In the chapter of Instruction of the ghost work, the book describes what is ghost work, how does ghost work work and why we need ghost work. Ghost work focuses on work that is task-based and content-driven which can be finished through the Internet and APIs. This kind of work includes various tasks, like labeling, editing, sorting, proofreading and so on. While technology is developing fast, people are looking forward to the future with robots and AI, ghost work is playing an important role in not only computer science but the whole area of humans socially currently.
In chapter 1, the authors give us several examples of how people do their ghost works for different companies, institutions, and platforms. They are MTurk (Amazon), UHRS (Microsoft), LeadGenius, AMARA, and Upwork. This chapter specifically describes how a person acts as a ghost worker in various short-time jobs. Firstly, a person needs to verify his identity to get the opportunity as a ghost worker. After verification, he will be able to pick this preferable work among hundreds of choices. Finally, if he does a good job, he will be paid due to his great effort. What’s more, this chapter analyzed people who work as ghost workers and surveyed why people like to find ghost workers instead of hiring someone else officially.
After reading these two chapters, I am interested in the point: “paradox of automation’s last mile”. From this view, it seems that is impossible to fully achieve the automation in computer science. In many cases, the best choice does not exist for AI, while humans can make select the best options based on their personal situations. However, I consider this view as a motivation for people who work in computer science chasing the final goal of automation. We can try our best to make this “last mile” further and further. In addition, I really like the point that comparing with computers, humans have creativity and innovation which are never can be replaced by computers. This idea makes me kind of proud as being an HCI student. For the ghost work, I used to think that these trivial tests are finished by computers automatically. Now, I know that thousands of ghost workers made a great effort to improve our software, applications and the Internet world. I agree with the method that AMARA allows workers to return their tasks, especially for macro-ghost work. If someone takes a ghost work which he is not familiar with, nobody can guarantee the correctness of this task. With wrong feedback, companies need to assign this work to other people again.
For the question part, I am interested that after a person finishes and submits his ghost work, will there be other people who check his work again?
If not, what would happen if someone does his work carelessly or select a wrong option by mistake?
In this book, the authors mentioned that people know nothing about the person behind each ghost work, I am curious about the responsibility and correctness problem, especially for that Uber example.
In addition, for those macro-ghost work that contains multiple people working together, I am confused about the effectiveness of working with several anonymous people.
