Amazon Mechanical Turk (MTurk) is a crowdsourcing Internet marketplace enabling individuals and businesses (known as Requesters) to coordinate the use of human intelligence to perform tasks that computers are currently unable to do. It is one of the sites of Amazon Web Services, and is owned by Amazon. Employers are able to post jobs known as Human Intelligence Tasks (HITs), such as choosing the best among several photographs of a storefront, writing product descriptions, or identifying performers on music CDs. Workers (called Providers in Mechanical Turk's Terms of Service, or, more colloquially, Turkers) can then browse among existing jobs and complete them in exchange for a monetary payment set by the employer. To place jobs, the requesting programs use an open application programming interface (API), or the more limited MTurk Requester site. To submit a request for tasks to be completed through the Amazon Mechanical Turk web site, a requester must provide a billing address in one of around 30 approved countries.
Video Amazon Mechanical Turk
Overview
The name Mechanical Turk was inspired by "The Turk", an 18th-century chess-playing automaton made by Wolfgang von Kempelen that toured Europe, beating both Napoleon Bonaparte and Benjamin Franklin. It was later revealed that this "machine" was not an automaton at all, but was in fact a human chess master hidden in the cabinet beneath the board and controlling the movements of a humanoid dummy. Likewise, the Mechanical Turk online service allows humans to help the machines of today perform tasks for which they are not suited.
Workers set their own hours and are not under any obligation to accept any particular task. Because workers are paid as contractors rather than employees, they don't have to file forms or pay payroll taxes, and they avoid laws stipulating conditions regarding minimum wage, overtime, and workers compensation. However, they must report their income as self-employment income. The average wage for the multiple microtasks assigned, if performed quickly, is about one dollar an hour, with each task averaging a few cents.
Requesters can ask that Workers fulfill qualifications before engaging in a task, and they can set up a test in order to verify the qualification. They can also accept or reject the result sent by the Worker, which affects the Worker's reputation. Workers can have a postal address anywhere in the world. Payment for completing tasks can be redeemed on Amazon.com via gift certificate (gift certificates are the only payment option available to international workers, apart from India) or be later transferred to a Worker's U.S. bank account. Requesters pay Amazon a 20% commission on the price of successfully completed jobs.
Location of Turkers
According to a survey conducted in 2008 through one MTurk HIT, Workers are primarily located in the United States with demographics generally similar to the overall Internet population in the US.
The same author carried out a second survey in 2010 (after the introduction of cash payments for Indian workers), which gave new and updated results on the demographics of workers. He currently runs a website showing worker demographics that is updated hourly. It shows that approximately 80% of workers are located in the United States and 20% are located elsewhere in the world, most of whom are in India.
A more recent study reports Worker demographics on over 30,000 Workers across 75 studies that have been conducted since 2013.
Maps Amazon Mechanical Turk
History
The service was initially conceived by Venky Harinarayan.
MTurk was launched publicly on November 2, 2005. Following its launch, the Mechanical Turk user base grew quickly. In early- to mid-November 2005, there were tens of thousands of jobs, all of them uploaded to the system by Amazon itself for some of its internal tasks that required human intelligence. HIT types have expanded to include transcribing, rating, image tagging, surveys, and writing.
In March 2007, there were reportedly more than 100,000 workers in over 100 countries. This increased to over 500,000 registered workers from over 190 countries in January 2011. In the same year, Techlist published an interactive map pinpointing the locations of 50,000 of their MTurk workers around the world.
Description
Users
A user of Mechanical Turks can be either a "Worker" (contractor) or a "Requester" (employer).
Employees have access to a dashboard that displays three sections: total earnings, HIT status and HIT totals.
- Total earnings: displays the total earnings a worker has received from the realization of human intelligence tasks, the gains made from bonuses and the sum of these two.
- HIT status: displays a list of daily activities and the daily income, along with the number of visits that were submitted, approved, rejected or waiting for the given day.
