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Introduction to Responsible AI: Challenges to Address Intellectual property and Toxicity

Explore the challenges of responsible AI and discover how to mitigate issues related to Intellectual property and Toxicity. Options include unsupervised learning, large language models (LLMs), intellectual property, toxicity, and enterprise risk.

Table of Contents

Question

Which options are challenges of responsible artificial intelligence (AI)? (Select TWO.)

A. Unsupervised learning
B. Large language models (LLMs)
C. Intellectual property
D. Toxicity
E. Enterprise risk

Answer

C. Intellectual property
D. Toxicity

Explanation

Toxicity and intellectual property are two challenges of responsible AI. Toxicity is explained as a foundation model output that is hateful, threatening, insulting, or demeaning to an individual or a group of individuals. There is a tendency of early LLMs to produce outputs that were verbatim regurgitation of parts of their training data, resulting in privacy and copyright concerns around intellectual property. Implementing responsible AI best practices can help overcome these challenges.

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