On-Demand Webinar

Toward Responsible AI: Creating Fair Machine Learning Models

Discover how to put responsible AI into practice with SAS® Viya®.

About the webinar

As incidents of discrimination by machine learning models continue to surface, organizations are questioning whether they can make decisions based on machine learning’s automated, self-learned logic. Globally, governments are shaping legal frameworks that govern the use of this technology.

With growing uncertainty and regulations, creating accurate, fair and trustworthy models is more important than ever.

Join the webinar to learn how SAS Viya helps organizations arm themselves against unfair decisions and implement responsible AI.

Why attend?

  • Learn about the legal requirements of machine learning models.
  • Discover how to assess and mitigate machine learning bias.
  • Get inspired about how SAS Viya’s fairness capabilities can help.

Have a SAS profile? To complete this form automatically Sign In

*
*
*
*
 
 

All personal information will be handled in accordance with the SAS Privacy Statement.

 
  Yes, I would like to receive occasional emails from SAS and SAS business partners about their products and services. I understand I can withdraw my consent at any time by clicking the opt-out link in the emails.
 
 

About the Experts


Véronique Van Vlasselaer
Analytics and AI Lead for South, West and East Europe, SAS

Véronique Van Vlasselaer helps companies envision and prepare for an AI-driven future, embrace the power of data science to support intelligent decisioning and discover the real value in their data. She holds a PhD in Business Economics from KU Leuven and is the co-author of Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection.


Tamara Fischer
Principal Data Scientist, Analytics and AI, SAS

Tamara Fischer has implemented solutions throughout the entire analytical life cycle, from model development to model deployment. She works with an international team of data scientists and architects and focuses on all analytical aspects of ModelOps. Before Fischer joined SAS, she graduated in statistics and worked for an insurance company.