The introduction and first chapter of the Ghost Work describes and creates a certain almost apprehensive atmosphere of the self-titled term “Ghost Work”. With the rise of the technological advancements made recently, the work has described the rise of one of the most popular companies Amazon while leading to the jobs produced and reduced through the process. Though the company (and various others) have taken many steps to remove redundancies and use robots instead of humans, it is well acknowledged that AI or Machine Learning techniques are not fully capable of replacing humans yet. To this end the companies have followed up available crowd sourcing works to be able to quickly hire, fire, and pay respondents for their aide and human interaction. This kind of interaction has proved to be very profitable for the companies, for example instead of hiring full time participants for a total amount of $2,500 it instead cost around $700 – $800 dollars. Being able to provide a quick and accurate response (based on the question giver) provides short term jobs, that were studied to be sometimes more profitable yet more volatile than full-time jobs. The people surveyed in the study have each ran into times of jobs not being available, in which they were not given any kind of stipend after the job was finished. This have even caused issues with filing tax information, since the lawsuit inquiring about the employee status was settled and undetermined. These results framed this way makes way for a conclusion that the jobs provided by automation will be intellectually dull and on the support side for computers, only limited by the API scope and the adapting law.
I disagree with how the technology was framed, but I can appreciate the rationality. Having worked with APIs they can easily be a mess and adapting one API to another may take time to connect. The technology has also been greatly simplified, though for the purpose of this work it seems appropriate. Given the users of the example MTurk (for example) were given a specific sequence of characters for their id were most likely a UUID and representative of a SSN, though for the argument using the worker ID also seems appropriate given the scenario.
It was interesting hearing about the age demographic of the crowd-source or “Ghost Workers”. Having been in the technology industry and in the research field, it is very easy to be lost within the scope of the experiment or the sub-target of the audience and forget the full scope of the project or world.
- Among the following, I would like to see a more direct representation of the demographic of “Ghost Workers”. Though it seems professions such as Engineers would have a better chance of finding a job, it doesn’t seem like that within this context. I would also like to know more information about the geographic locations of the “Ghost Workers”. If majority of them are located within the more rural locations of the globe, then that would seem to make sense with the boost in the technological advances.
- Something else I would like to see a “post-mortem” survey on the ex “Ghost Workers”. Most of them appear to want to build from being a “Ghost Worker” to move onto a full-time job.
- A final question I would like to see represented is the rate of burn out “Ghost Workers” experience. Since one of the common themes is it is not legally a full-time job, the only limiter on the work produced is not a union but the person themselves.
