AI Basics Quiz: What Do You Actually Know About AI?

A lawyer asks an AI for case citations supporting a specific legal argument. What is the risk, and what should they do?

High hallucination risk — AI may generate convincing-looking but nonexistent case citations. Every citation must be verified in a legal database before use The risk is low if the AI is asked to cite recent cases from 2024 or later The risk is only if the lawyer is in a jurisdiction not covered by US law training data There is no risk — AI was trained on legal databases and citations are reliably accurate

What is the '80/20 trap' in AI adoption?

AI can only be used for 20% of any professional's tasks; 80% must remain fully human AI tools cost 80% more than traditional software and deliver only 20% of the value Only 20% of AI tools are reliable; 80% are experimental and should not be used at work AI handles 80% of a task well but fails at the remaining 20% in ways requiring human correction — making autonomous completion risky, but AI-assisted draft work highly valuable

What is the key difference between 'narrow AI' and 'general-purpose AI'?

Narrow AI runs on phones; general-purpose AI requires large servers Narrow AI is for small companies; general-purpose AI is only for enterprise use Narrow AI is cheaper; general-purpose AI is always more expensive per use Narrow AI is designed for one specific task (spam filtering, recommendations); general-purpose AI handles many different tasks through a single model that users direct with language

What made ChatGPT feel fundamentally different from previous AI products like Siri or Alexa?

ChatGPT was the first AI to use the internet in real time to answer questions ChatGPT was different because it ran on quantum computers unavailable to earlier AI ChatGPT was a general-purpose system — one interface could write, analyze, code, and answer questions across any domain, unlike assistants built for narrow command-response tasks ChatGPT was the first AI ever to understand English language

What is the 'thinking partner' use case for AI?

Using AI to make decisions for you when you're uncertain what to do A specific AI product designed for therapists and mental health professionals Asking AI to agree with your existing conclusion to build confidence before a presentation Using AI to stress-test plans, identify weaknesses in arguments, and explore a decision from multiple angles — not for the answer, but to sharpen your own thinking

Which of the three habits of effective AI users is most important for working with AI in a professional context?

Delegating final decisions to AI to remove human bias from the process Keeping the judgment — AI generates options and drafts; the human remains accountable for decisions and final outputs Using AI for every task, no matter how simple, to build maximum fluency Never verifying AI output to avoid slowing down the productivity gains

Why is 'Artificial Intelligence' considered a misleading name by many researchers?

AI is misleading because the system is not artificial — it uses real human data The name is misleading because AI is more intelligent than humans in every domain AI systems don't think or understand — they perform sophisticated pattern recognition and statistical prediction, which produces human-seeming outputs without human-like comprehension There is no controversy about the name — it accurately describes how the systems work

What is the recommended approach when starting with AI tools for the first time?

Try every major AI tool simultaneously to quickly determine which is best Wait until AI tools become more mature and reliable before starting to use them Take a certification course before using any AI tool in a professional context Pick one tool and use it consistently on real work for 30 days, building habits through hands-on experimentation rather than reading about AI or switching between tools

What is the core training objective of a large language model?

Predict what word (token) comes next, given all the words before it — repeated billions of times across vast text to build pattern knowledge Build a logical reasoning engine that can prove mathematical theorems Memorize every fact in its training data so it can retrieve them accurately Create a database of question-answer pairs to look up when asked something

For which type of task would AI hallucination risk be LOWEST?

Brainstorming a list of marketing tagline ideas — there are no 'correct' facts to get wrong; creativity and fluency are the objective Looking up the exact revenue of a private company last quarter Describing a competitor's product features from their latest press release Finding the specific statute number of a regulation passed in 2025