Expert Alternatives
The policy research team studies problems, evidence, reform alternatives, and constraints.
APPLICATION 01Research in Progress
Pension Reform Project
This is AIPOL's first use case, connecting policy experts' pension-reform alternatives, synthetic-citizen responses, AI-generated additional alternatives, and human review.
Research question
How can AI assist in developing complex policy alternatives?
Designing and validating the roles of humans and AI for pension reform, which intertwines intergenerational interests, long-term finances, retirement income, and system trust.
First Synthetic Responses
100 synthetic-citizen personas record judgments and conditions for each expert alternative.
Opinions and Conditions
Structuring not only participants' choices but also conditions, concerns, and reasons for opposition.
Additional Alternatives
AI proposes based on opinions, while humans review, modify, and approve.
Development record
Research and tool development are conducted concurrently.
Methodology and execution paths are verified with synthetic data prior to real-world application, distinguishing results from actual public opinion.
Two-round pension deliberation scenario
Review the professor-provided flow—pre-survey, first ballot, AI diagnosis and small-group discussion, then the second and final ballot—inside this pension reform case. Policy figures and analytical copy remain pending expert approval.
Open the pension experiment preview →Policy Development Protocol
Structure linking evidence, expert alternatives, synthetic responses, AI proposals, and human approval.
Synthetic Citizen Experiment
Expert pension proposals and fiscal assumptions were entered; the engine ran and recorded two response rounds from 100 model-generated personas and an AI-generated additional option. This did not validate real acceptance, public opinion, representativeness, behaviour, deliberative effects, policy effects, or the legitimacy of any pension proposal.
View synthetic simulation pre-verification →First Field Application
Policy experiments will be conducted with a real audience at the Korean Association for Policy Studies flagship session.
Event Info →What will be shared
Public Assets to Leave Behind in the Case
Leave materials for reuse and critique by other research, rather than a single policy conclusion.
Methodology
Policy development stages and human-AI roles.
Prompts and Conditions
Model, version, input, and review criteria.
Tools
Research engine and online/on-site participation tools.
Limitations
Framing, sample, errors, and unaddressed issues.