Responsible AI
Responsible AI refers to a set of frameworks that promote accountable, ethical and transparent Artificial Intelligence (AI) development and adoption. From approving loan agreements to selecting job candidates, many AI use cases are sensitive in nature. Organizations adopt responsible AI models to avoid biases, which can be ingrained in AI design or the data sources it uses.
As AI becomes more sophisticated and prevalent, ethical considerations must be given significant consideration. Industry leaders and end users alike are calling for more AI regulation.
Responsible AI best practices generally apply the following guidelines:
- Asking questions that evaluate why you’re using AI for each use case
- Establishing management policies that address accountability and potential flaws
- Committing to appropriate and secure data use
- Understanding that humans should be auditing an AI’s decision-making and results
- Recognizing that bias can be unconsciously included in AI design
- Creating documentation that explains how the AI works
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