ArticleslgStudy

computer science

Ghost work

Ghost work is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Ghost work rather than just read about it. In short: Ghost work is work performed by a human, but believed by a customer to be performed by an automated process. The term was coined by anthropologist Mary L.

Key takeaways

  • Ghost work belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Ghost work to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Ghost work from memory before moving on to harder problems.

Reference excerpt

Ghost work is work performed by a human, but believed by a customer to be performed by an automated process. The term was coined by anthropologist Mary L. Gray and computer scientist Siddharth Suri in their 2019 book, Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.

Definition Gray and Suri state that ghost work focuses on task-based and content-driven work that can be funneled through the Internet and application programming interfaces (APIs). They say that this work can include labelling, editing, and sorting information or content, as well as content moderation. They also state that ghost work can be performed remotely and on a contractual basis and that it is an invisible workforce, scaled for those who desire full-time, part-time, or ad-hoc work. A benefit of ghost work is flexible hours because the worker chooses when they complete a task, making it an appealing option for those in between jobs or in need of side work. Ghost work is differentiated from gig work or temporary work because it is task-based and uncredited. While gig work involves a general platform, ghost work emphasizes the software or algorithm aspect of assisting machines to automate further. Through labelling content, ghost workers teach the machine to learn. Ghost workers at Amazon have found ways to help each other and self-organize, often through WhatsApp groups where they mobilize to push for changes to the platform.

False perception According to Lilly Irani, an associate professor of labor at the University of California, San Diego, the computer science world and tech companies are invested in producing the image of technological magic. She says that MTurk– Amazon's task/ gig recruiting platform– hides the people involved in the production, whose visibility could otherwise obstruct this favorable perception. Her view is that this perception isn't only aimed at the public image of the company but also at investors, who are significantly more likely to back businesses built on scalable technology, rather than unwieldy work forces demanding office space and minimum wages. In addition, she feels that there is a strong belief that these workers are a stopgap until better AI reduces the need for relying on humans for such tasks. Despite the belief, the market for ghost work doesn't show apparent signs of declining. There are some disadvantages, but the ghost work industry will potentially grow even more in the upcoming years.

References

Worked examples

Example 1 — a first encounter with Ghost work

Start with the simplest possible case. Write down what Ghost work claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Ghost work before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Ghost work ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Ghost work

In research
Ghost work appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Ghost work in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Ghost work is common in secondary-school and first-year university syllabi. It links to neighbouring topics Employment classifications, Human-based computation, Precarious work, so understanding it makes those chapters shorter.
In everyday life
Look for Ghost work outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Ghost work” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Ghost work in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Ghost work means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Ghost work out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Ghost work in simple terms?

Ghost work is work performed by a human, but believed by a customer to be performed by an automated process. The term was coined by anthropologist Mary L.

Why does Ghost work matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Ghost work?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Ghost work.

Tags

  • Employment classifications
  • Human-based computation
  • Precarious work

Keep exploring