Reducing risk from AI chatbots in public sector applications

Music City Center 

AI-powered chatbots are promising tools for the public sector. They can make official statistics more findable, accessible, and interpretable for more constituents. However, AI chatbots also create risk. They can return incorrect or misleading information, and they are often vulnerable to misuse. To date, most statistical agencies have viewed this risk-reward tradeoff as unacceptable. In this work, we present a toolkit for reducing risk from AI chatbots. We use the motivating example of a chatbot enabling interaction with the findings of a large, federal survey. We discuss six risk reduction tools: 1) system guardrails, 2) Q&A interfaces, 3) open-source models, 4) extractive responses, 5) system validation, and 6) red-teaming. These tools help prevent misuse, reduce the likelihood of incorrect or misleading responses, and avoid privacy concerns. We conclude with a roadmap for AI chatbot implementation following a responsible AI framework.

AI

Chatbot

LLM

RAG

Responsible AI

AI-ready data 

Government Statistics Section