Overview of Indicators Requiring Qualitative Analysis

Nine indicators were assessed through qualitative analysis of publicly available government policies and frameworks. These indicators covered key areas such as responsible AI policies, ethical considerations in AI procurement, public engagement, data ownership, interoperability, bias mitigation, audit practices, and vendor compliance requirements.

Indicators

• Does the agency have publicly available policies, frameworks, or guidelines that specifically address responsible AI procurement or acquisition?

• Does the agency provide information about how ethical considerations are incorporated into AI/ML contracts, procurement or acquisition processes?

• Does the agency provide information about measures taken to promote diversity and inclusion in AI procurement, such as efforts to engage minority-owned businesses?

• Does the agency provide information about public engagement in its AI procurement or acquisition process?

• Does the agency provide information about data ownership and privacy concerns in its AI procurement or acquisition practices?

• Does the agency provide information about steps taken to ensure interoperability and prevent vendor lock-in when procuring or acquiring AI systems?

• Does the agency publicly disclose its processes for addressing (such as evaluation and mitigation) potential biases and AI-enabled discrimination in AI systems during the procurement or acquisition process?

• Does the agency publicly disclose whether it conducts AI audit and/or impact assessments before and/or after procurement?