Improving AI Reliability: Building Effective Feedback Mechanisms for Quality Assurance

Join our session to learn strategies for quality assurance in AI. Discover how to implement feedback mechanisms to monitor and improve your AI tools, ensuring they perform reliably and meet user expectations. Perfect for anyone looking to improve their AI tooling's effectiveness.

Agenda for this session:

Introduction and Objectives

   - Welcome and brief overview of the session's goals.

Tracking Accuracy in AI

   - Importance of data review and tracking accuracy metrics for AI.

Feedback and QA Processes for AI

   - Overview of different feedback mechanisms and QA processes.

Implementing Feedback with Macros and Tools

  - Quick guide to using macros in QA processes.

   - Introduction to a new free open-source app to assist in these processes.

Q&A and Wrap-Up