Kin-Directed Smart Cities

Human CENTERED CITIES

Kin-Directed Smart Cities

Capturing Phenomenological Experiences with Generative Agents

Call To Action

Human-Centered City

Not a Ghost City of Sensors

Kin-Directed City

Not a Ghost City of CCTVs

Our Approach

Three Steps Process:

Urban AI Anthropology

AI & Scenario-Driven Technology Roadmapping

People Walking on Pedestrian Lane during Daytime

Urban Sensemaking

Urban AI Anthropology

This step leverages design anthropology principles to provide cities with deep insights into the socio-cultural dynamics and phenomenological experiences of urban populations. We utilize tools including Wargaming miniatures and the METIS platform, integrated with generative agent-based modeling and ethnopsychology analytics, alongside physical devices to capture thick data and human experiences as they occur. This stage focuses on understanding current usage, perceptions, and the socio-cultural impact of existing technologies, rather than projecting future technological evolutions.

Implementation

Scenario Development:
Develop diverse future scenarios based on current insights that account for potential developments in urban culture, technology, and environmental conditions. These scenarios are used to stimulate discussion and thought about different futures that might emerge from present trends, latent needs, and possible advancements. In a research by Harvard, a scenario was developed for drones not just as surveillance tools but as integral parts of urban life, enhancing safety and interaction in public spaces.

Objective

To deeply understand current interactions with technologies and how these fit into broader urban cultural and social dynamics. This involves capturing the subjective, phenomenological experiences of users to grasp the cultural, social, and technological factors influencing technology adoption and usage patterns.

Outcome

Produce a set of grounded visions that provide a rich, qualitative understanding of potential urban futures. These visions, informed by a detailed and empathetic understanding of human-centered design principles, ensure that future urban scenarios are both innovative and closely aligned with human needs and cultural dynamics.

AI & Scenario-Driven Technology Roadmapping

This forward-looking step focuses on planning the diffusion, integration and evolution of technologies within the urban context. It uses the grounded visions developed in Step 1 to explore and project future technological trajectories, considering how emerging technologies might transform city landscapes under various conditions.

Outcomes

AI-based Scenario Development for Future Technologies:
Create dynamic, diverse scenarios that show how different technologies might evolve and interact within the urban fabric, impacting everything from daily city operations to long-term planning. These scenarios, informed by the socio-cultural insights from Step 1, project how technologies could meet future needs and challenges.
Technology Roadmapping:
Construct detailed, nonlinear roadmaps to guide the development, adoption, and integration of technologies according to each scenario. This includes outlining key technological milestones, necessary infrastructure adjustments, required partnerships, and potential policy changes, aligning these elements with strategic objectives to manage technology deployment effectively over time

Objective

To identify emerging technologies likely to offer significant economic and social benefits, ascertain which technologies will have longevity, and determine which might become obsolete or fail to integrate effectively into daily urban life.

Urban Sensemaking

Urban sensemaking emphasizes the creation of an environment where various parties can experiment, develop, and test ideas. It fosters social innovation and active participation through our living labs offering.

Example

Consider the evolution of e-scooters within the urban context by creating community hubs where residents can access e-scooters, bicycles, and other transportation options. These hubs serve as both a practical resource and a platform for community engagement and feedback on urban mobility solutions.

Objective

Facilitate a participatory environment where community members and stakeholders can collaboratively develop and refine urban solutions, such as new transportation models and community hubs.

Outcome

Establish dynamic urban labs where innovative ideas are continuously tested and refined by the community, leading to solutions that are practically viable and culturally resonant. This process ensures that urban innovations are responsive to the actual needs and conditions of the city, enhancing the overall quality of urban life.

Integrated Use Case Example: Smart Waste Management System

Overview: The city is facing challenges with waste management efficiency, impacting environmental sustainability and public health.

Objective: Deeply understand how different urban communities handle waste and their attitudes towards smart waste management technologies.

Implementation:

– Conduct ethnographic research and use physical devices to gather data on current waste management practices across diverse neighborhoods.
– Utilize Wargaming miniatures in workshops to represent different waste management scenarios, allowing participants to physically interact with and visualize the impact of various strategies.
– Implement generative agent-based modeling to simulate community behaviors and interactions with existing waste management systems. This advanced modeling approach generates dynamic scenarios that mirror real-life community responses under different waste management strategies.
– Analyze both qualitative data from ethnographic research and quantitative data from Generative agents to gain a comprehensive understanding of the current waste management challenges and community attitudes.

Outcome: Detailed insights into how different communities interact with the waste management system, backed by data-driven simulations that forecast the effectiveness of potential changes. This foundational knowledge is critical for designing a smart waste management system that is culturally and practically aligned with community needs.

Overview: Using insights from the previous step, plan the integration of a smart waste management system.

Objective: Develop a phased plan for implementing smart waste technologies that align with urban needs and capabilities.

Implementation:

– Use the METIS platform to generate scenarios showing how smart waste systems could integrate into the existing infrastructure and its impact on waste management efficiency.

– Develop a detailed technology roadmap that includes pilot testing, community feedback sessions, full-scale deployment, and necessary policy adjustments.

– Employ agent-based models to predict the outcomes of different implementation strategies and to adjust the approach based on dynamic urban conditions.

Outcome: A strategic plan that outlines clear steps, timelines, and expected challenges for the deployment of a smart waste management system.

Overview: After initial testing and data analysis, refine the smart waste management solution to ensure it meets the community’s needs and expectations.

Objective: Co-create the final waste management solution with active community involvement to ensure it is widely accepted and effective.

Implementation:

– Organize additional wargaming workshops using miniatures to simulate the operation of the new waste management system, incorporating real-time feedback from residents.

– Implement living labs in select neighborhoods to test the smart waste systems, using action research methods (plan, act, observe, reflect) to iteratively improve the system.

– Adjust the system based on ongoing community feedback and observed effectiveness in the living labs.

Outcome: A community-endorsed smart waste management system that is optimized for local conditions and preferences, fostering sustainable urban practices and improving overall environmental quality.