From the course: IAPP Artificial Intelligence Governance Professional (AIGP) Cert Prep

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Defining key roles in AI governance

Defining key roles in AI governance

From the course: IAPP Artificial Intelligence Governance Professional (AIGP) Cert Prep

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Defining key roles in AI governance

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Let's now discuss one of the most critical foundations of AI governance, who is responsible. Unlike traditional systems, AI development and deployment involve diverse cross-sectional teams. Effective governance requires clarity around roles and responsibilities at each stage of the AI lifecycle. Let's start with the three broad categories used in many legal and governance frameworks. First, developers, those who design, build, or train AI systems. This includes data scientists, machine learning engineers, and research teams. They're responsible for model architecture, data set curation, algorithm selection, and performance testing. Second, deployers, those who integrate and operationalize AI systems in real-world environments. This often includes IT operations, DevOps, and systems architects. They ensure models are properly configured, secured, and monitored in production. Third, users, the end users or business units who apply AI outputs in decision making. This group may include…

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