper highlights the implications of performative knowledge production for critical consumer learning. It also explores how the hitherto neglected concept of marketplace exclusion might bring together insights into the mechanics and outcomes of exclusion.

While theatrical and performative metaphors have been widely used to theorise interactions in the marketplace, as yet the possibility of using theatre as a form of inquiry within marketing has been largely neglected. Documentary theatre is revealing of the ways in which marketplace cultures can perpetuate social inequality. Involving local communities in the co-production of knowledge in this way gives them a voice in the policy arena not hitherto fully addressed in the marketing field. Similarly, marketplace exclusion as a concept has been sidelined in favour of marketplace discrimination and consumer vulnerability – the authors think it has the potential to bring these fields together in exploring the range of dynamics involved.

This paper aims to critically examine the digital transformation of anti-money laundering (AML) and countering the financing of terrorism (CFT) in light of the Financial Action Task Force (FATF) San Jose principles, the Organisation for Economic Co-operation and Development (OECD) principles for artificial intelligence (AI) and the proposed European Union (EU) Artificial Intelligence Act. The authors argue that AI tools can revolutionize AML/CFT and asset recovery, but there is a need to strike a balance between optimizing AML efficiency and safeguarding fundamental rights.

This paper draws on reports, legislation, legal scholarships and other open-source data on the digital transformation of AML/CFT, particularly the deployment of AI in this context.

A new regulatory framework with robust safeguards is necessary to mitigate the risks associated with the use of new technologies in the AML context.

This study is one of the first to examine the use of AI in the AML/CFT context in light of the FATF San Jose principles, the OECD AI principles and the proposed EU AI Act.