Driving Quality in Your AI Training Data

What do biased chatbots, a failed facial recognition system and self-driving car accidents have in common? They were all trained using poor quality AI training data.

This webinar will discuss the different components of quality and how you can use best practices to ensure your data is annotated for optimal model performance.

Listen to our panel of experts as they provide relevant information and real-world advice on data quality, which you can take away and apply to your business.

Topics covered:

• Definition of quality for annotated data
• Job design and active monitoring techniques
• Ground truth and auditing to ensure quality
• Contributor targeting and custom channels
• Continuous improvement via machine learning