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

What happens when a conversation exceeds an AI's context window limit?

The AI stores the overflow in external memory and retrieves it when needed The AI loses access to text that falls outside the window — it effectively 'forgets' earlier parts of the conversation and may give inconsistent responses Exceeding the context window triggers an automatic upgrade to a larger model The AI stops responding and requires a new conversation to be started

Which of the following describes a realistic and high-value use of AI in 2026?

Using AI to produce a first draft of a client proposal, then editing it with domain knowledge and relationship context the AI doesn't have Using AI to make final legal or medical decisions without a professional reviewing them Using AI to replace all written communication with a client without any human involvement Delegating an entire client project to an AI agent with no human review of outputs

What does the Gartner Hype Cycle predict about technologies that go through a 'trough of disillusionment'?

The Hype Cycle predicts AI will be replaced by a completely different technology by 2027 Most eventually reach a 'plateau of productivity' where real, consistent value is delivered — the trough represents reality calibration, not permanent failure Technologies that enter the trough of disillusionment never recover and should be abandoned The trough of disillusionment only applies to hardware technologies, not software like AI

How did the relationship between users and AI change with generative AI tools like ChatGPT?

Users became more passive — generative AI automates everything without requiring input Users shifted from passive recipients of AI decisions (algorithms deciding what you see) to active operators directing AI to produce content and analysis on their behalf Users lost control — AI now makes all decisions without user input The relationship didn't change — generative AI works the same way as recommendation algorithms

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

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 The name is misleading because AI is more intelligent than humans in every domain AI is misleading because the system is not artificial — it uses real human data

What fundamentally changed about AI in late 2022 with ChatGPT's release, compared to AI that existed before?

ChatGPT was the first AI to run on computers; previous AI required specialized hardware The 2022 breakthrough was AI becoming conscious and able to truly understand language Generative AI crossed a quality and accessibility threshold — anyone could use it for genuinely useful work, without technical expertise, for the first time AI was invented in 2022 — there was no meaningful AI before ChatGPT

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

Wait until AI tools become more mature and reliable before starting to use them Try every major AI tool simultaneously to quickly determine which is best 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 Take a certification course before using any AI tool in a professional context

Which of these everyday products uses machine learning or AI?

A standard calculator — it follows fixed mathematical rules with no learning A basic alarm clock — it does only what it's explicitly programmed to do A physical thermostat with a timer — it executes pre-set rules without learning Netflix's recommendation engine — it uses machine learning to predict what content you'll enjoy based on your viewing patterns

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

A specific AI product designed for therapists and mental health professionals Using AI to make decisions for you when you're uncertain what to do 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

Even the most capable AI models in 2026 cannot do which of the following?

Reliably verify whether their own output is factually correct — models can produce false information with the same confidence as true information Produce grammatically correct text in English Write code that executes correctly in common programming languages Summarize a long document into key bullet points

Why does an AI model perform better on common tasks than on rare or highly specialized knowledge?

Common tasks appear more frequently in training data, so the model has seen more examples to learn from — rare or specialized topics have fewer training examples, increasing error and hallucination risk AI models are intentionally limited on specialized topics to avoid replacing experts Common tasks are hard-coded into AI models; rare tasks require internet access Rare topics require more parameters, and models have a fixed number available

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

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

What is the transformer architecture, and why does it matter for modern AI?

A type of electrical transformer that powers AI data centers more efficiently A 2017 research breakthrough that enabled models to track how words relate across long text — making it possible to train AI on vast amounts of text at a scale that produces today's LLMs A programming language used to build ChatGPT and similar AI products A hardware chip designed specifically for Google's AI research

When would you want a LOWER temperature setting for an AI task vs. a HIGHER temperature?

Temperature controls language formality: low for formal writing, high for casual writing Higher temperature always produces better quality — you should maximize it for all tasks Lower for precise tasks (data extraction, code, factual answers) where consistency matters; higher for creative tasks (brainstorming, varied options, creative writing) where variation is desirable Temperature only affects response speed, not content — lower is faster, higher is slower

What usage pattern consistently predicts high-value AI adoption?

Starting with a specific, recurring real problem; using AI for first drafts with human review; building task-specific prompting habits; knowing which tasks to keep fully human Using AI to replace human involvement in all written tasks entirely Waiting for AI tools to mature further before integrating them into real workflows Trying every new AI tool as soon as it launches to stay current

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

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

After completing AI Basics, what is the recommended next course in the AI Readiness curriculum?

AI Landscape Essentials — which builds on this foundation to cover specific AI models, their capabilities, and how to choose between them for different use cases The AI Economy course — which focuses on macroeconomic trends and is best taken after building practical AI skills The Vibe Coding Economy course — which is the advanced technical course and assumes significant AI experience There is no recommended next step — AI Basics is a standalone course with no further progression

What is 'hallucination' in the context of AI?

When AI becomes confused and stops responding to questions Hallucination is a technical term for when AI models become overloaded and crash When AI produces visual hallucinations or images instead of text When AI generates plausible-sounding but factually incorrect information — because the model predicts likely text, not verified facts

What is a 'token' in the context of AI language models?

A security credential required to access AI APIs A cryptocurrency used to pay for AI model usage A single character of text — AI processes text one character at a time A unit of text roughly corresponding to a word or word fragment — the basic unit AI models use to process and generate language, and how usage and pricing are measured

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

Build a logical reasoning engine that can prove mathematical theorems Predict what word (token) comes next, given all the words before it — repeated billions of times across vast text to build pattern knowledge 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