Prefer the only quantitative study on the effects of AI-integrated unionization.

The findings above reinforce the importance of situating contributions AI can bring to union growth and capacity in terms of the specific and changing institutional and identity contexts unions face, rather than positioning them in relation to abstract notions of ‘bureaucracy’ per se (Martínez Lucio, ). In this case study, the app offered the potential to transform the capacities of the alt-labour network in a dramatic way, promising the possibility of an autonomous, self-contained organising space for workers that was not reliant on the good graces of a major technology company. The transformational promise of the app was very different for the traditional union in Australia (despite the fact that both entities shared identities as ‘organising’, rather than ‘servicing’ organisations) because its affordances had to be reconciled with, and configured in relation to, existing capabilities and structures of a union that was over one hundred years old. This institutional context meant that the app was, from a relatively early stage, necessarily viewed as a tool that had to be understood as one that would only ever augmenting and enhancing existing systems, rather than replace them (Rego et al., : 326). The case study confirms, too, the tenacity of pre-existing ‘communities of practice’ (Martinez Lucio et al., ) in shaping how digital initiatives develop. Significantly, both the digital and non-digital ‘home’ organising environments in the traditional union (represented by home care workers and casino workers) proved highly durable in the face of early efforts to shift the locus of organising, wholesale, onto the app. Shorn of the possibility of the app becoming an autonomous self-contained organising space, UWU had to wrestle with how it might be best integrated into its existing capabilities, which included both legal ‘servicing’ and ‘organising’ dimensions, dilemmas that did not arise in the alt-union context where no pre-existing ‘servicing’ facility existed.

For the chatbot to advance the unions’ purpose and identity as an ‘organising’, rather than ‘servicing’ union (Hodder and Edwards, : 847), a series of conscious steps had to be taken to re-orient it from the epistemic footing set for it by IBM, as a customer service tool for streamlining human interaction, to one that laid the ground for increased substantive human interaction in the future. Remaking the chatbot as organising tool required a reconceptualisation of multiple aspects of its programming, from the way it was described and promoted, to the way it interacted with members during ‘chats’ and contextualised data, to the way that the ‘backend’ labour of data-provision was allocated and to the way that ‘success’ was calibrated. In place of metrics which placed value on the chatbot’s ability to ‘problem solve’, the app was instead evaluated for its value as an tool for initial engagement, issue detection and workplace mapping, all of which formed foundations for future, human-led, organising conversations. This re-orientation was undertaken consciously and carefully through a process of value-led reflection, observation and continual dialogue with members. It did not arise mechanically as a consequence of any blunt ‘disruption’ of existing union systems by digital technology or unmanaged ‘clash’ between logics of network and hierarchy. The process of designing and reframing the app was a resource-intensive, rather than ‘labour saving’ one (Rego et al., ). Once reconfigured as an organising tool, however, the chatbot contributed to strengthening union power and capacity in several dimensions of the Lévesque and Murray () framework outlined below.

The case study demonstrates the potential of chatbots to both strengthen and deplete union infrastructural resources, depending on how they are configured. Lévesque and Murray define infrastructural resources as the ‘material resources that permit [a union] to pursue its mission’ and give its members ‘access to expertise [and] knowledge about industry and community environments’ (Lévesque and Murray, : 340). Like other member-facing digital tools, the chatbot strengthened the union’s infrastructural capacity for ‘remote participation’ by otherwise marginal members by enabling transcendence of temporal and spatial limits (Greene and Kirton, ) and by introducing mechanisms for interactive member engagement (Hodder and Houghton, ). The chatbot also boosted organisers’ capacity to map workplaces by gathering data about the identities, workplaces and issues of concern to members and potential members, thus rendering existing processes more efficient and accurate. It also enabled organisers to pick up on sensitive issues, such as potential sexual harassment or bullying, that workers may have been reluctant to broker in an in-person context. The chatbot strengthened the unions’ infrastructural resources in indirect ways, too, as delegates, activists and union staff expanded their skill sets and capacities to organise and campaign in digital environments.

The chatbot also revealed the potential for web 3.0 technologies to deplete existing union infrastructures in circumstances where they are introduced without adequate support, time and resources for organisers to devote to chatbot-mediated enquiries. Similarly, the presence of technical glitches and bugs had the potential to cause frustration to members and organisers alike. In these circumstances, the chatbot showed the potential to be a barrier, as well as a facilitator, of responsive communication between members and union officials, and thus weaken existing infrastructure.

The case study similarly reveals the potential of chatbots to enhance or erode internal solidarity within the union, depending on how they are designed. Once reconfigured as an organising tool, the chatbot contributed to the union’s capacity to build internal solidarity and engender a sense of collective cohesion and shared status among its members (Lévesque and Murray, ). Such contributions were the consequence of active decision-making on the part of the union to design the tool to highlight the specific occupational identity and expertise of workers in every element of the chatbot’s functioning and reject the ‘default’ conceptions of the technology as mechanisms for neutrally conveying apolitical ‘facts’. Initially, when programmed to provide literal legal answers to questions, the chatbot acted to ‘informationalise’ industrial knowledge (Hardt and Negri, ), detaching the content of information from the identity of the human beings who were its source. Subsequently, the tool was redesigned to instead situate industrial information within a political context and lay the ground for human relationships of solidarity between fellow workers. The use of industry-specific identities, languages and norms (rather than generic worker ones) and the close involvement of delegates in programming the chatbot was crucial in enabling this strengthening of internal solidarity to occur. Important, too, was the decision to highlight the artificiality of the chatbot as a technological construction. In this regard, the solidarity affordances of chatbots might be contrasted with MSCNs which, as self-evident ‘networks’, inherently countenance the possibility of ‘distributed discourse’ and solidaristic communication between specifically identified workers (Greene et al., ). The democratic and solidaristic affordances of chatbots, by contrast, hinge more directly on their design, programming and the extent to which they are embedded within organisational processes that are structured around an organising ethos.