The Idea
Career anxiety about AI is real and often poorly handled — either “don’t worry, everything will be fine” or “everything is going to be automated.” Neither serves teenagers who are actually trying to plan their lives.
This activity grounds the conversation in data: what has actually happened when technology transformed work in the past, and what specific patterns can we observe? Then it uses those patterns to make concrete, reasoned predictions — not speculation.
Part 1: Research (15 minutes)
Each participant researches 3–5 jobs that didn’t exist (or barely existed) in 2010–2015 and are now established careers.
A starter list to research and expand:
- Prompt engineer
- AI trainer / data annotator
- Social media manager
- Podcast producer
- App developer
- UX designer
- Cloud solutions architect
- Drone operator / drone data analyst
- Sustainability consultant
- Creator economy manager (helping YouTubers/influencers run their businesses)
- Cybersecurity analyst (this existed but has grown enormously)
- Climate risk analyst
- Content moderator
- Remote work facilitator
- Electric vehicle infrastructure specialist
For each job, note:
- What it involves (2–3 sentences)
- What technology enabled it
- What human skills are central (beyond just technical skill)
- Approximate salary range in your country
- Whether it requires a traditional degree
Part 2: Pattern Finding (10 minutes)
Put all the researched jobs on sticky notes and arrange them on a big piece of paper. Then look for patterns:
Common patterns in new jobs:
- Technology requires human oversight. AI training, content moderation, drone operations — someone has to supervise and correct the machine.
- New technology creates new communication needs. Every new platform or tool needs people who can explain it, design it, and help others use it.
- New technology creates new ethical and legal needs. Privacy law, AI ethics, cybersecurity — these fields grow when technology creates new risks.
- Complexity requires integration specialists. When many complex systems exist, people who can connect them become valuable.
- Human-facing roles resist automation hardest. Healthcare navigation, elder care, education, therapy — work that requires genuine human relationship.
Draw circles around clusters that share patterns. Name each cluster.
Part 3: Predictions (10 minutes)
Now look at technologies that are just emerging or becoming significant in 2024–2025. For each, use the patterns to predict what new jobs will emerge.
Technologies to consider:
- Advanced AI assistants becoming standard tools
- Gene editing and synthetic biology becoming more accessible
- Augmented and virtual reality maturing
- Autonomous vehicles becoming more common
- Climate response becoming a major economic sector
- Quantum computing beginning to have practical applications
Prediction template: “Because [technology] is emerging, there will be demand for people who [specific role]. This requires human skills including [skills]. It will be hard to automate because [reason].”
Write each prediction on a sticky note of the second color.
Example prediction: “Because AI systems are making consequential decisions in healthcare, hiring, and law, there will be demand for AI auditors who can evaluate whether AI systems are working fairly and accurately. This requires human judgment, ethics reasoning, and domain expertise. It’s hard to automate because you need human accountability for human-affecting decisions.”
Part 4: The Skills Audit
Look at the jobs researched and the jobs predicted. Make a list of the human skills that appear most often — across the most jobs, in the most valuable roles.
These are likely to include:
- Communication (translating between technical and non-technical)
- Ethical reasoning and judgment
- Creative synthesis (connecting ideas across domains)
- Project management under ambiguity
- Teaching and explanation
- Human relationship and trust-building
- Critical evaluation of information and AI output
Now ask: “Which of these skills are you actively developing? Which aren’t you developing?”
This is not a guilt question — it’s a planning question. If the most automation-resistant skills are listed here, these are worth deliberate investment.
Closing Reflection
Write individually, then discuss:
- “What surprised me most about what I found.”
- “One skill I want to develop more deliberately.”
- “One job I found that I’d actually like to do.”
- “My prediction for the single most important new job in the next 10 years.”
Optional: Return to this activity in 5 years and see which predictions came true.
The Honest Conversation
Some jobs will be eliminated by AI. This is real and worth acknowledging without panic. The question isn’t whether automation will happen — it’s how individuals can position themselves to be most adaptable.
The consistent finding from labor economists studying automation: tasks are automated, not jobs. A radiologist doesn’t disappear when AI can read scans — the job changes to focus on the cases that require judgment, the communication with patients, the integration of scan findings with full medical context. The demand for the job may decrease, the nature of the work will change, but the role of human judgment in high-stakes decisions remains.
This is both reassuring and demanding. Reassuring: there’s still a role for humans in most fields. Demanding: you have to be the part of the job that AI can’t do.