Abstract: Computer systems and associated methods are disclosed to implement a decision model auditing system that allows clients of a machine learning decision system to audit the decision-making process the decision system. In embodiments, the decision system is instrumented with reporting code to collect internal decision data of the decision system and send the data to a decision auditing service. In embodiments, the auditing service provides the client with an obfuscated token, which may be used to anonymize the client requests to the decision system. As client requests are handled by the decision system, the reporting code generates audit messages to the auditing service. The auditing service stores the audit information, which may later be provided to the client or used generate an audit report. In embodiments, the audit report may indicate whether the decision system contains any undesired bias.

Abstract: Embodiments of systems and methods are described for performing community analysis of computing performance. These systems and methods can collect and analyze community performance data from a plurality of physical or virtual infrastructure installations. The systems and methods can leverage this community performance data to identify and recommend areas where individual physical or virtual infrastructures can improve performance.