Remove Business Objectives Remove Data Quality Remove Measurement Remove Risk
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Automating Model Risk Compliance: Model Validation

DataRobot Blog

What are some steps that the modeler/validator must take to evaluate the model and ensure that it is a strong fit for its design objectives? Evaluating ML models for their conceptual soundness requires the validator to assess the quality of the model design and ensure it is fit for its business objective.

Risk 52
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Beyond the hype: Key components of an effective AI policy

CIO Business Intelligence

An AI policy serves as a framework to ensure that AI systems align with ethical standards, legal requirements and business objectives. While this leads to efficiency, it also raises questions about transparency and data usage. This includes regular audits to guarantee data quality and security throughout the AI lifecycle.

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Deep automation: A CIO weapon for turning disruption into opportunity

CIO Business Intelligence

Implement robust risk assessment and mitigation strategies encompassing automation initiatives. This includes regular security audits of automated systems and ensuring compliance with data protection regulations. Prioritize data quality to ensure accurate automation outcomes.

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

First, don’t do something just because everyone else is doing it – there needs to be a valid business reason for your organization to be doing it, at the very least because you will need to explain it objectively to your stakeholders (employees, investors, clients).

Strategy 290
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10 digital transformation roadblocks — and 5 tips for overcoming them

CIO Business Intelligence

Failure to align technology capabilities with business goals can result in a wasted investment in technology that doesn’t support business objectives. Transformational leaders must ensure their organizations have the right systems and processes in place to collect, store, and analyze data effectively.

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Bringing an AI Product to Market

O'Reilly on Data

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Any metric can and will be abused.

Marketing 363
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Ways to ward off a doomed stakeholder management strategy

CIO Business Intelligence

And with AI used in almost every part of the business, stakeholders have become much more tech savvy, reducing their dependency on IT departments. But as a result, anybody could then expose a lot of company data inadvertently. The CIO is really worried about cybersecurity and the risk of data exfiltration,” says Fernandes.