RESEARCH / TRANSPARENCY
Source selection & update policy
How sources are chosen, what each source can support and when career pages are reviewed or corrected.
No single dataset can describe how AI changes every job. Offline Observer combines global exposure research, occupational task data, official employment projections and observed AI-use research while keeping their limits visible.
What is changing
- Primary and official sources first
- Task evidence separated from forecasts
- Material changes receive a review date
Where people still lead
- Sources can disagree
- US data is not a global forecast
- Vendor usage data is not the whole labor market
What to build next
- Review core sources at least yearly
- Replace broken or superseded links
- Publish corrections that change interpretation
Keep moving with a useful next step.
Move from this signal to the industry, skill or tool that helps you act on it.
Methodology
How Offline Observer turns task-level evidence into a career signal without pretending to predict layoffs.
→02 / Career tools
AI task exposure map
Separate the tasks AI can accelerate from the judgment, trust and physical work that still need you.
→03 / Skills to build
Data literacy for AI work
Understand where data came from, what a metric leaves out and when a confident pattern is misleading.
→04 / Industry outlooks
Healthcare
Documentation and decision support change quickly, but safety, regulation, trust and physical care limit unattended automation.
→05 / Industry outlooks
Finance & insurance
Analysis and operations accelerate, while controls, auditability, regulation and customer trust determine safe scale.
→06 / Industry outlooks
Education
Planning, practice and feedback can scale, while motivation, safeguarding and adaptive instruction remain human-centered.
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