AI Fluency – Data Privacy

Topics covered include: 

• Defining large language models and multimodal models 

• Discussing how models are trained on data 

• Defining grounding data, data classification, and training data 

• Explaining the types of personal data that AI tools collect 

• Listing sources of training and grounding data 

• Identifying ways to block your data from the primary training sources 

• Explaining the importance of safeguarding customer data 

• Identifying laws and regulations that apply to specific industries and locations 

• Listing three techniques for protecting internal data 

• Defining data loss prevention and data classification 

• Discussing the difference in privacy levels for free vs. paid versions 

• Reviewing a sample privacy policy 

• Identifying the privacy features of common AI tools