- HIT totals: displays information about HIT which have been accepted or are in process (including the percentage of successes that occurred, returned or abandoned and the percentage of jobs that were approved, rejected or pending those presented).
Employers (companies or independent developers that need jobs performed) can use the Amazon Mechanical Turk API to programmatically integrate the results of that work directly into their business processes and systems. When employers set up their job, they must specify
- how much are they paying for each HIT accomplished,
- how many workers they want to work on each HIT,
- maximum time a worker has to work on a single task,
- how much time the workers have to complete the work,
as well as the specific details about the job they want to be completed.
Other aspects
- Crowd labor
Amazon Mechanical Turk provides access to a crowd-sourced market of workers that can help to complete work on an as-needed basis. For work that does not require significant task-specific training, this can contrast with the traditional costs of hiring and management of temporary staff. For users, it also allows them to select among a variety of different tasks.
- Quality management
Amazon Mechanical Turk allows more than one user to send a response to the same HIT. When a specific number of users give the same answer, the HIT is automatically approved. All data for HITs is available for viewing as soon as it is submitted, allowing Requesters to manually assess quality. Requesters are not required to accept a worker's results if they are deemed inadequate, which may lead to frustration between parties. If the result is not adequate, the job is rejected and the Requester is not required to pay.
- Price determination
Users are free to work on tasks that they find most interesting, those they like to complete or the best paid. Requesters are allowed to define the payments based on the desired balance of performance and cost-efficiency. Payments are made in cooperation with Amazon Payments.
- User qualification
Amazon Mechanical Turk allows for qualifying users before they work in their tasks using rapid tests. The qualifications can be a series of questions, performing tasks or request users to have historically responded to a minimum percentage of their HIT sent correctly. Such preliminary tests can be used by companies to get data for questions without paying anything.
- Data for Machine Learning
Machine Learning algorithms require enormous amounts of human data to be successful. Acquiring such cognitive data can be very difficult and companies such as Mturk and CrowdFlower offer means to acquire it efficiently and cheaply
Uses
Applications
Missing persons searches
Since 2007, the service has been used to search for prominent missing individuals. It was first suggested during the search for James Kim, but his body was found before any technical progress was made. That summer, computer scientist Jim Gray disappeared on his yacht and Amazon's Werner Vogels, a personal friend, made arrangements for DigitalGlobe, which provides satellite data for Google Maps and Google Earth, to put recent photography of the Farallon Islands on Mechanical Turk. A front-page story on Digg attracted 12,000 searchers who worked with imaging professionals on the same data. The search was unsuccessful.
In September 2007, a similar arrangement was repeated in the search for aviator Steve Fossett. Satellite data was divided into 85 squared meter sections, and Mechanical Turk users were asked to flag images with "foreign objects" that might be a crash site or other evidence that should be examined more closely. This search was also unsuccessful. The satellite imagery was mostly within a 50-mile radius, but the crash site was eventually found by hikers about a year later, 65 miles away.
Social science experiments
Beginning in 2010, numerous researchers have explored the viability of Mechanical Turk to recruit subjects of social science experiments. Thousands of papers that rely on data collected from Mechanical Turk workers are published each year, including hundreds in top ranked academic journals. Researchers generally found that while samples of respondents obtained through Mechanical Turk do not perfectly match all relevant characteristics of the U.S. population, they're not wildly misrepresentative either. The general consensus among researchers is that the service works best for recruiting a diverse sample; it is less successful with studies that require more precisely defined populations or that require a representative sample of the population as a whole. Overall, the U.S. MTurk population is mostly female and white, and is somewhat younger and more educated than the U.S. population overall. Data collected on jobs conducted since 2013 show that the U.S. population is no longer predominantly female, and that Workers are currently slightly more likely to be male. The cost of MTurk was considerably lower than other means of conducting surveys, with workers willing to complete tasks for less than half the U.S. minimum wage.
