SERIES: The Future of Work in the AI Age

S4-S6 / Adult

60–90 minutes

Which Jobs Actually Change? Separating AI Hype From Real Data

AI-and-jobs headlines often jump from ‘AI can perform some tasks’ to ‘this career is disappearing’. The more useful way to think is at task level and to ask exactly what each study measured. You will compare occupations, examine workforce-report methods and create a briefing that replaces one oversimplified claim with a more accurate evidence-based […]

Which Jobs Actually Change? Separating AI Hype From Real Data

Your Mission

Separate AI-and-jobs headlines from what the evidence actually measures.

You will break jobs into tasks, compare occupations with different exposure and investigate why credible workforce reports can produce different-looking conclusions.

The Shape of This Challenge

Discover

✏️ ️ Notice & question

Explore

️ Investigate & test

Create

✏️ Make & communicate

Reflect

️ Think & apply

Discover

Start by treating every job as a bundle of tasks.

Step 1

Jobs Are Bundles of Tasks

️ Break it apart · 8–10 mins

We are learning to analyse a job at task level rather than treating the whole occupation as automatable or safe.

AI rarely changes every part of a role equally. A single job can contain writing, physical work, judgement, customer interaction, coordination and accountability.

Your Task

Choose one familiar job.
List at least eight real tasks performed in that role.
Sort each task into easy to assist with AI, possible but needs checking or hard to automate well.
Write one sentence explaining why the job title alone hides important detail.

I can break a job into tasks and explain why exposure varies within one occupation.

→ This gives you the task-level model for judging workforce change.

ResearchCritical ThinkingAI Literacy

Step 2

Exposure Is Not the Same as Job Loss

✏️ Concept check · 8–10 mins

We are learning to distinguish AI task exposure from replacement, productivity and employment outcomes.

A study showing that AI can affect many tasks does not automatically mean the entire job disappears.

Your Task

Write four headings: Exposure, Augmentation, Automation, Employment outcome.
Write a one-sentence definition for each.
Create one example where high task exposure could increase productivity without removing the job.
Create one example where automation could reduce the number of people needed.

I can explain why task exposure and job loss are related but not interchangeable ideas.

→ This prevents headline claims from becoming your conclusion.

Critical ThinkingCommunicationAI Literacy

Explore

Use current evidence and examine the method behind the numbers.

Step 3

Compare a High-Exposure and Low-Exposure Role

Choose your route · 12–18 mins

We are learning to use real evidence to explain why AI affects different occupations differently.

Look for the mechanism behind the gap: digital information, physical environment, judgement, accountability, social interaction or another factor.

Your Task

Choose two occupations with noticeably different AI exposure.
Complete one research route.
Compare at least five tasks across the two roles.
Identify the strongest reason the exposure differs.

⚡ Quick Track

Use one credible task-exposure or labour-market source plus official occupation descriptions. Compare five tasks and explain the main pattern.

Dig Deeper

Use two independent AI-workforce sources with different methods. Compare what each measures, then explain why their results may differ without assuming one must be wrong.

I can use current evidence and task analysis to compare AI exposure across jobs.

→ This becomes the evidence core of your final briefing.

ResearchCritical ThinkingInformation Evaluation

Step 4

Why Do Credible Forecasts Disagree?

️ Method audit · 10–12 mins

We are learning to evaluate workforce claims by looking at method, timeframe and what is being measured.

Reports can all be credible while answering different questions: technical capability, task use, employer intentions, productivity, job creation or job displacement.

Your Task

Choose two credible reports with different-looking conclusions.
Record the publication date, geography, timeframe and unit of measurement.
Write the main question each report is actually answering.
Explain one reason the headlines can sound contradictory even when the evidence is not.

I can compare workforce forecasts by method rather than only by headline.

→ This gives your final myth-versus-reality briefing appropriate context.

ResearchCritical ThinkingMedia Literacy

Create & Share

Create a myth-versus-reality briefing grounded in task-level evidence.

Step 5

Create an AI Jobs Myth-vs-Reality Briefing

✏️ Analyse · Create · 25–35 mins

We are learning to correct an oversimplified AI-and-jobs claim using task-level evidence.

