Before we talk about AI, let’s talk about your data
More businesses are addressing their digital transformation initiatives
Generative AI models heavily rely on the training data they receive to generate meaningful and reliable outputs. It only makes sense that you would work to “purify†your data ?to ensure that the data used to train these models is of high quality, accurately representing the desired outcomes. By implementing data validation, cleaning, and normalization
Data governance helps you navigate the complex landscape of data protection regulations and maintain the security of sensitive information. Setting up your data governance provides a secure and compliant infrastructure that can help you meet various regulatory requirements when you transition into working with AI. By implementing data governance practices
Generative AI models may require access to personal or sensitive data. Data governance enables you to implement privacy safeguards
AWS provides services like Amazon Macie, which automatically discovers, classifies, and protects sensitive data. By leveraging features like data anonymization and pseudonymization, available through AWS services, you can protect individual privacy and prevent exposure of PII when working with Generative AI.
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Generative AI models have the potential to inherit biases present in the training data, leading to unfair or discriminatory outcomes. Data governance practices can help identify and address biases by carefully curating and evaluating training datasets. It is important to address these issues within your data automation. Amazon SageMaker Clarify can help identify and mitigate biases in your datasets. It provides model examinability and fairness testing capabilities, allowing you to ensure that your Generative AI models produce fair and unbiased outputs.
Generative AI has the potential to create realistic content, including text, images, and videos. Data governance plays a critical role in establishing ethical guidelines
Optimizing your data to ?take full advantage of Generative AI can be challenging.?Therefore, it’s helpful to have outside experience, whether that be trusted colleagues or a good message board you can reference while planning.?Alternatively, you can work with solution architects from AWS or look to leverage outside consultants.?It is important to build a team of resources that you trust to execute your mission. If you are looking for guidance please feel to reach out to us at? Oxford Global Resources .