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Website content navigation chatbot

Italy - Senate

Use case ID: 025

Author: Senate of Italy

Date: 12 June 2024 

Objective: 

Assist users in navigating the Senate website by providing an artificial intelligence (AI)-powered chatbot that offers content recommendations and guidance based on user queries in natural language. 

Actors: 

  • Senate website users (citizens, researchers and journalists)
  • Senate IT and web development team 

Prerequisites: 

  • Existing Senate website with accessible content
  • Trained large language model (LLM)-based AI model for understanding and processing natural-language queries
  • Database of Senate documents and website content
  • Internet accessibility for users 

Scenario: 

  1. The user accesses the Senate website.
  2. User initiates a chat session with the AI-powered chatbot, asking a question or seeking guidance (e.g. “How can I find recent bills on health care?”).
  3. The LLM-based AI model processes the natural-language query to understand the intent and key terms.
  4. The AI chatbot provides a relevant response, directing the user to specific sections, documents or links on the website.
  5. If the user’s request is complex, the chatbot may ask follow-up questions to narrow down the results.
  6. The chatbot guides the user step by step to the desired content or provides direct links.
  7. The user can continue to ask additional questions or seek further assistance within the same chat session.
  8. The system logs the interaction for continuous improvement of the chatbot. 

Alternate flows: 

  • If the LLM-based AI model cannot understand the query, it prompts the user to rephrase or provides suggestions.
  • If the user requests information not available on the website, the chatbot can suggest alternative sources or direct them to contact support. 

Expected results: 

  • User satisfaction is improved owing to quick and accurate content navigation assistance.
  • Engagement and interaction with the Senate website are increased.
  • It takes less time and effort for users to find specific information.
  • Accessibility for users unfamiliar with the website layout or content structure is improved. 

Potential challenges: 

  • Ensuring the LLM-based AI model can accurately understand diverse phrasing and terminologies
  • Handling ambiguous queries or those with multiple possible interpretations 

Data requirements: 

  • Historical user interactions and queries for training and improving the LLM-based AI model
  • Database of Senate documents, laws and other relevant information. 

Integrations with other systems: 

  • Existing Senate website infrastructure
  • LLM-based AI processing systems and models
  • User interface components for the chatbot 

Success metrics: 

  • Query response time
  • User satisfaction ratings and feedback
  • Accuracy and relevance of chatbot responses
  • Increase in the number of users engaging with the chatbot
  • Reduction in user queries requiring manual intervention or support

 

The Use cases for AI in parliaments collection is published by the IPU’s Centre for Innovation in Parliament as part of the Parliamentary Data Science Hub’s project to create guidelines for AI governance in parliaments.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International licence. It may be freely shared and reused with acknowledgement of the author and the IPU. 

A use case describes how a system should work. It is used to plan, develop and measure implementation. A use case is not the same as a case study, which is a descriptive text of an actual project’s implementation. Please note that this use case is provided “as is” and neither the IPU nor the author accepts any responsibility for its use.

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