9 questions to ask when auditing your AI systems
IT audits for systems of record data are an annual event at most companies. But auditing artificial intelligence and big data, while ensuring that they are under sufficient security and governance, is still a work in progress.
The good news is that companies already have a number of practices that they can apply to AI and big data. These practices are embodied in IT policies and procedures that can be adapted for both AI and big data. All are extremely helpful at a time when professional audit firms offer limited AI and big data services.
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Here are nine questions and ways that companies can use to self-audit their AI and big data:
1. Do you know where your data is coming from?
Companies acquire their own data from business operations, but they also purchase and use data from outside vendors for AI and analytics. All data from the outside should be evaluated for trustworthiness and quality of data before data is used in AI and analytics. Vetting data from third parties should be part of every RFP.
2. Have you addressed data privacy?
You can have your own data privacy rules and agreements with clients or customers, but these data privacy rights get stretched when they are extended to outside business partners that may not have the same data privacy standards. . In these cases, there should be policies and procedures for data privacy not only in IT, but in corporate legal and compliance departments to ensure that customers/clients whose data could be used, anonymized or shared are aware of that fact.