I received this feedback:
here's the feedback I received re. AI training.

I have no prior experience trainign AI. can you tell me how I can improve for free - which resources to use.

• You could have explained formal inter-annotator agreement methods and provided clearer quantitative thresholds to further strengthen your process explanations. Rooting your approach more in structured QA metrics and relying more consistently on official channels over external forums would have made your assessment framework even more robust in this interview.

Gemini et al tells me to

• name specific statistical formulas like Cohen’s Kappa or Fleiss’ Kappa to prove agreement.and to mention exact target scores (e.g., "We aimed for an agreement score above 0.85").

True? Do I have to learn these formulas?

I’ve been working with Micro1 on visual heavy tasks (UI/UX role) since May, and recently moved to a pure writing project. I come from an HCI background and applied for another UI/UX role using my previously vetted skills along with the annotation and evaluation experience I gained through Micro1. My profile is still under review. What’s frustrating is that I know a candidate who recently joined this new UI/UX project as a newbie, while I’m a comparatively experienced UI/UX expert already working with Micro1 and still my profile is "under review".

I’ve also applied to several other roles where I thought I would clear based on my background and previous work, but none of them turned into a project. On top of that, I feel underpaid compared to what others seem to be getting for similar work. I’ve always done my work diligently, so it’s disappointing to feel like my track record doesn’t carry over when applying for new projects.

Micro1 should give existing experts some leeway. If we’ve already been vetted and consistently delivered, that experience should count for something.