🌀 When AI Disrupts More Than Just Work
For many of us, AI didn’t arrive gently. It hit hard. Careers that felt solid started to wobble. Decades of dedication were suddenly up for debate. If you’re feeling that tension, you’re not alone.
This story doesn’t come from theory. It comes from personal upheaval—and choosing to explore the landscape anyway.
🔎 What I Learned When I Looked Closer
Instead of sitting with panic, I turned to research. Here’s what I found when I stepped into the AI annotation world.
🗺 Key Terms and Players
- Data Annotator – The human behind the labels that teach AI to “read” and “respond.”
- Third-party vendors – Companies like Scale AI, Appen, and TELUS that handle recruitment and project management.
- LLMs (Large Language Models) – AI systems like ChatGPT, Gemini, and Claude trained on huge datasets to simulate human language understanding.
🔧 Platforms I Explored
- Scale AI (OpenAI, Anthropic)
- Appen (Google, Nvidia)
- Outlier & e2f (smaller but responsive)
- TELUS International (frequent listings but variable support)
Some replied. Most didn’t. The onboarding process was real—and so were the trade-offs.
📌 The Reality Behind the Buzz
Here’s what the work involved:
- Long training periods, often unpaid or paid at partial rates
- Highly repetitive tasks with narrow margins for error
- Ongoing assessments, daily feedback loops (including weekends)
- Project eligibility often based on location or cultural fit
- Pay that rarely reflects the effort, especially at entry level
There were moments of interest—especially crafting prompts or evaluating AI-generated content. But sustainable? For me, no.
🎯 Is This a Path for You?
Annotation can be a useful experience if you:
- Are new to the language industry and exploring adjacent fields
- Want to understand how AI systems learn
- Have flexible hours and need side income
- Don’t rely on it as your main source of professional growth
It’s not creative. It’s not strategic. But it might give you insight, tech fluency, or even a pivot point—depending on your goals.
🔁 What I Took Away (That Was Worth It)
I didn’t find a new career—but I found:
- Clarity about what I need from my work
- Context for how AI is built and where we fit in
- Confidence that adapting doesn’t mean abandoning who I am
Sometimes, the best thing a challenging experience can give you is perspective.
✍️ Mentoring Prompts
- What do you actually want from your relationship with AI?
- Could annotation be a temporary bridge while you build something else?
- Are you prepared to separate hype from real-world workflows and rates?
Not all experiments lead to reinvention—but they can lead to grounded choices.
💬 Final Note from Romina
AI isn’t the end of your path. It’s a new terrain you can choose to explore—or not. You decide how your words serve the future. You still hold the pen. That matters more than ever.
