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What We Learned Auditing Sophisticated AI for Bias

O'Reilly on Data

As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. applies external authoritative standards from laws, regulations, and AI risk management frameworks. The answer is simple—bad things and legal liabilities.

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Cyber Fraud Statistics & Preventions to Prevent Data Breaches in 2021

Smart Data Collective

One bad breach and you are potentially risking your business in the hands of hackers. In this blog post, we discuss the key statistics and prevention measures that can help you better protect your business in 2021. Cyber fraud statistics and preventions that every internet business needs to know to prevent data breaches in 2021.

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Data Analytics Helps Hedge Funds Improve Customer ROIs

Smart Data Collective

We will talk about some of the biggest ways that big data is changing the future of risk management among hedge funds. Data Analytics Helps Create More Robust Risk Management Controls We mentioned years ago that big data is changing risk management.

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How to build a successful risk mitigation strategy

IBM Big Data Hub

Step 2: Perform a risk assessment The next step is to quantify the level of risk for each risk identified during the first step. This is a key part of the risk mitigation plan since this step lays the groundwork for the entire plan. This approach may require the organization to compromise other resources or strategies.

Risk 69
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Managing risk in machine learning

O'Reilly on Data

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. As we deploy ML in many real-world contexts, optimizing statistical or business metics alone will not suffice. Classification parity means that one or more of the standard performance measures (e.g.,

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. This beats projections for almost all other occupations. BI engineer. BI Data Scientist.

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What to Do When AI Fails

O'Reilly on Data

And last is the probabilistic nature of statistics and machine learning (ML). Because statistics: Last is the inherently probabilistic nature of ML. Materiality is a widely used concept in the world of model risk management , a regulatory field that governs how financial institutions document, test, and monitor the models they deploy.

Risk 357