Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences最新文献

We explore an augmented democracy system built on off-the-shelf large language models (LLMs) fine-tuned to augment data on citizens' preferences elicited over policies extracted from the government programmes of the two main candidates of Brazil's 2022 presidential election. We use a train-test cross-validation set-up to estimate the accuracy with which the LLMs predict both: a subject's individual political choices and the aggregate preferences of the full sample of participants. At the individual level, we find that LLMs predict out of sample preferences more accurately than a 'bundle rule', which would assume that citizens always vote for the proposals of the candidate aligned with their self-reported political orientation. At the population level, we show that a probabilistic sample augmented by an LLM provides a more accurate estimate of the aggregate preferences of a population than the non-augmented probabilistic sample alone. Together, these results indicate that policy preference data augmented using LLMs can capture nuances that transcend party lines and represents a promising avenue of research for data augmentation. This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Recently the transportation sector has witnessed several new technologically driven disruptions that have amplified the complexity of city planning and policymaking. Traditional well-established processes of decision-making in urban planning and transportation are proving insufficient to deal with this degree of complexity and uncertainty. This paper proposes an alternative approach, combining qualitative and normative urban design, with quantitative and predictive transport modelling. This requires urban designers and transport modellers to co-create goal-driven and agile transport models that act as a heuristic tool to guide planning decisions in early design stages. Heuristic modelling is informed by design optioning and vice versa in an iterative loop. A case study is presented to demonstrate how this approach is operationalized to study the impacts of automated vehicles on urban planning. Design workshops are used as a method to elicit responses from stakeholders, which are used to co-create the simulation models. This collaborative process grounds the research in real-world practice and enhances the communication of design proposals and research findings across disciplines. By integrating design thinking methods with agent-based transport simulations, this approach provides a better understanding of emergent effects in complex urban systems and improves stakeholder engagement in the planning process.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Currently, there are increasing attempts to better involve citizens in political decision processes. A successful approach in that regard has been participatory budgeting (PB), which allows citizens to propose projects and then decide how to distribute a given budget over them. Meanwhile, the literature on collective intelligence (CI) has also shown the ability of groups to solve complex problems. Thus, by combining CI and PB, it should be possible for citizens to identify problems and create their own solutions. In this article, we study this possibility by using agent-based models. Specifically, we first show that a system combining CI and PB produces solutions that strongly penalize minorities if the solution quality depends on group size. Then, we introduce an approach that can overcome this issue. Indeed, by using a common knowledge base for the storage of partial solutions, the quality of solutions of minorities can benefit from the work of the majority, thereby promoting fairness. Interestingly, this approach also benefits majorities, as the quality of their solutions is further improved by the work of the minorities, thus reaching better solutions for everyone. This stresses the potential and importance of an open innovation approach, which is committed to information sharing.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Efforts to realize on-demand delivery drone networks present a stark example of how the technology industry seeks to dominate new markets, regardless of societal consequences. Analyzing the most advanced of these efforts-Google Wing's operations in Australia since 2017-we identify the instrumental role of narratives of technological inevitability (of tech expansion, and societal adaptation) in catalyzing new sky-based commerce. Yet the interest of this case study lies in a twist. Google Wing's rollout in Australia's capital, Canberra, initially proceeded as a textbook example of tech expansion. However, citizen engagement and public governance dramatically intervened and, we argue, disrupted the logic of technological inevitability. This article is the first to analyze these dynamics, many of which originated with Bonython Against Drones (BAD), a community action group forged from those who first lived under Google's food delivery drones. The article exposes the flawed logic of technological inevitability as the enabling force of tech expansion; characterizes the governance failures that help install corporate visions for public goods; animates the potentialities of communities living with new technologies; and identifies the sky itself, as both a public commons and a vital, living habitat, as a key future locus for participatory governance. This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

In this article, we identify challenges in the complex interaction between artificial intelligence (AI) systems and society. We argue that AI systems need to be studied in their socio-political context to be able to better appreciate a diverse set of potential outcomes that emerge from long-term feedback between technological development, inequalities and collective decision-making processes. This means that assessing the risks from the deployment of any specific technology presents unique challenges. We propose that risk assessments concerning AI systems should incorporate a complex systems perspective, with adequate models that can represent short- and long-term effects and feedback, along with an emphasis on increasing public engagement and participation in the process.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

