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3 AI Training Tactics For Your Chatbot

This is a new section offering three ways to solve a problem. See more on Linkedin.com/in/ahern

1. Review your fallbacks
   Review your fallbacks and "thumbs up, thumbs down" feedback. Fallbacks occur when the AI cannot answer the question. This tells you the AI needs more data for training and/or specific intents on the subject. The "thumbs up, thumbs down" is a user's immediate reaction to the chatbot's response. Although this can be another useful way to gauge how the chatbot's performing, it can have false positives. Although a chatbot's response may have been true, the user may not have liked the answer. In other cases, the thumbs down can tell you the answer was not adequate enough.

2. Don't assume AI is smarter than you
   Review conversation logs to make sure the AI is responding correctly and not getting off-topic. Off-topic responses can indicate gaps or weaknesses in the AI's knowledge base. Checking the logs can also inform you on when you have to add a decision flow to expedite the conversation.

3. Test and test again
   When adding content for your AI, test it from multiple perspectives to make sure the AI answers the questions correctly. Remember: scripted AI intents override generative AI responses. It's important to test to make sure you do not have intent collisions where the AI is overridden with an incorrect response. You may also run into a situation where the AI data set used may be biased or unknowledgeable on a topic, so it presents the wrong answer.

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