Remove Document Remove Measurement Remove Metrics Remove Risk
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Preliminary Thoughts on the White House Executive Order on AI

O'Reilly on Data

The recent discovery (documented by an exposé in The Atlantic ) that OpenAI, Meta, and others used databases of pirated books, for example, highlights the need for transparency in training data. Operational Metrics. Methods by which the AI provider manages and mitigates risks identified via Red Teaming, including their effectiveness.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. How Do You Measure Data Quality?

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How to build a successful risk mitigation strategy

IBM Big Data Hub

.” This same sentiment can be true when it comes to a successful risk mitigation plan. The only way for effective risk reduction is for an organization to use a step-by-step risk mitigation strategy to sort and manage risk, ensuring the organization has a business continuity plan in place for unexpected events.

Risk 74
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The hard truth of IT metrics

CIO Business Intelligence

You might have heard that if you can’t measure you can’t manage. And if you think you need metrics to manage you might be feeling guilty about not having enough of them. Good metrics are hard to craft, harder to manage, expensive to maintain, and perishable besides. Bad metrics are worse than no metrics.

Metrics 103
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Automating Model Risk Compliance: Model Monitoring

DataRobot Blog

If the assumptions are being breached due to fundamental changes in the process being modeled, the deployed system is not likely to serve its intended purpose, thereby creating further model risk that the institution must manage. Monitoring Model Metrics. Figure 1: Data drift tab of a deployed DataRobot model.

Risk 59
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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362
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Sport analytics leverage AI and ML to improve the game

CIO Business Intelligence

Working with partner Amazon Web Services (AWS), the NFL has developed Digital Athlete, a platform that uses computer vision and ML to predict which players are at the highest risk of injury based on plays and their body positions. million video frames and documents about 100 million locations and positions of players on the field.

Analytics 110