Local governments around the world are spending millions to monitor, analyse and visualise air pollution using smart technologies; however, data and visualisations can only be effective if equally strong actions are taken to improve air quality. This thesis critically analyses the often reductionist technological approaches to, and narratives of, smart cities which are aimed at addressing air pollution and mitigating the effects of climate change, with a focus on two main areas. First, it offers evidence-based practical alternatives to these approaches and suggests how future work in this field might expand this narrow design space. Second, it examines and applies in practice a number of social psychology and behaviour change insights, to understand the most appropriate ways of helping people transition to zero- and low-pollution lifestyles through the design of new technology enablers and through collective action.

Mitigation-focused actions will not be enough to address the complexity and severity of the air pollution challenge alone. This enquiry focuses on using design research practices to develop a set of technology experiments or enablers that could shift the focus from pollution monitoring (measuring pollution that has already been produced) to pollution prevention (pre-empting pollution before it is produced). Current sensing and data visualisation projects in the fields of design for behaviour change, human-computer interaction (HCI) and persuasive technologies often either focus on 1) the behaviour while it is being performed or 2) reporting about the behaviour that has already been performed. The prevention-focused technology design experiments in this PhD set out to understand the moment or space right before a behaviour occurs. Through this enquiry, it is argued that a technology enabler can be designed to address
this moment or space and intervene to gain time for and enable a deliberate pause between people’s ‘auto-pilot’ behaviours and more effortful considerations of their day-to-day activities; their usual behaviour can be disrupted and shifted to a new behaviour. But this shift is only possible if 1) the right advice is designed and delivered at 2) the right time with 3) the right frequency, and in 4) the right place and context. Moreover, while it is difficult to identify and address all the reasons for the discrepancy between people’s values and intentions and their actual behaviours or actions, this thesis also argues that technology enablers could help in efforts of closing the ‘value-action’ gap and deliver feedback to a space where it was previously missing.

In alignment with these findings, and because of their widespread use in people’s homes, this thesis tests current home artificial intelligence (AI) assistants and applies them to deliver a set of behavioural and psychological insights in practice. The four design experiments described in this thesis offer new socially and environmentally minded adaptations to these assistants. They shed light on potentially more meaningful types of interactions with these technologies, demonstrating how they could engender a more proactive role for citizens in enabling positive social and environmental change.

In the first two experiments, a new skill is applied to an existing AI assistant technology. In the second, the author takes on the role of an AI assistant, to better understand her participants’ view on air pollution, the climate crisis and sustainability in general: what they value and prioritise in their daily lives, social practices and behaviours, and what activities they might be willing to change. In the third experiment, a new design method and custom-built, digital assistant or social companion known as Climate Pal (CP) is developed with a group of participants. This demonstrates the potential role of home assistant technologies to increase the degree of participation in pre-empting pollution in cities and help people articulate their own agency in complex environmental matters. The final experiment offers a new alternative to further increasing people’s agency by connecting them through a network of home assistant
devices to a group of like-minded people, so they could enable and take collective social and environmental action together. This new approach tests whether the social aspect of the intervention makes participants’ engagement and the changes in their behaviour more durable than if the intervention were to be focused solely on individual action. The outcomes point to the need for new technology designs that account for and support participants’ core values and desire for social connection and belongingness, for being challenged by, and learning from, others; for doing good for other people; working towards a shared goal; and becoming part of something greater than themselves.

This PhD sets out to design technologies that increase people’s agency in taking meaningful social and environmental action, individually as well as collectively. The aim of this is to overcome the perception that small changes by individuals are somewhat futile when it comes to the inaction of a whole world of other people. The four design research experiments result in a new set of technology design principles for others to use. By moving beyond passive observation of pollution and energy use through air quality sensing technologies, clean air route-finder apps and smart metres, this set of design principles aims to enhance people’s agency and establishes a new, prevention-focused technology design approach that can help reduce polluting and energyintensive behaviours before they even happen. The work has value for those designing for agency and behaviour change, as well as governments and local authorities interested in improving pollution, and for designers involved in developing emerging AI technologies and
improving human-computer interaction.