AI Economy Quiz: How Ready Are You for the Transformation Ahead?

A company uses AI to screen resumes and notice that the tool systematically ranks candidates from certain universities higher. What is the most likely cause?

There is no cause — AI resume screening is required to be unbiased by design The university ranking reflects the AI's access to university prestige databases The AI was trained on historical hiring data where those universities were over-represented among successful hires — encoding past selection bias The AI is correctly identifying the objectively better universities

Why is the 'care economy' (healthcare aides, childcare, social work) particularly resilient to AI displacement?

Care economy workers earn too little for automation to make economic sense Physical presence and human relationship are the core service delivery mechanism — the human attending to another human IS the product, which no remote AI can substitute AI models are not capable of processing information in healthcare contexts Care economy roles are protected by regulation that prevents any AI use

Why is maintaining deep domain expertise emphasized alongside developing AI fluency, rather than prioritizing one over the other?

AI fluency without domain expertise produces volume without quality; domain expertise without AI fluency loses productivity to AI-augmented competitors. The combination — T-shaped AI-fluent experts — produces the highest-quality output at scale Domain expertise is no longer valuable once AI can perform most knowledge work tasks Only AI engineers need domain expertise; most professionals only need basic AI tool fluency AI fluency is sufficient — domain expertise is what AI provides from its training data

Why are skilled trades like electricians and plumbers considered AI-resilient occupations?

Skilled trades are fully automated but workers are still needed to supervise the machines AI models already work as plumbers and electricians in smart homes Skilled trades require no judgment and are therefore not worth automating They require physical dexterity in variable, unpredictable physical environments — something current AI cannot perform — and industry aging plus declining new entrants is creating wage-driving shortages

What does 'labor market polarization' or 'hollowing out' refer to in the context of AI?

All manual labor becomes higher-paid as AI takes over cognitive work AI causes rural labor markets to 'hollow out' as work becomes geographically concentrated in tech hubs AI causes job losses at all skill levels equally, regardless of task type High-skill and low-skill roles grow while middle-skill routine cognitive jobs shrink — creating an 'hourglass' labor market with fewer middle-income paths

Which statement about AI API output tokens is correct?

Output tokens are not counted toward API costs at the Sonnet/GPT-4o tier Output tokens are typically more expensive per token than input tokens Input and output tokens are always priced identically at major providers Output tokens are always cheaper because the model is just retrieving stored answers

A consultant generates proposals manually, which takes 3 hours each. They close 30% of proposals. What is the most direct AI impact opportunity?

Use AI to generate first-draft proposals from a project brief, reducing the 3-hour task to 1 hour of review and customization — enabling more proposals at the same time investment Use AI to automatically send proposals without owner review to maximize volume Use AI to increase the proposal price to improve ROI per proposal Use AI to find and pitch leads, bypassing the proposal stage

According to the 90-day learning approach, what should be the focus in the FIRST 30 days of building AI skills?

Build AI fluency within your current role by using AI for 3 tasks you currently do manually and establishing consistent prompting habits Spend the first month evaluating AI tools without committing to using any yet Immediately start building an automation that replaces your entire workflow Complete a full AI tools certification course before using any AI in your actual work

Why is AI's current impact on labor markets historically unprecedented compared to the computerization era?

AI affects only manufacturing; previous technologies affected only service work Computerization actually increased employment in all categories; AI is uniquely destructive For the first time, automation significantly affects knowledge workers — lawyers, doctors, writers, analysts — whereas previous technologies primarily affected manual and routine tasks, leaving white-collar work largely untouched Previous technologies never displaced any workers; AI is the first to do so

What is the EU AI Act's 'high risk' category, and what does it require?

High-risk AI systems (used in hiring, credit, healthcare, and critical infrastructure) must meet strict requirements for transparency, human oversight, accuracy, and safety before deployment High-risk AI is banned outright in the EU — organizations cannot use AI in these domains The EU AI Act's high-risk category only applies to AI systems built in Europe, not imported High-risk AI systems require approval from the AI system's provider but no additional organizational obligations

A restaurant receives 20 new Google Reviews per week. Responding to all of them takes too much time. What is the best AI-assisted approach?

Use AI to generate personalized response drafts for each review that the owner quickly reviews and publishes Respond only to negative reviews — positive reviews don't need responses Consolidate all responses into one weekly post Use AI to respond automatically to all reviews without any human review

A solo accountant wants to implement an AI chatbot on their website. Which capability is MOST appropriate to implement first?

Processing client payments and scheduling automatically without human review Autonomous tax advice for website visitors FAQ response — answering common questions about services, pricing, and availability to handle basic inquiries 24/7 Automated client onboarding that collects financial documents

For a worker in a high AI substitution risk role, what is the most effective adaptation strategy?

Advocate for regulation that bans AI in your industry Upskill into adjacent roles with more human judgment content — a data entry clerk learning SQL and data analysis moves into an AI-augmented growth role rather than a declining substituted one Specialize more deeply in the exact tasks AI is replacing to become the best human doing those tasks Avoid using AI tools entirely so that your role remains necessary

What is meant by 'distributional tension' in the context of AI economic gains?

AI companies are required to distribute profits to all affected workers AI creates equal productivity gains for all workers regardless of skill level Distributional tension refers to AI models that provide uneven answer quality AI productivity gains are initially concentrated among AI company shareholders and skilled tech workers, raising concerns about inequality before benefits spread broadly

Which AI capability allows a small business to maximize the reach of a single piece of content?

Using AI to automatically post the same content to all platforms simultaneously AI translating content into multiple languages automatically Having AI scrape competitor content and rewrite it Using AI to repurpose one piece of content into multiple formats — blog to social posts, email, FAQ, LinkedIn article

A small e-commerce store has 200 products but no descriptions written yet. What is the most efficient AI-assisted workflow?

Use AI to write descriptions but publish them without any human review Hire a copywriter first since AI cannot write e-commerce product descriptions Create a template prompt with product name, category, key features, and target customer, then batch-process all 200 products through an AI writing tool Write one product description manually and ask AI to copy it for all other products

Why does the T-shaped model predict that deep domain expertise becomes MORE valuable in an AI era, not less?

AI output quality depends on expert direction and validation — an AI model plus an expert produces better results than AI alone. Experts who add AI fluency multiply their output without diminishing their expertise premium Deep domain experts can resist using AI tools and still maintain their advantage over AI-augmented generalists AI only affects surface-level knowledge work; deep expertise is in a completely separate category Domain expertise becomes less valuable because AI can replicate expert knowledge from training data

A bakery owner wants to post daily on Instagram and send a weekly email newsletter but has no time to write content. What is the most practical AI solution?

Wait for platform-native AI tools directly in Instagram Use AI (ChatGPT or Jasper) to generate captions and email drafts from brief descriptions of weekly specials, saving hours of writing each week Use AI to autonomously post to Instagram without any human review Hire a social media agency — AI is not ready for food business content

What is the difference between 'high AI exposure' and 'high substitution risk' for a role?

Substitution risk refers only to blue-collar roles; white-collar roles only face exposure High exposure means AI significantly affects the tasks in a role; it may complement the worker (boosting productivity) or substitute for them. Risk depends on whether AI augments or replaces the majority of tasks High exposure and high substitution risk mean the same thing High exposure always means high risk — any role AI touches is at risk of disappearing

According to research on AI initiative failure, what is the most common root cause?

Most AI projects fail because the AI models are inaccurate AI technology is still too immature to deliver on organizational promises Organizations usually choose the wrong AI vendor Change management and governance failures — not training users, not updating processes, and not establishing accountability — rather than the AI technology itself