Data labeling is one job that seems to lend itself well to gig work. There were many times where I would have gladly spent a day labeling images in exchange for $50, no need for benefits
I fundamentally disagree. Its not the size of the dateset that determines performance but the quality. Sure. Bigger is better. But simply better is *way* better. I can do more with 1000 high quality examples of the thing than I can with 40k low quality ones.
I've gone as far as bringing on 40 digitizers at once full time. I would never have been able to accomplish that project with turks. I would never have been able to call a team meeting and explain a very specific shift in interpretation we would be doing regarding the relationship of feature apple to feature banana, and when and where it would apply.
The difference between thinking you need oom more examples over a few quality ones I think depends on how in the thick of it you've been with regards to ML on theoretical grounds versus doing the boots on the ground work to get a product out. Having control over digitization and labeling and being willing to pay for high quality label's has allowed me to get results that directly meet my clients needs as opposed to sitting in some uncanny valley where the results are close, but no cigar.
1) I spent $100 on 1000 labels
2) I spent $100 on 500 good labels and 500 bad ones and can’t tell them apart.
If I spent $0.20 per label on 500 labels with good better accuracy I end up spending less and getting more.
The only way what you said makes sense is if we ignore the quality of the data as a consideration.