Remove Experimentation Remove Finance Remove Risk
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Practical Skills for The AI Product Manager

O'Reilly on Data

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

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AI adoption in the enterprise 2020

O'Reilly on Data

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines. But what kind?

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Liberty Mutual CIO Monica Caldas on developing a digital-savvy workforce

CIO Business Intelligence

Whether you’re in claims, finance, or technology, data literacy is a cornerstone of our collective accountability. This team addresses potential risks, manages AI across the company, provides guidance, implements necessary training, and keeps abreast of emerging regulatory changes. We have 25% of our employees on Liberty GPT.

Insurance 120
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AI Has an Uber Problem

O'Reilly on Data

To the extent that entrepreneurial funding is more concentrated in the hands of a few, private finance can drive markets independent of consumer preferences and supply dynamics. The risk of these deals is, again, that a few centrally chosen winners will quickly emerge, meaning there’s a shorter and less robust period of experimentation.

Marketing 225
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How Svevia connects roads, risk, and refuse through the cloud

CIO Business Intelligence

Digital alerts Another project deals with slow-moving vehicles, something that increases the risk of accidents on the roads. Not for experiments For a company like Svevia, there’s no room for experimentation, underlines Wester. “We Since the route optimization came into place, fewer emptyings are required, he notes.

Risk 98
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AI poised to replace entry-level positions at large financial institutions

CIO Business Intelligence

Right now most organizations tend to be in the experimental phases of using the technology to supplement employee tasks, but that is likely to change, and quickly, experts say. But that’s just the tip of the iceberg for a future of AI organizational disruptions that remain to be seen, according to the firm.

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3 steps to eliminate shadow AI

CIO Business Intelligence

The familiar narrative illustrates the double-edged sword of “shadow AI”—technologies used to accomplish AI-powered tasks without corporate approval or oversight, bringing quick wins but potentially exposing organizations to significant risks. Establish continuous training emphasizing ethical considerations and potential risks.