Purpose Digital transformation leverages digital technologies to change current processes and introduce new processes in any organisation’s business model, customer/user experience and operational processes. Artificial intelligence plays a significant role in achieving DT. As DT is touching each sphere of humanity, AI led DT is raising many fundamental questions. These questions raise concerns for the systems deployed, how they should behave, what risks they carry, the monitoring and evaluation control we have in hand, etc. These issues call for the need (...) to integrate ethics in AI led DT. The purpose of this study is to develop an “AI led ethical digital transformation framework”. Design/methodology/approach Based on the literature survey, various existing business ethics decision-making models were synthesised. The authors mapped essential characteristics such as intensity and the individual, organisational and opportunity factors of ethics models with the proposed AI led ethical DT. The DT framework is evaluated using a thematic analysis of 23 expert interviews with relevant AI ethics personas from industry and society. The qualitative data of the interviews and opinion data has been analysed using MAXQDA software. Findings The authors have explored how AI can drive the ethical DT framework and have identified the core constituents of developing an AI led ethical DT framework. Backed by established ethical theories, the paper presents how DT pillars are related and sequenced to ethical factors. This research provides the potential to examine theoretically sequenced ethical factors with practical DT pillars. Originality/value The study establishes deduced and induced ethical value codes based on thematic analysis to develop guidelines for the pursuit of ethical DT. The authors identify four unique induced themes, namely, corporate social responsibility, perceived value, standard benchmarking and learning willingness. The comprehensive findings of this research, supported by a robust theoretical background, have substantial implications for academic research and corporate applicability. The proposed AI led ethical DT framework is unique and can be used for integrated social, technological and economic ethical research. (shrink)

Our social relations are changing, we are now not just talking to each other, but we are now also talking to artificial intelligence (AI) assistants. We claim AI assistants present a new form of digital connectivity risk and a key aspect of this risk phenomenon is related to user risk awareness (or lack of) regarding AI assistant functionality. AI assistants present a significant societal risk phenomenon amplified by the global scale of the products and the increasing use in healthcare, education, (...) business, and service industry. However, there appears to be little research concerning the need to not only understand the changing risks of AI assistant technologies but also how to frame and communicate the risks to users. How can users assess the risks without fully understanding the complexity of the technology? This is a challenging and unwelcome scenario. AI assistant technologies consist of a complex ecosystem and demand explicit and precise communication in terms of communicating and contextualising the new digital risk phenomenon. The paper then argues for the need to examine how to best to explain and support both domestic and commercial user risk awareness regarding AI assistants. To this end, we propose the method of creating a risk narrative which is focused on temporal points of changing societal connectivity and contextualised in terms of risk. We claim the connectivity risk narrative provides an effective medium in capturing, communicating, and contextualising the risks of AI assistants in a medium that can support explainability as a risk mitigation mechanism. (shrink)

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use (...) AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers. (shrink)

PurposeThis paper aims to investigate behavioural changes related to self-censorship (SC) in social networking sites (SNSs) as new methods of online surveillance are introduced. In particular, it examines the relationships between SC and four related factors: privacy concerns (PC), privacy awareness (PA), perceived vulnerability (PV) and information management (IM).Design/methodology/approachA national wide survey was conducted in the UK (N= 519). The data were analysed to present both descriptive and inferential statistical findings.FindingsThe level of online SC increases as the level of privacy (...) concern increases. The level of privacy concern increases as the levels of PA and PV increase and the level of effective IM decreases.Originality/valueThis study extends the literature on online SC, showing that PCs increase the level of SC in SNSs. It provides support for three antecedent factors to PC which impact upon levels of SC when communicating in SNSs. (shrink)

PurposeThis paper aims to investigate algorithmic governmentality – as proposed by Antoinette Rouvroy – specifically in relation to law. It seeks to show how algorithmic profiling can be particularly attractive for those in legal practice, given restraints on time and resources. It deviates from Rouvroy in two ways. First, it argues that algorithmic governmentality does not contrast with neoliberal modes of government in that it allows indirect rule through economic calculations. Second, it argues that critique of such systems is possible, (...) especially if the creative nature of law can be harnessed effectively.Design/methodology/approachThis is a conceptual paper, with a theory-based approach, that is intended to explore relevant issues related to algorithmic governmentality as a basis for future empirical research. It builds on governmentality and socio-legal studies, as well as research on algorithmic practices and some documentary analysis of reports and public-facing marketing of relevant technologies.FindingsThis paper provides insights on how algorithmic knowledge is collected, constructed and applied in different situations. It provides examples of how algorithms are currently used and how trends are developing. It demonstrates how such uses can be informed by socio-political and economic rationalities.Research limitations/implicationsFurther empirical research is required to test the theoretical findings.Originality/valueThis paper takes up Rouvroy’s question of whether we are at the end of critique and seeks to identify where such critique can be made possible. It also highlights the importance of acknowledging the role of political rationalities in informing the activity of algorithmic assemblages. (shrink)