Genrative AI

What does generative AI primarily do?

• Solve mathematical problems

• Generate content such as text, images, and audio

• Play video games

• Control robotic movements

What is one way to reduce bias in generative AI?

• Using biased training data

• Avoiding any form of data preprocessing

• Ensuring diverse and representative training datasets

• Ignoring bias issues

Why is transparency important in AI systems?

• To help users understand how decisions are made

• To make the systems more complex

• To keep the algorithms secret

• To improve system speed

How can AI systems protect user privacy?

• By sharing user data with third parties

• By storing data in plain text

• By ignoring privacy concerns

• By encrypting personal data

What should generative AI systems do to respect intellectual property?

• Copy content from other sources without permission

• Generate completely original content or use licensed content

• Ignore intellectual property laws

• Use any content found online

Who is typically held responsible for the actions of an AI system?

• The end-users

• No-users

• The AI system itself

• The developers and operators of the AI system

What is a key component of informed consent in AI?

• Using complex language to describe AI functionalities

• Avoiding any explanation about the AI system

• Clearly explaining the capabilities and limitations of the AI system

• Assuming users know about AI

How can the misuse of generative AI be controlled?

• By implementing strict usage policies and monitoring compliance

• By making AI models publicly available without restrictions

• By allowing anonymous access to AI systems

• By ignoring potential misuse

How can the environmental impact of AI be mitigated?

• By using more energy-intensive algorithms

• By running AI models continuously without consideration

• By ignoring environmental concerns

• By optimizing algorithms for efficiency and using renewable energy sources

What is the role of ethical guidelines in AI development?

• To make AI development more expensive

• To slow down AI innovation

• To ensure AI systems are developed and used responsibly

• To keep AI development secretive