Be accountable for errors
From early in the product development process, plan for the fact that your AI system will make bad predictions at some point. This is an important part of confirming that AI is the right technology for your project.
Think through the types of errors that your system could make, and their consequences. You should have an informed point of view about what's at stake for your user for a given error and expected impact of false positive and false negative predictions.
Plan to remediate for such errors using approaches like:
- Setting users expectations about your system with explanations
- Providing manual controls when the AI fails
- Offering high-touch customer support
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Provide a way forward
Providing access to a person can be one way to make sure users’ concerns and problems are directly addressed.
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Make changes to product
Sometimes the user’s error can’t be directly remedied but actions can be taken to make sure other users don’t encounter the same problem.