Exercises: AI and Work

Part A: Foundational (Understand/Apply)

Exercise 10.1 — Task Decomposition Practice

Choose three of the following occupations and decompose each into at least six specific tasks. For each task, classify it as (a) routine/structured, (b) non-routine/pattern-based, or (c) non-routine/deeply contextual. Then estimate the percentage of work time spent on each task.

  • Elementary school teacher
  • Accountant
  • Restaurant server
  • Graphic designer
  • Real estate agent
  • Social worker

Exercise 10.2 — Historical Pattern Matching

For each of the following historical technologies, identify: (a) which jobs were most threatened, (b) which new jobs were created, and (c) how long the transition took.

  1. The automobile (replacing horse-drawn transportation)
  2. The spreadsheet software (replacing manual bookkeeping)
  3. The ATM (reducing need for bank tellers)

Based on these historical cases, what patterns do you notice that might apply to AI?

Exercise 10.3 — Vocabulary Application

Write a short paragraph (100–150 words) explaining the difference between automation and augmentation to a friend who doesn't take this course. Use a specific real-world example — not one from the textbook — to illustrate the distinction.

Exercise 10.4 — Identifying Algorithmic Management

List three services or products you use regularly where algorithmic management might affect the workers who provide them. For each one, describe at least one way the algorithm likely controls or monitors the workers involved.

Part B: Intermediate (Apply/Analyze)

Exercise 10.5 — Automation Exposure Analysis

Using data from a national labor statistics source (such as the U.S. Bureau of Labor Statistics or equivalent in your country), select five occupations with high employment numbers. For each:

  1. List the primary tasks associated with the role (most national databases describe "typical duties").
  2. Apply the task-based framework to assess automation exposure.
  3. Rank the five occupations from most exposed to least exposed.
  4. Identify which demographic groups are most represented in the highest-exposure occupations.

Exercise 10.6 — Augmentation Redesign

Choose an occupation that is commonly cited as "threatened by AI." Instead of arguing whether the job will disappear, redesign the role as a human-AI team. Specifically:

  1. Which tasks would the AI handle?
  2. Which tasks would remain human?
  3. How would the human and AI interact — what's the "handoff" between them?
  4. What new skills would the human need?
  5. Would the redesigned role be a better or worse job for the worker? Why?

Exercise 10.7 — The Gig Worker's Perspective

Interview a gig economy worker (rideshare driver, food delivery worker, freelance platform worker) or read a detailed first-person account online. Write a 300–400 word analysis addressing:

  1. How does the algorithm assign and manage their work?
  2. What aspects of their work experience are controlled by the algorithm vs. their own judgment?
  3. Do they understand how the algorithm evaluates them?
  4. What changes would improve their experience without eliminating the benefits of the platform?

Exercise 10.8 — Claim Evaluation

Find a recent news article or opinion piece making a specific claim about AI and jobs (e.g., "AI will eliminate X million jobs by 20XX" or "AI will create more jobs than it destroys"). Evaluate the claim using the frameworks from this chapter:

  1. Does the claim distinguish between tasks and jobs?
  2. Does it consider both automation and augmentation?
  3. Does it address who is most affected?
  4. What evidence does it offer?
  5. What does it leave out?

Part C: Advanced (Evaluate/Create)

Exercise 10.9 — Policy Debate: Universal Basic Income

One proposed response to AI-driven job displacement is Universal Basic Income (UBI) — a government payment to all citizens regardless of employment status. Prepare a structured argument either for or against UBI as a response to AI automation. Your argument should:

  1. State your position clearly.
  2. Provide at least three supporting points with evidence or reasoning.
  3. Acknowledge at least two strong counterarguments and respond to them.
  4. Address the specific context of AI automation (not just UBI in general).

Then write a one-paragraph response from the opposing perspective.

Exercise 10.10 — Industry Impact Report

Select a specific industry (healthcare, legal services, education, manufacturing, creative arts, finance, retail, etc.) and write a 500–700 word analysis of AI's likely impact over the next decade. Your analysis should include:

  1. The current state of AI adoption in the industry.
  2. Which tasks are most likely to be automated, augmented, or unaffected.
  3. Which worker categories within the industry are most and least vulnerable.
  4. What new roles or skills the industry will likely need.
  5. What policies or organizational practices could support a just transition.

Exercise 10.11 — Designing a Just Transition

Imagine you are advising a city government. A major employer in the city — a large insurance processing center employing 2,000 people — has announced it will deploy AI systems that will reduce its workforce by 40% over the next three years. Design a just transition plan that addresses:

  1. Short-term support for displaced workers (0–6 months).
  2. Retraining and reskilling programs (6–24 months).
  3. Economic diversification strategies for the city (1–5 years).
  4. Funding mechanisms for the plan.
  5. Metrics for evaluating the plan's success.

Exercise 10.12 — Personal Career AI Strategy

Using the Self-Assessment framework from Section 10.6, create a personal AI career strategy document (500–700 words) that includes:

  1. Your current or intended occupation and its task decomposition.
  2. An honest assessment of which tasks are most exposed to AI automation.
  3. Your "last mile" — the tasks where you bring uniquely human value.
  4. Three specific actions you will take in the next 12 months to strengthen your position.
  5. Two things you would advocate for at the policy or organizational level.

Reflection Question

Think about a time when technology changed how you or someone you know does their work — even in a small way. Did the change feel like automation (replacing what they did), augmentation (making them better at what they did), or algorithmic management (controlling how they did it)? How did the person respond? What does that experience teach you about how people actually navigate technological change?