Understanding AI: Concepts and Ethics

What is artificial intelligence (AI)?

• A programming language for web development.

• A method for increasing computer speed.

• A type of computer hardware.

• Artificial intelligence (AI) is the simulation of human intelligence in machines.

Explain the difference between narrow AI and general AI.

• Narrow AI can perform any task a human can, while General AI is limited to specific tasks.

• General AI is designed for a single application, whereas Narrow AI can adapt to multiple tasks.

• Narrow AI is more advanced than General AI, as it can learn from fewer examples.

• Narrow AI is task-specific and limited, while General AI has the ability to understand and learn across various domains like a human.

How does machine learning relate to AI?

• AI does not involve data analysis.

• Machine learning is a type of hardware used in AI.

• Machine learning is a subset of AI that enables systems to learn from data.

• Machine learning is the same as AI.

What are some common applications of AI in everyday life?

• Common applications of AI in everyday life include virtual assistants, recommendation systems, chatbots, smart home devices, and navigation apps.

• Video editing software

• Social media management tools

• Online shopping platforms

Discuss one positive impact of AI on society.

• AI has no effect on education.

• AI increases unemployment rates.

• AI makes healthcare less accessible.

• AI positively impacts society by revolutionizing healthcare.

What is a potential negative impact of AI technology?

• Increased efficiency in all industries.

• Job displacement and increased unemployment.

• Improved job security and stability.

• Enhanced creativity and innovation.

How can AI influence job markets?

• AI only affects high-skilled jobs

• AI has no impact on job markets

• AI influences job markets by automating tasks, creating new job categories, and requiring new skills.

• AI eliminates all jobs completely

What ethical considerations should be taken into account when developing AI?

• Fairness, transparency, privacy, societal impact, safety, and human oversight.

• Data collection efficiency

• Profit maximization

• User engagement metrics

Why is transparency important in AI systems?

• Transparency is only necessary for government AI systems.

• Transparency is important in AI systems to ensure accountability, build trust, and facilitate understanding of decision-making processes.

• Transparency is irrelevant to user experience in AI.

• Transparency increases the complexity of AI algorithms.

What is bias in AI, and how can it affect outcomes?

• Bias in AI can lead to unfair outcomes, discrimination, and perpetuation of stereotypes.

• Bias in AI ensures equal treatment for all individuals.

• Bias in AI is a method to enhance decision-making accuracy.

• Bias in AI has no impact on the results produced by algorithms.