2023 |
This grant aims to provide an in-depth overview of current practices involving digital technology from different angles and to open up discussions on future developments, threats, and opportunities.
The grant was used to develop and assess various participatory AI methods and UX/UI designs specifically tailored for children aged 6 to 14.
Urban planning has long promoted participatory approaches, yet the actual implementation across diverse age groups faces significant challenges.
The complexity of urban planning tasks has intensified with digitalization and smart city technologies, often reinforcing top-down, expert-led models that overshadow participation.
Despite policies evolving to incorporate participatory strategies, such approaches often lead to conflicts and tokenism, fostering skepticism among community members.
Current community engagement platforms focus on data collection through surveys, which are later analyzed by experts, failing to employ human dialogue and debate in the actual decision-making process - often relegated to the bell curve of big data statistical analyses.
This oversight particularly impacts children, whose perspectives are often inadequately integrated. Traditional participatory planning tools necessite new techniques and tools that can effectively engage them with creative ideation media.
This project shifts the role of children from commentators to active placemakers, ensuring their visions are integrated into urban planning decisions by utilizing collective intelligence and generative AI.
The goal was to develop a Participatory AI framework that could be integrated into the educational curriculum, allowing children to contribute meaningfully to urban design projects.
Designing a Participatory AI for the youth
We examined existing theories and practices to identify the best approaches for engaging children in digital environments.
Our team, experienced in conducting participatory AI workshops, leveraged this knowledge to formulate hypotheses on effective UX/UI design for young users.
The focus was on creating a seamless, enjoyable user experience that could facilitate both guided and unguided exploration.
Based on the feedback, we made several adjustments to the interface. For younger children, we simplified the navigation and added more visual prompts and interactive elements. For older children, we incorporated more advanced features that allowed for deeper engagement and exploration.
We developed a continuous cycle where children could select a starting image, apply their ideas, and see real-time visualizations of their transformations.
The interface was designed to provide immediate, intuitive feedback, helping children understand how their ideas were shaping the urban space. We also included features that allowed children to vote on their favorite designs, fostering a sense of collective decision-making.
With the validated interface, we deployed UrbanistAI in pilot projects, including workshops at Harviala School and other community events ran by Tampere University researhers. These real-world applications provided additional insights and opportunities for further refinement. Our commitment to continuous improvement ensures that as we gather more data and feedback, the UX/UI will evolve to better meet the needs of its users.
Participatory AI Workshop Structure
The imagination phase was tailored to different grade levels, each employing a method suited to the cognitive and social development of the participants.
Drawing Guided Approach
For the youngest participants, the workshop started with a drawing activity. Children were provided with drawing materials and encouraged to sketch their ideal outdoor spaces. This tactile approach allowed them to freely express their ideas without the constraints of technology. The specialists then translated these drawings into visual prompts for the AI, bringing the children’s hand-drawn concepts to life on the screen.
Image Guided Approach
Fourth graders were introduced to a library of images depicting various urban spaces. They navigated through these visuals, selecting the ones that aligned with their vision for an ideal recess area. This method provided a balance between guidance and freedom, allowing students to make choices within a curated framework. The selected images served as starting points for the AI to generate designs, which were then refined through group discussion and selection.
Unguided Approach
The oldest group of children engaged with the workshop with a higher degree of independence. Equipped with iPads, they used the UrbanistAI app to interact directly with the platform. These students brainstormed and articulated their ideas freely, showcasing an impressive level of digital literacy and creativity. This method fostered collaboration and communication among the participants as they worked in groups to develop their urban space designs.
After generating the initial ideas, each participant took turns vocalizing their transformative ideas for the spaces.
A researcher from Tampere University input their suggestions into UrbanistAI, enabling a dynamic exchange of ideas. This iterative process allowed for multiple rounds of interaction with the AI to refine the children’s concepts. As ideas took visual form, children indicated their preferred images, which were then highlighted within the platform.
The workshop culminated in a collective decision-making process. All the favored images were projected for the group, and the children cast their votes for the top designs by a show of hands. This phase was essential in fostering a sense of ownership and collective decision-making among the participants.
Takeaways
UrbanistAI workshops showcased the potential of Generative AI in participatory design, establishing a scalable framework for involving children in urban planning. This initiative marks a significant step towards inclusive urban development, where the imaginations of young minds shape vibrant, dynamic, and playful urban spaces.