Conference Agenda

Citizen participation has undergone profound transformations over the past fifty years, evolving from traditional consultation methods to more dynamic, digital, and co-productive forms of engagement. This paper explores the historical trajectory of participatory governance, from early participatory planning and international development initiatives to the rise of New Public Management (NPM), New Public Service (NPS), and digital democracy. It examines how participatory frameworks enhance transparency, public trust, and democratic legitimacy by analyzing successful international models such as Estonia’s digital governance and Brazil’s participatory budgeting. The role of AI-driven engagement platforms, blockchain technology, and digital consultation tools is critically assessed, with attention to both their transformative potential and the risks they pose, such as algorithmic bias, digital exclusion, and ethical concerns.

Beyond structured participatory processes, the paper explores grassroots mobilization, informal citizen activism, and the power dynamics within institutions that shape the effectiveness of democratic engagement. It also evaluates the economic and social impacts of citizen participation, particularly in relation to public trust, redistributive justice, and social welfare policies. A key section of the study examines citizen participation during crises, with a focus on the COVID-19 pandemic as a case study of participatory governance under emergency conditions. While the pandemic underscored the importance of community-led public health initiatives, digital civic engagement, and participatory crisis management, it also revealed significant challenges such as restricted civic spaces, digital inequalities, and public distrust fueled by misinformation.

The paper concludes by offering policy recommendations for enhancing participatory democracy through the institutionalization of participatory governance models at multiple levels, the expansion of AI-driven engagement platforms with ethical safeguards, and the strengthening of grassroots activism to ensure the inclusion of marginalized groups. It also discusses the need to embed citizen participation into crisis management and resilience strategies to make governance more inclusive and adaptive in an era of poly-crises and technological disruption.

The increasing deployment of artificial intelligence (AI) in public services raises critical questions about its impact on citizens’ willingness to coproduce. While existing research has explored citizen preferences for human versus AI service agents, significant gaps remain in understanding how the multidimensional attributes of both human and AI agents shape coproduction willingness. Prior studies have predominantly focused on single identity traits (e.g., gender or age) or binary human-AI comparisons, overlooking the joint effects of symbolic, interactive, ethical, and responsiveness attributes of service agents. Addressing these gaps, this study investigates: (1) whether citizens prefer human agents, AI agents, or hybrid human-AI collaboration for coproducing public services; (2) which attributes of human agents (e.g., representative symbolic features, responsiveness) drive citizens’ coproduction willingness; and (3) which AI design features (e.g., anthropomorphism, multimodal interaction) enhance such willingness.

Building on symbolic representation theory, multimodality theory, technology ethics governance, and coproduction literature, we designed and conducted a conjoint experiment (n = 1,600) in two environmental complaint scenarios in China (noise pollution and solid waste pollution reporting) across six experimental rounds. Four attribute dimensions were systematically manipulated: symbolic representation (gender, age, accent), modality interaction (anthropomorphism, text/voice interaction), technological ethics (data privacy, transparency, accountability), and responsiveness (proactiveness, personalization). We further examined the moderating roles of political efficacy (both external and internal). The experimental design compared citizen preferences across three interaction modes: human-only, AI-only, and human-AI hybrid (e.g., human-supervised AI) in the context of coproducing public services.

This study advances AI-enabled public services through three key contributions. First, by unpacking how citizens weigh multidimensional signals in human-AI interactions—spanning symbolic representation, multimodality, ethics, and responsiveness—it bridges gaps in prior research that isolated single identity traits or framed human-AI collaboration as binary trade-offs. This approach deepens our understanding of the effects of joint attributes of service agents in motivating coproduction willingness. Second, the findings provide actionable guidance for designing AI systems that balance algorithmic efficiency with citizen-centric values. By identifying AI design features that enhance coproduction willingness, the study equips public service agencies to mitigate algorithmic aversion while addressing ethical risks such as data privacy. Third, it empirically evaluates the deployment of AI in public services, informing policymakers on whether and how AI can effectively promote coproduction willingness. By integrating insights from AI governance, representative bureaucracy theory, and behavioral public administration, the research provides a roadmap for ethically embedding AI into public services while fostering citizen engagement.

Currently, 62% of EU soils are unhealthy. The quality and productivity of the soil is deteriorating by intense agricultural use. Healthy soil is crucial to addressing climate change, reducing heat and boosting biodiversity. To secure the benefits of healthy soil, it is necessary to move toward soil-inclusive practices. However, our disconnection from soil keeps growing. Still too often, soil is approached as a collective good that stands at the disposal of any human activity (EC, 2023; ESDAC, 2024). Despite our growing disconnection from soil, community-led activities like urban gardening and farming attempt to keep that link alive. Can studying urban food forests help develop soil-inclusive practices, teach communities soil's role in healthy food access and enhance soil literacy (EC, 2024; ESDAC 2024)? Urban food forests are a relatively new phenomenon in the Netherlands, but there is increased interest (De Groot & Veen 2017). Humanity faces socio-environmental challenges, such as food security, climate change adaptation and biodiversity loss. These challenges have sparked research into sustainable and healthy food sources within cities, like urban food forests (Oncini et al. 2024). Food forests offer a model for collaboratively rethinking sustainable urban design, by addressing issues like biodiversity loss, food insecurity and climate change (Riolo 2019). Furthermore, urban food forests can help promote public participation in sustainable and healthy food production (Coffey et al., 2021; Abdulai, 2024) which is vital in urban areas like the Rotterdam metropolitan area, where many live in poverty and/or social isolation. They also serve as community engagement hubs for social interaction and shared responsibility for the (natural) environment (Riolo 2019). How do urban food forests strengthen the connection between residents and their (natural) environment? By co-creating audiovisual stories with local communities, through visual ethnography and urban design, this research proposal aims to explore these questions. This is grounded in two methods: co-creative visual ethnography and spatial planning and design. Visual ethnography is a qualitative research method, which assumes the unique possibility that audiovisuality can offer to develop and communicate academic insights (Pink 2021; Hylland-Eriksen, T. (2015). Visual ethnography captures social impact and interactions with food forests and soil, revealing insights often missed by traditional planning. Involving communities in creating images and narratives deepens engagement and lets them shape their own knowledge representation. Spatial planning uses typologies to categorize sites, connecting local observations to broader systems for transferable findings. These help planners create adaptable policies and strategies (Hooimeijer et al., 2017). However, spatial planners often exclude soil using 2D techniques. Can visual ethnography, combining scientific and local knowledge, expand this view, while also improving soil literacy for residents? This research proposal involves two learning objectives: (1) Explore how people engage with each other and the land in three food forests in the Rotterdam area and how to strengthen this engagement through visual ethnography and (2) analyze the social, environmental, and urban impact of these forests and help spatial planners move beyond 2D soil representations. Researchers will identify spatial typologies of food forests, examining factors like location, size, function, and user groups (proposal phase). The visual output will be edited into a short documentary highlighting the societal, environmental, and urban impacts of food forests, while also sharing knowledge back with the community.