This paper explores the perspectives of different urban actors regarding public participation in the context of the increasing incorporation of digital technologies and urban platforms. The study is based on three workshops with local governance actors, six semi-structured interviews with academics in the fields of public participation and digital technologies and a citizen survey with 260 respondents. The results provide multi-perspective insights into the challenges of participatory processes and are synthesized into three contributions: (i) guidelines for effective public participation, including factors that encourage or discourage citizen engagement; (ii) guidelines for designing participatory platforms, highlighting specific features that promote digital engagement (i.e. social media, gamification and user-friendly interfaces), and (iii) a typology of digital participation platforms to connect the diverse needs of actor groups with the various possibilities provided by new technologies. The guidelines provide concrete recommendations to support both urban practitioners and interface designers in designing participatory strategies and platforms, respectively. Recognizing that there is no-one-size-fits-all platform, the typology provides a framework for the assessment and further development of digital platforms for public participation.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Evaluating sidewalk accessibility is conventionally a manual and time-consuming task that requires specialized personnel. While recent developments in Visual AI have paved the way for automating data analysis, the lack of sidewalk accessibility datasets remains a significant challenge. This study presents the design and validation of Sidewalk AI Scanner, a web app that enables quick, crowdsourced and low-cost sidewalk mapping. The app enables a participatory approach to data collection through imagery captured using smartphone cameras. Subsequently, dedicated algorithms automatically identify sidewalk features such as width, obstacles or pavement conditions. Though not a replacement for high-resolution sensing methods, this method leverages data crowdsourcing as a strategy to produce a highly scalable, city-level dataset of sidewalk accessibility, offering a novel perspective on the city's inclusivity; fostering community empowerment and participatory planning.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

This article explores the role of hackathons for good in building a community of software and hardware developers focused on addressing global sustainable development goal (SDG) challenges. We theorize this movement as computational diplomacy: a decentralized, participatory process for digital governance that leverages collective intelligence to tackle major global issues. Analysing Devpost and GitHub data reveals that 30% of hackathons since 2010 have addressed SDG topics, employing diverse technologies to create innovative solutions. Hackathons serve as crucial kairos moments, sparking innovation bursts that drive both immediate project outcomes and long-term production. We propose that these events harness the neurobiological basis of human cooperation and empathy, fostering a collective sense of purpose and reducing interpersonal prejudice. This bottom-up approach to digital governance integrates software development, human collective intelligence and collective action, creating a dynamic model for transformative change. By leveraging kairos moments, computational diplomacy promotes a more inclusive and effective model for digital multilateral governance of the future. This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

The world is undergoing a rapid process of urbanization. Currently, it is estimated that over 55% of the global population resides in urban areas, a figure projected to reach nearly 70% by 2050. This trend is accompanied by a spatial reorganization of human activities on a global scale, bringing about significant changes in mobility patterns and urban traffic management capabilities. Consequently, it is imperative to evaluate, on a broad scale, how city size influences traffic capacity. This study aims to analyse on-road traffic patterns using a diverse dataset comprising cities of varying population sizes, geographical extents and global locations. Specifically, we conduct an analysis encompassing 25 cities primarily situated in several European countries (France, Italy, Germany, Spain, Switzerland, and the United Kingdom), as well as in North America (Canada) and East Asia (Japan and Taiwan). Our findings shed light on how physical aspects related to urban form influence mobility patterns, offering insights for the implementation of more effective and sustainable traffic management policies.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

In the domain of participatory research and co-creation, understanding the dynamic interplay between group cohesion and diversity is pivotal for fostering innovation. While diversity fuels the generation of novel ideas, cohesion ensures these ideas are effectively synthesized and implemented. This study aims to explore the nuanced role that facilitators play in navigating the balance between cohesion and diversity, particularly in groups characterized by pronounced faultlines. Employing agent-based modeling, the study examines how facilitators affect the cohesion-diversity nexus. The findings reveal a complex facilitator's paradox. While facilitative actions can successfully enhance group cohesion by mitigating the negative effect of faultlines, such efforts often inadvertently reduce the within-group diversity that is crucial for sparking innovative outcomes. These findings challenge the conventional view of faultlines as merely divisive and underscore the intricate role of facilitators in modulating group dynamics. This research discusses a novel framework for dynamic facilitation strategies, emphasizing the need for facilitators to skillfully balance cohesion and diversity. This framework not only enriches the theoretical understanding of group facilitation but also offers practical insights for optimizing collaborative innovation in diverse settings. This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.