1. Do you (i.e., your organization) have an inventory of tools/systems/engines that could meet the definition of an “algorithm” or “machine learning” or “artificial intelligence”?
2. Do you (i.e., your organization) know all of the data elements used for each tool/system/engine that could meet the definition of an “algorithm” or “machine learning” or “artificial intelligence”?
3. Do you (i.e., your organization) know how many of the data sets used, could contain biases?
4. Have you (i.e., your organization) classified all of the systems that could meet the definition of an “algorithm” or “machine learning” or “artificial intelligence” as to its capabilities?
5. Do you (i.e., your organization) know how many and what types of testing is being conducted on a system that could meet the definition of an “algorithm” or “machine learning” or “artificial intelligence” as to its capabilities?
6. Do you (i.e., your organization) have dependent AI engines (primary systems from Amazon, IBM, etc.) or multiple AI systems interacting with each other?
7. Are you (i.e., your organization) aware of how many regulatory bills have been passed or pending and in which US states?
8. Do you (i.e., your organization) have legal clauses you use for contracts with third party AI providers, specifically related to the use of AI systems?
9. Do you (i.e., your organization) conduct AI third party risk assessments, using third party risk questionnaires, to gain transparency on the system and how it is managed?
10. Do you (i.e., your organization) have specific governance documents and requirements for the use of AI and related systems?
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