Humble AI: Building Guardrails Against Overconfidence

Share this Session:
Share on facebook
Share on twitter
Share on linkedin
Session Date & Time:
On Demand
Days
Hours
Minutes
Seconds

Presented by DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.

  • Session Description
  • Presenters
  • Additional Resources

As AI becomes ubiquitous, more and more high-stakes decisions will be made automatically by machine learning models. AI can determine the very future of your business and can make life-or-death decisions for real people.

But as the world changes, an AI system is often faced with new examples that it hasn’t seen before, and it may not know the right answer. Without proper guardrails, these automated decisions can quickly turn into catastrophic failures if left unchecked and can reduce trust in AI. As the stakes get higher, it is critical that AI systems are built to be humble — just like humans, AI should know when it doesn’t know the right answer.

With DataRobot’s Humble AI, models that aren’t confident in their predictions can respond accordingly, whether that means defaulting to a “safe” decision, alerting an administrator for human review, or not making a prediction at all.

Learn how to:

  • Understand the limitations of your model and when you may need human intervention
  • Create a comprehensive set of Humble AI triggers that will protect from common failures of model overconfidence
  • Monitor your model over time for new errors and sources of overconfidence

You will learn how to build robust, fault-tolerant, humble AI systems using DataRobot’s Humble AI feature in MLOps.

Login to View Content

Login Or Register

Event Registration

Almost there!

We need to confirm your email.

You're Almost thEre!

Check your Email for Confirmation and Login Instructions

You will receive an email confirming your registration – please click on the link in the email to confirm.

Login instructions will also be provided in the email. If you don’t get the email, please let us know at info@cognilytica.com.