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To understand the risks posed by AI, follow the money

O'Reilly on Data

Others retort that large language models (LLMs) have already reached the peak of their powers. It’s difficult to argue with David Collingridge’s influential thesis that attempting to predict the risks posed by new technologies is a fool’s errand. However, there is one class of AI risk that is generally knowable in advance.

Risk 221
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What is Model Risk and Why Does it Matter?

DataRobot Blog

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. What is a model?

Risk 111
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Enabling a data-driven IT modernization strategy

CIO Business Intelligence

The big picture : In the midst of a rush to technology modernization, it’s critical to ensure the organization’s data assets are not overlooked. Why it matters:  Data-driven business decisions must factor prominently in modernization efforts. The bottom line:  Don’t leave data behind.

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What Is Data Modeling? Data Modeling Best Practices for Data-Driven Organizations

erwin

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

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4 IT Management Best Practices Data-Driven Businesses Must Practice

Smart Data Collective

Data-driven businesses are far more successful than companies that don’t utilize data to their advantage. Unfortunately, they often find that managing their data effectively can be a challenge. Companies that rely on big data need a reliable IT department. Keep reading to learn how to do this.

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Product lifecycle management for data-driven organizations 

IBM Big Data Hub

The key foundation of a strong PLM strategy is healthy and orderly product data, but data management is where enterprises struggle the most. To take advantage of new technologies such as AI for product innovation, it is crucial that enterprises have well-organized and managed data assets.

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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. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk?