Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To (...) reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being. (shrink)

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within (...) a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research—among researchers and with data subjects—is grounded in trust, which should be more explicitly recognised in the governance of health data research. (shrink)

In the 1960s, influential thinkers defined design as a rational problem-solving approach to deal with the challenges of sustainable human development. In 2009, a design consultant and a business academic selected some of these ideas and successfully branded them with the term “design thinking.” As a result, design thinking has developed into a stream of innovation management research discussing how to innovate faster and better in competitive markets. This article aims to foster a reconsideration of the purposes of design thinking (...) moving forward, in view of the sustainable development challenges intertwined with accelerating innovation in a perpetual economic growth paradigm. To this end, we use a problematization method to challenge innovation management research on design thinking. As part of this method, we first systematically collect and critically analyze the articles in this research stream. We uncover a prominent focus on economic impact, while social and environmental impacts remain largely neglected. To overcome this critical limitation, we integrate design thinking with responsible innovation theorizing. We develop a framework for responsible design thinking, explaining how to apply this approach beyond a private interest and competitive advantage logic, to address sustainable development challenges, such as climate change, resource depletion, poverty, and injustice. The framework contributes to strengthening the practical relevance of design thinking and its theoretical foundations. To catalyze this effort, we propose an agenda for future research. (shrink)

An online world exists in which businesses have become burdened with managerial and legal duties regarding the seeking of informed consent and the protection of privacy and personal data, while growing public cynicism regarding personal data collection threatens the healthy development of marketing and e-commerce. This research seeks to address such cynicism by assisting organisations to devise ethical consent management processes that consider an individual’s attitudes, their subjective norms and their perceived sense of control during the elicitation of consent. It (...) does so by developing an original conceptual model for online informed consent, argued through logical reasoning, and supported by an illustrative example, which brings together the autonomous authorisation (AA) model of informed consent and the theory of planned behaviour (TPB). Accordingly, it constructs a model for online informed consent, rooted in the ethic of autonomy, which employs behavioural theory to facilitate a mode of consent elicitation that prioritises users’ interests and supports ethical information management and marketing practices. The model also introduces a novel concept, the informed attitude, which must be present for informed consent to be valid. It also reveals that, under certain tolerated conditions, it is possible for informed consent to be provided unwillingly and to remain valid: this has significant ethical, information management and marketing implications. (shrink)

In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence. First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities can support AI. At the (...) heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations. (shrink)

This paper introduces the concept of business-related conspiracy theories. Drawing on Aristotelian virtue ethics and undertaking a narratological and ethical analysis of 28 BrCTs found online, I emphasize that BrCTs are narratives with structures rooted in other latent macro- and meta-narratives, including centuries-old myths. In particular, I reconstruct the fictional world of BrCTs – one in which CSR and social contracts have failed – before identifying eight different types of actors as which people can morally situate themselves in their relationships (...) with business. Finally, I elaborate on the actors’ performances and their use of external and legitimate forces to end the story. The paper concludes with a discussion of potential future research to help combat BrCTs, as well as a call for the critical study of political CSR. (shrink)