I know nothing about this particular company. I also see no reason to assume it’s particularly bad (it could very well be above average). But I do see a lot of data around company engagement. There’s basically no chance this level of positivity is ubiquitous for them, especially when the target workforce appears to be people otherwise below the poverty line.<p>Although pointless tedium is not the most important factor in rating a job, I think data labeling could well be along the most pointlessly tedious jobs ever created.
I don’t feel that the pat in the back is necessary when highlighting these realities of the world economic inequality. The whole article could have been published without the intense PR focus.<p>To clarify, there is no hard numbers around the quantity of people performing this task, for how long they are employed, their average working hours per day, the median satisfaction rating, the median pay per employee, etc. It feels as if only some happy examples were picked.
Similar sort of thing with an autonomous food delivery startup from my university:<p><a href="https://medium.com/kiwicampus/how-kiwi-empowers-students-in-colombia-fe99cf1bbc8d" rel="nofollow">https://medium.com/kiwicampus/how-kiwi-empowers-students-in-...</a>
There are many laboratories that hire part-time data labelers to secure their own verified dataset. In fact, many global companies actually create values and earn money from their own various datasets. I think the value will be created from the data itself, less focus on data-processing skills. Of course, modeling skills will be still important at future, but data-processing would rather become much more easier. That's why self-bi tools like Tableau, elastic search are becoming more and more popular. I personally recommend Metatron Discovery, which is an Open-Sourced Big data analytics platform for citizen scientists.
Link : <a href="https://github.com/metatron-app/metatron-discovery" rel="nofollow">https://github.com/metatron-app/metatron-discovery</a>
"Life of a data labeler" is a wildly inaccurate description for "we asked some of our labelers for times when working for Scale made a positive difference in their lives."<p>What's the median hourly pay for a Scale data labeler? What fraction of their employees enjoy working for Scale? What's their six month retention rate? Amazon's Mechanical Turk has a reputation for grinding people up and burning them out; what makes Scale better?
A similar opportunity (and maybe a step up) would be 'crowd tester'; if a Dollar or Euro goes a little farther in your country than in the west, then 1€ for a bug reproduction up to 10€ for a major bug could be an attractive additional income ...<p>... while of course not providing with a stable regular job, and not necessarily doing much to strengthen the local economy in a fundamental sense.
And how am I supposed to know if the attractive, well-educated, contented folks chosen by this company's PR department are actually representative of its workforce?