Choose a claim such as ‘AI will replace programmers’, ‘manual jobs are safe’ or another industry-specific statement. Your job is to make it more accurate, not simply more optimistic or pessimistic.

Your Task

State the oversimplified claim.
Use at least two credible sources with publication dates.
Include one task-level comparison.
Distinguish exposure, augmentation and possible employment effects.
Choose one output below.

Myth-vs-Reality Brief

1 page · 280–350 words

⏱ 25–30 mins

Correct one AI-and-jobs claim with task evidence, source comparison and a balanced conclusion.

Jobs Under the Microscope

4 slides · maximum 30 words per slide

⏱ 30–35 mins

Show the claim, task comparison, evidence differences and your corrected version.

AI Jobs: What the Data Actually Says

90 seconds final runtime

⏱ 30–35 mins

Explain one common claim and what task-level evidence adds to the story.

I can create a sourced briefing that separates evidence from interpretation.

→ This is your finished mission output.

ResearchCritical ThinkingCommunication

Step 6

Reflect, Apply, Look Forward

️ Think or discuss · 5–8 mins

We are learning to reflect on how better measurement changes career decisions.

The next challenge asks a different question: if tasks change, which human skills remain valuable across many roles?

Your Task

Answer the prompts.
Name one AI-workforce claim you would now question differently.
Choose one job you want to investigate for durable skills next.

Reflect

Which distinction — exposure, augmentation, automation or employment — mattered most?

Apply

How could task-level thinking help you choose what to learn next?

Look Forward

What new data would make AI workforce forecasts more useful five years from now?

I can explain why task-level evidence is more useful than blanket predictions about whole occupations.

→ You now have the evidence habits needed to investigate durable skills.

ReflectionCritical ThinkingResearch

Dex AI Study Partner

Hi! I'm Dex, your AI Study Partner. Ask me a question, attach a screenshot, test your skills with Quiz, or click Mastery for feedback!

Screenshot attached

TOOLKIT

Choose Your Tools

Use current sources where possible. AI and labour-market evidence changes quickly, so record publication dates and distinguish forecasts from observed data.

Evidence

Use at least two credible current sources such as labour-market reports, occupation/task databases, employer research or published AI-usage studies. Note publication date and method.

Compare

Break jobs into tasks rather than treating a job title as one indivisible activity. Record where AI assists, changes, automates or has little effect.

Create

Use a one-page briefing, 4-slide explainer or 90-second evidence-based video.

Educator / Parent Notes

Age, Stage and Prior Learning: Designed for S4–S6 and adults. Learners should be comfortable comparing sources and distinguishing measured data from predictions.

Before You Start: Use current reports or teacher-provided extracts. Avoid presenting one exposure index as a definitive forecast of job losses.

How to Open This: Put two contradictory-looking AI jobs headlines on screen and ask: “What would we need to know before deciding which is right?”

Scheduling: Steps 1–4 need around 40–50 minutes. Step 5 needs 25–35 minutes.

If a Pupil Gets Stuck: Provide two occupations, one exposure source and a task table. Focus on five tasks rather than a full report comparison.

For Fast Finishers: Ask learners to compare two studies with different methodologies and explain which career question each is better suited to answer.

Marking Guidance: Look for task-level reasoning, careful use of terms, current dated sources, method awareness and a conclusion that separates evidence from interpretation.

Which Jobs Actually Change? Separating AI Hype From Real Data

Which Jobs Actually Change? Separating AI Hype From Real Data

Discover

Jobs Are Bundles of Tasks

Exposure Is Not the Same as Job Loss

Explore

Compare a High-Exposure and Low-Exposure Role

Why Do Credible Forecasts Disagree?

Create & Share

Create an AI Jobs Myth-vs-Reality Briefing

Reflect, Apply, Look Forward

Show What You Have Learned

Evidence

Compare

Create

Show What You Have Learned

Evidence

Compare

Create

TOOLKIT

Evidence

Compare

Create

Educator / Parent Notes

More like this

LET'S TALK DIGITIZE