Responsible use of AI refers to developing, deploying, and operating artificial intelligence systems according to principles that promote fairness, transparency, accountability, safety, and appropriate human oversight.
In this scenario, the company wants AI adoption to align with organizational objectives while minimizing discriminatory outcomes and supporting transparent decision-making.
These requirements directly correspond to responsible AI governance principles.
AWS emphasizes incorporating responsible AI considerations throughout the complete machine learning lifecycle, including initial design, data preparation, model training, evaluation, deployment, and ongoing monitoring.
Risk management focuses on identifying and mitigating potential threats. Data curation concerns collecting, cleaning, and maintaining datasets. Cloud financial management addresses the financial efficiency of cloud resources.
Although these activities may support AI governance, they do not fully represent the ethical and organizational responsibilities described in the question.
Therefore, responsible use of AI is the correct governance perspective.
