All the Nordic states (except for Iceland at the time of analysis) have published a national artificial intelligencestrategy (NAIS) document. The NAISs provide a window through which to view a consolidated point where statesset out a socio-technical imaginary ostensibly focused on the impact of AI on the national society but, in so doing,communicate present-day value-laden assumptions. These future visions see an expansion in the scale and scope ofprivate-sector-driven AI applications in healthcare provision as inevitable, positive, and justified based on a promiseof efficiency. In so doing, the NAISs institutionalise a shift in how issues of participation, deliberation, and inclusionin health are structured in the future. The article asks what kind of ‘welfare’ the NAISs present for the Nordic regionwith respect to the governance, role, and ownership of AI healthcare. In so doing, it reveals how the NAISs providea vehicle by which to enable a paradigm shift in state–market relations that is, nonetheless, hidden from politicalscrutiny through its technological futurism

Trust in AI healthcare technologies is often treated as an obtainable end-state enforceable byregulation, in which developers can claim their product to be ‘trusted’. The article shows thelimits of this approach, arguing instead for a processual understanding in which trust isunderstood to be dynamic and forever a state ‘to come’. The argument is developed byconsidering several types of trust relations amongst key stakeholders in AI healthcare, includingwhere developers often distrust users. Drawing on political theory and Coactive Design, thearticle argues that trust relations as a negotiation are integral to a well-functioning designprocess that not only supports the moral acceptability of AI healthcare technologies but also theirinnovation and efficacy.

AI’s role in healthcare has been hyped both via utopian and dystopian narratives, with the latter often used to argue that the technology is the only saviour to a labour and cost crisis. The problem with hype is that it undermines the nuance and debate needed if we are to use this still-largely-speculative technology for societal good. Where such technology is dominated by big firms based far away, how can municipal care providers ensure sufficient control to maintain quality when using AI? What procedures and processes are necessary to ensure that the use of AI in, for example, care assessment decisions doesn’t erode basic values and democratic rights within the welfare model? In considering these questions, the talk will outline the key political and ethical issues faced when adopting AI in healthcare with a particular focus on the welfare model.

Health services and medical research are subject to growing use of ADM. Whilst such technology brings many benefits, it is important to understand that it is not just a tool but involves a more fundamental shift in the infrastructure through which healthcare takes place. Where that development is driven by the private sector, it also indicates a wider paradigmatic change in how healthcare is provided. To ensure that ADM in healthcare follows an equitable path that benefits humanity, it is necessary to begin asking critical questions as to the power relations through which it is taking place but also it maintains and strengthens as the technology becomes ubiquitous. The chapter expands on the notion of the everyday as a means for contesting the current elitist and exclusionary model of ADM in healthcare by drawing upon two other related but distinct approaches to the everyday-‘Everyday International Political Economy’ in which the everyday can sometimes take power through institutional and economic means, and Davina Cooper’s focus on ‘everyday utopias’ as a space in which actors can perform alternative ways of social and political being. An enriched understanding of the everyday provides a means to reimagine the automation of healthcare as a sphere for collaborative future-making that is much more equitable than the currently skewed economic model for global health.

The term ‘artificial intelligence’ has arguably come to function in political discourse as, what Laclau called, an ‘empty signifier’. This article traces the shifting political discourse on AI within three key institutions of global governance–OHCHR, WHO, and UNESCO–and, in so doing, highlights the role of ‘crisis’ moments in justifying a series of pivotal re-articulations. Most important has been the attachment of AI to the narrative around digital automation in human healthcare. Greatly enabled by the societal context of the pandemic, all three institutions have moved from being critical of the unequal power relations in the economy of AI to, today, reframing themselves primarily as facilitators tasked with helping to ensure the application of AI technologies. The analysis identifies a shift in which human health and healthcare is framed as in a ‘crisis’ to which AI technology is presented as the remedy. The article argues the need to trace these discursive shifts as a means by which to understand, monitor, and where necessary also hold to account these changes in the governance of AI in society.

Just recently Amazon announced that it will no longer use ‘no-checkout’ payment – a system where AI would supposedly monitor and tally up whatever you were removing from the shelves – because it wasn’t working as planned. What had been billed as a technological AI-fuelled revolution in retail was, supposedly, dependent on cheap human labour based in India watching security camera footage.[1] Such stories are increasingly common, functioning as urban myths that remind us of an alternate reality behind the utopian allure of techno-hype. But going beyond the question of whether AI is driven by micro-processors or underpaid agency workers, how much of what our politicians and business leaders call ‘AI’ is really AI?

Healthcare systems are the embodiment of big data – as evident in the logistics of resource management, estate maintenance, diagnoses, patient monitoring, research, etc. – such that human health is often heralded as one of the fields most likely to benefit from AI. Yet, the prevalence of hype – both positive and negative – risks undermining that potential by distracting healthcare policy makers, practitioners, and researchers from many of the non-AI factors that will determine its impact. Here we categorise AI hype in healthcare into three types that include both utopian and dystopian narratives and plot a series of more productive paths ahead by which to realise the potential of AI to improve human healthcare.