Public consultations are crucial for the policymaking process, but analyzing the responses is time-consuming. To address this, the Incubator for Artificial Intelligence (i.AI) is developing the Consultation Analyser tool, which utilizes AI and data science techniques to extract patterns and themes from public consultation responses. By automating the analysis process, computers can efficiently handle large amounts of data, allowing humans to focus on understanding the patterns. This tool aims to save the UK government a significant amount of money, as consultations cost around £80 million per year. The Analyser uses topic modeling to identify recurring themes, presents the outcomes on dashboards, and keeps the raw responses for transparency. The project is being piloted with the Department of Health and Social Care and will be made open source via GitHub.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| Developing AI tool to analyze public responses to government consultations | Use of AI in analyzing consultation responses | AI automates analysis, saving time and costs | Efficiency and cost-saving measures |
| Consultation process becoming faster and fairer with AI technology | Adoption of AI in government consultations | Analyzing responses becomes quicker, more comprehensive, and unbiased | Need for efficient and equitable analysis |
| Government consultations cost £80m a year; AI tool could save most of that | Cost reduction in government consultations | Significant cost savings in consultation process | Financial efficiency and optimization |
| AI tool uses topic modeling to extract themes from responses | AI-driven theme extraction from consultation responses | Better understanding of common recurring themes in responses | Enhanced analysis and decision-making process |
| Analyzing outcomes presented on dashboards for policy makers | Data visualization for policy makers | Enhanced exploration of consultation outcomes | Improved accessibility and understanding of data |
| Pilot project running with the Department of Health and Social Care | Testing and evaluation of Analyser | Continued testing and refinement in government departments | Iterative development and improvement of the tool |
| Code will be open source and published via GitHub | Open sourcing the Analyser | Accessibility and collaboration in further development and use of the tool | Foster community participation and innovation. |