Generative AI Certificate Q&A: Key dangers for organizations that over rely generative AI systems?

Question

What’s one of the key dangers for organizations that over rely on generative AI systems?

A. Generative AI systems might make key decisions about who works for the company.
B. They will regenerate the same material without any spark of creativity.
C. Your employees might resign if they feel that your system is in danger of replacing their livelihood.
D. Generative AI systems will start to run these organizations with little to no human oversight.

Answer

D. Generative AI systems will start to run these organizations with little to no human oversight.

Explanation

Generative AI systems are powerful and innovative technologies that can create new and original content, such as text, images, music, or code, by learning from massive datasets. Generative AI systems have many potential benefits and applications for various domains and industries, such as entertainment, education, healthcare, or cybersecurity.

However, generative AI systems also pose many risks and challenges, both technical and ethical, that need to be addressed and mitigated by the organizations that use them. Some of the key dangers for organizations that over rely on generative AI systems are:

• Hallucinations: Generative AI systems may produce outputs that are inaccurate, misleading, or nonsensical, due to errors, noise, or biases in the data or the model. These outputs may cause confusion, harm, or liability for the organization or its customers if they are not detected and corrected.
• Deepfakes: Generative AI systems may produce outputs that are realistic but fake, such as manipulated images, videos, or audio of people or events. These outputs may be used for malicious purposes, such as spreading misinformation, impersonating identities, or compromising security.
• Data privacy: Generative AI systems may require access to large amounts of personal or sensitive data to train or generate outputs. This data may be subject to legal or ethical obligations of protection and consent. The organization may face risks of data breaches, identity theft, or regulatory violations if it does not secure and manage the data properly.
• Copyright issues: Generative AI systems may produce outputs that are similar or identical to existing works of art, literature, music, or code. These outputs may infringe on the intellectual property rights of the original creators or owners. The organization may face risks of lawsuits, fines, or reputational damage if it does not respect and acknowledge the sources and licenses of the data or the outputs.
• Cybersecurity problems: Generative AI systems may be vulnerable to cyberattacks, such as hacking, tampering, or poisoning. These attacks may compromise the integrity, availability, or confidentiality of the data or the outputs. The organization may face risks of operational disruption, financial loss, or customer harm if it does not implement adequate security measures and controls.
• Poor development process: Generative AI systems may be developed without following best practices or standards of quality, reliability, transparency, or accountability. The organization may face risks of poor performance, errors, failures, or unintended consequences if it does not adopt a rigorous and ethical development process.

Therefore, any of these dangers could be a valid answer to the question. However, if only one answer can be chosen, then option D. Generative AI systems will start to run these organizations with little to no human oversight might be the most suitable answer, as it reflects a possible scenario where the organization loses control and governance over its generative AI systems and their impacts.

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