W1 AI

Q1: What is Artificial Intelligence (AI)?

A: Computer systems that perform tasks requiring human-like intelligence such as learning, adapting, and decision-making.

Q2: What makes AI different from traditional software?

A: Traditional software follows fixed rules; AI learns from data and improves over time.

Q3: Why must business students study AI?

A: AI affects all industries, improves decisions, increases efficiency, and introduces ethical and legal risks managers must understand.

Q4: What are the 3 learning stages of the course?

A: Understand AI, Apply AI, Analyze risks and ethics.

Q5: What is the technical definition of AI?

A: Systems that perform tasks that normally require human intelligence.

Q6: What is the business definition of AI?

A: Technologies that enable machines to sense, comprehend, act, and learn.

Q7: What is the popular definition of AI?

A: Smart machines that think and act like humans.

Q8: What is the regulatory definition of AI?

A: A machine-based system operating with varying levels of autonomy.

Q9: What is the core ability of AI?

A: Learning from data and improving performance.

Q10: Is AI smarter than humans?

A: No. AI today is narrow and specialized.

Q11: Are AI systems unbiased?

A: No. AI can inherit human bias from data.

Q12: Will AI replace all human jobs?

A: No. Jobs will change; collaboration is key.

Q13: Does AI require massive resources?

A: Not always. Cloud and no-code tools make AI accessible.

Q14: What are human strengths compared to AI?

A: Creativity, emotions, context, common sense, adaptability.

Q15: What are AI strengths compared to humans?

A: Speed, processing large data, consistency, pattern recognition.

Q16: List AI business opportunities.

A: Efficiency, automation, personalization, better decisions, innovation.

Q17: What are AI limitations?

A: Data dependency, bias risk, struggles with context, requires maintenance.

Q18: What is Narrow AI (ANI)?

A: AI designed for one specific task.

Q19: What is General AI (AGI)?

A: Future AI with human-level intelligence across tasks.

Q20: What is Artificial Superintelligence (ASI)?

A: Theoretical AI beyond human intelligence.

Q21: What is Step 1 of the AI process?

A: Data input.

Q22: What is Step 2 of the AI process?

A: Feature extraction.

Q23: What is Step 3 of the AI process?

A: Pattern detection.

Q24: What is Step 4 of the AI process?

A: Apply patterns to make predictions.

Q25: What happens at Automation Level 1?

A: AI analyzes; humans decide.

Q26: What happens at Automation Level 2?

A: AI recommends; humans approve.

Q27: What happens at Automation Level 3?

A: AI decides within rules; humans handle exceptions.

Q28: What happens at Automation Level 4?

A: AI operates autonomously; humans oversee.

Q29: What is Data in AI?

A: Raw material AI learns from.

Q30: What are Algorithms?

A: Methods that find patterns.

Q31: What is a Model?

A: Trained system ready to predict.

Q32: What is a Feedback Loop?

A: New data improves the model.

Q33: Why was the AI perception challenge done?

A: To challenge beliefs and separate hype from reality.

Q34: “AI will replace most jobs.” Reality?

A: Debate topic; AI changes jobs more than eliminates all.

Q35: “AI can think like humans.” Reality?

A: No. AI processes patterns but lacks real understanding.

Q36: “AI is only for tech companies.” Reality?

A: False. AI is used across industries.

Q37: “AI decisions are always objective.” Reality?

A: False. Bias can exist.

Q38: “AI requires massive data.” Reality?

A: Helpful but modern tools reduce the need.

Q39: Who is better at recognizing faces?

A: AI.

Q40: Who is better at understanding sarcasm?

A: Humans.

Q41: Who is better at chess?

A: AI.

Q42: Who is better at showing empathy?

A: Humans.

Q43: Who is better at processing 1 million data points?

A: AI.

Q44: Who is better at creative problem-solving?

A: Humans.

Q45: What makes the advising system “AI”?

A: It learns from student data and makes predictions.

Q46: What type of AI fits advising systems?

A: Narrow AI.

Q47: What is the human role in advising AI?

A: Oversight, ethics, approvals, handling exceptions.

Q48: Explain the AI factory analogy.

A: Data = input, Algorithms = machines, Models = output.

Q49: What balance must businesses maintain?

A: Opportunity vs risk.

Q50: Final mindset toward AI?

A: AI is a practical tool used responsibly with human collaboration.