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Salesforce AI Associate: How to Test Models with Diverse Datasets for Inclusive AI

Learn how to test models with diverse datasets for inclusive AI with this guide. Find out why diversity is important, how to collect and curate diverse datasets, and how to evaluate model performance and fairness.

Table of Contents

Question

What is an example of Salesforce’s Trusted AI Principle of Inclusivity in practice?

A. Testing models with diverse datasets
B. Striving for model explain ability
C. Working with human rights experts

Answer

A. Testing models with diverse datasets

Explanation

The correct answer is A. Testing models with diverse datasets. Inclusivity is one of the Salesforce’s Trusted AI Principles that aims to improve the human condition and represent the values of all those impacted, not just the creators. Testing models with diverse datasets is an example of this principle in practice, as it helps to ensure that the models are fair, accurate, and representative of the diverse customer base. Testing models with diverse datasets can help to prevent and mitigate bias, avoid harmful or discriminatory outcomes, and enhance customer satisfaction and trust.

An example of Salesforce’s Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing models with diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.

Salesforce AI Associate actual real practice exam question and answer (Q&A)

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