Remove Modeling Remove Risk Management Remove Testing Remove White Paper
article thumbnail

What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

article thumbnail

Data Literacy for Responsible AI: Governance and Accountability

DataRobot

Throughout history, introducing innovations in fields like aviation and nuclear power to society required robust risk management frameworks. AI is no different, and by its nature, it demands a comprehensive approach to governance utilizing risk management. White Paper. Step 1: Classify the AI Decision Type.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Simulation for better decision making

Cloudera

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. These examples are well covered by many others (e.g.,

article thumbnail

Minding Your Models

DataRobot Blog

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

Modeling 105
article thumbnail

Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for There are models everywhere. In other words, #adulting.