I did read quite a lot on the topic, including “Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.” (2019) and saw numerous documentaries e.g. “Invisibles - Les travailleurs du clic” (2020).
What I find interesting here is that it seems the tasks go beyond dataset annotation. In a way it is still annotation (as in you take a data in, e.g. a photo, and your circle part of it to label i.e. e.g “cat”) but here it seems to be 2nd order, i.e. what are the blind spots in how this dataset is handled. It still doesn’t mean anything produced is more valuable or that the expected outcome is feasible with solely larger datasets and more compute yet maybe it does show a change in the quality of tasks to be done.
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Sad but unsurprising.
I did read quite a lot on the topic, including “Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.” (2019) and saw numerous documentaries e.g. “Invisibles - Les travailleurs du clic” (2020).
What I find interesting here is that it seems the tasks go beyond dataset annotation. In a way it is still annotation (as in you take a data in, e.g. a photo, and your circle part of it to label i.e. e.g “cat”) but here it seems to be 2nd order, i.e. what are the blind spots in how this dataset is handled. It still doesn’t mean anything produced is more valuable or that the expected outcome is feasible with solely larger datasets and more compute yet maybe it does show a change in the quality of tasks to be done.