AI and Data Quality Quiz

What is a benefit of a diverse, balanced, and large dataset?

• Training time

• Data privacy

• Model accuracy

What are the three commonly used examples of AI in CRM?

• Predictive scoring, reporting, Image classification

• Predictive scoring, forecasting, recommendations

• Einstein Bots, face recognition, recommendations

Cloud Kicks wants to optimize its business operations by incorporating AI into its CRM. What should the company do first to prepare its data for use with AI?

• Remove biased data.

• Determine data availability.

• Determine data outcomes

A healthcare company implements an algorithm to analyze patient data and assist in medical diagnosis. Which primary role does data Quality play In this AI application?

• Enhanced accuracy and reliability of medical predictions and diagnoses

• Ensured compatibility of AI algorithms with the system's Infrastructure

• Reduced need for healthcare expertise in interpreting AI outouts

What are some of the ethical challenges associated with AI development?

• Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes

• Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions

• Inherent neutrality of AI systems, which eliminates any potential for human bias in decisionmaking

Cloud Kicks discovered multiple variations of state and country values in contact records. Which data quality dimension is affected by this issue?

• Usage

• Accuracy

• Consistency

How is natural language processing (NLP) used in the context of AI capabilities?

• To cleanse and prepare data for AI implementations

• To interpret and understand programming language

• To understand and generate human language

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

• Testing models with diverse datasets

• Striving for model explain ability

• Working with human rights experts

Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution. Which data quality dimension Is essential for this custom application?

• Consistency

• Duplication

• Age

What should organizations do to ensure data quality for their AI initiatives?

• Collect and curate high-quality data from reliable sources.

• Rely on AI algorithms to automatically handle data quality issues.

• Prioritize model fine-tuning over data quality improvements.