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CIOs look to sharpen AI governance despite uncertainties

CIO Business Intelligence

He emphasizes there is no single document that captures all aspects of the risks and no clear authority to enforce use of generative AI, which is advancing on a daily basis.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Crucially, it takes into account the uncertainty inherent in our experiments. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. In this section we’ll discuss how we approach these two kinds of uncertainty with QCQP.

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Uncertainties: Statistical, Representational, Interventional

The Unofficial Google Data Science Blog

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Those F’s are: Fragility, Friction, and FUD (Fear, Uncertainty, Doubt). encouraging and rewarding) a culture of experimentation across the organization. Encourage and reward a Culture of Experimentation that learns from failure, “ Test, or get fired! Test early and often. Expect continuous improvement.

Strategy 290
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Great Resignation 3.0? Rising workload and skills gap push workers to consider job changes

CIO Business Intelligence

As workers face heightened uncertainty, rising workloads, and continue to confront financial stress, they are prioritizing skills growth and embracing new and emerging technologies such as generative AI to accelerate their careers,” Carol Stubbings, Global Markets and Tax & Legal Services Leader at PwC UK said in the report.

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Generative AI: now is the time to ‘learn by doing’

CIO Business Intelligence

The pattern for success at learning how to create value safely and responsibly is a mindful culture of experimentation and thoughtful “learning by doing.” He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. Artificial Intelligence, Machine Learning

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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”