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Computer Vision on AWS
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AI governance is the process of implementing controls and establishing processes and procedures to minimize risks of the development and use of AI systems, while maximizing the delivery of business outcomes. AI systems are prone to the same risks as other technology stacks. Their infrastructure needs to be designed to be resilient, scalable, and be able to withstand security vulnerabilities and cyber attacks. They also face additional unique risks, which we will discuss throughout this section.
ML models require large amounts of data. The amount of data that is available for ML development is rapidly increasing, and not all of this data is beneficial or relevant for solving an AI/ML problem. There is potential for unintended bias within the data processing phase and throughout the entire ML life cycle. Organizations also have to abide by regulations and compliance standards. By proactively establishing an organizational AI governance framework, you can...