UROP Project
Designing AI Agents to Support Resident Interpretation and Deliberation
AI agents, Land User Planning, Urban Planning, Human-Computer Interaction, Civic Engagement, Qualitative Research
Research Mentor: Ms. Jiwoo Seo,
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: js25p@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Qunfang Wu
Research Assistant Supervisor Email: qunfang.wu@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: js25p@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Qunfang Wu
Research Assistant Supervisor Email: qunfang.wu@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Urban Planning (preferred)
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Number of Research Assistants: 1
Relevant Majors: Urban Planning (preferred)
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Project Description
Public participation in land use planning is crucial, yet many residents face challenges engaging meaningfully due to the complexity of planning documents and technical jargon. While governments increasingly use AI chatbots to share information, these tools often provide generalized responses and struggle with the personalized, context-aware inquiry needed for meaningful civic engagement.This project investigates how AI agents can be co-designed to bridge this gap and better support public participation, using the Tallahassee-Leon County 2030 Comprehensive Plan. We explore how AI tools can assist residents in interpreting complex land-use policies, evaluating “what-if” scenarios, and deliberating on urban development trade-offs. By conducting interviews and co-design sessions with local residents and stakeholders, this research aims to understand the socio-technical factors that influence AI trustworthiness and ultimately design human-centered AI systems that foster inclusive and reflective civic participation.
Research Tasks: The undergraduate research assistant will primarily be involved in the qualitative data collection and analysis phases of the project. Specific tasks include:
1) Conducting Interviews: Assisting or leading semi-structured interviews with local residents and stakeholders to understand their perspectives on urban planning and AI tools.
2) Participant Recruitment: Helping with outreach efforts, such as disseminating flyers at community centers, and relevant online groups.
3) Qualitative Data Analysis: Transcribing audio recordings, reviewing interview data to identify recurring themes, and extracting key insights.
4) Literature Review (Optional): Assisting with gathering and organizing relevant literature on Human-Computer Interaction (HCI) and participatory urban planning.
Skills that research assistant(s) may need: - Required: Excellent English communication skills (both verbal and written) for conducting interviews and interacting with diverse community members. Ability to extract key insights from the interviews.
- Recommended: A basic understanding of or strong interest in land use/urban planning (familiarity with the Tallahassee-Leon County Comprehensive plan is a major plus) or civic participation. Interest in HCI and qualitative research methods.
Mentoring Philosophy
My mentoring philosophy centers on developing independent analytical thinkers through guided self-motivation and mutual respect. I believe that undergraduate researchers are not just assistants, but valuable co-collaborators who bring fresh perspectives to complex problems.My approach involves three core pillars:
1) Providing Scaffolding, then Autonomy: I start by providing clear guidance and concrete examples (how to conduct a semi-structured interview or how to code qualitative data). As the mentee builds confidence, I gradually step back, empowering them to take ownership of their tasks and encouraging independent discovery.
2) Fostering Critical Inquiry: I create an interactive environment where asking "why" and "how" is expected. I encourage mentees to look beyond the surface of the data, question assumptions, and develop logical arguments without fear of making mistakes. Learning from trial and error is a critical part of the research process.
3) Aligning with Individual Goals: I strive to understand what motivates each mentee (whether they are preparing for graduate school or building a resume for industry). I tailor their research tasks to build the specific analytical and practical skills that will serve their long-term professional objectives.