Artistic and educational research
In addition to receiving growing interest from the social sciences, MTurk has also been used as a tool for both artistic and educational exploration. Artist Aaron Koblin has made use of MTurk's crowdsourcing ability to create a number of collaborative artistic works such as The Sheep Market and Ten Thousand Cents which combined thousands of individual drawings of a US$100 bill. The work functions as a sort of reverse exquisite corpse drawing.
Inspired by Koblin's collaborative artworks, a Concordia University graduate research student turned to MTurk to see if the crowdsourcing technology could also be used for educational research. Scott McMaster conducted two pilot projects which used HITs to request drawings, but, in contrast to Koblin's work, the workers knew exactly what the drawings were being used for. The jobs required participants to visually represent sets of words in drawings and fill out a short demographic survey. Although the research was in its infancy, McMaster's findings suggested that a globalizing effect is emerging within visual cultural representations. It is a published instance of this type of online research into visual culture.
Third-party programming
Programmers have developed various browser extensions and scripts designed to simplify the process of completing jobs. According to the Amazon Web Services Blog, however, Amazon appears to disapprove of the ones that completely automate the process and preclude the human element. Accounts using so-called automated bots have been banned. There are services that extend the capabilities to MTurk.
API
Amazon makes available an application programming interface (API) to give users another access point into the MTurk system. The MTurk API lets a programmer access numerous aspects of MTurk like submit jobs, retrieve completed work, and approve or reject that work. In 2017, Amazon launched support for AWS Software Development Kits (SDK), allowing for nine new SDKs available to MTurk Users. MTurk is accessible via API from the following languages: Python, JavaScript, Java, .NET, Go, Ruby, PHP or C++. Web sites and web services can use the API to integrate MTurk work into other web applications, providing users with alternatives to the interface Amazon has built for these functions.
Use case examples
Processing photos / videos
Amazon Mechanical Turk provides a platform for processing images, a task well-suited to human intelligence. Requesters have created tasks asking workers to label objects found in an image, select the most relevant picture in a group of pictures, screen inappropriate content, and classify objects in satellite images. Also, crowd workers have completed tasks of digitizing text from images such as scanned forms filled out by hand.
Data cleaning / verification
Companies with large online catalogs use Mechanical Turk to identify duplicates and verify details of item entries. Some examples of fixing duplicates are identifying and removing duplicates in yellow pages directory listings and online product catalog entries. Examples of verifying details include checking restaurant details (e.g. phone number and hours) and finding contact information from web pages (e.g. author name and email).
Information collection
Diversification and scale of personnel of Mechanical Turk allow collecting an amount of information that would be difficult outside of a crowd platform. Mechanical Turk allows requesters to amass a large number of responses to various types of surveys, from basic demographics to academic research. Other uses include writing comments, descriptions and blog entries to websites and searching data elements or specific fields in large government and legal documents.
Data processing
Companies use Mechanical Turk's crowd labor to understand and respond to different types of data. Common uses include editing and transcription of podcasts, translation, and matching search engine results.
Research validity
The validity of research conducted with the Mechanical Turk worker pool has been questioned. This is in large part due to the proprietary method that Mechanical Turk uses to select its workers. Since the method of selection is not shared with researchers, researchers can not know the true demographics of the pool of participants. It is unclear if Mechanical Turk uses fiscal, political, or educational limiters in their selection process. This may invalidate any surveys or research done using the Mechanical Turk worker pool.
Labor issues
Monetary compensation
Because tasks are typically simple and repetitive and users are paid often only a few cents to complete them, some have criticized Mechanical Turk for exploiting and not compensating workers for the true value of the task they complete. Computer scientist Jaron Lanier notes how the design of Mechanical Turk "allows you to think of the people as software components" that conjures "a sense of magic, as if you can just pluck results out of the cloud at an incredibly low cost." On the other hand, in one psychological study done by the University of Texas, evidence showed that many of the workers did not complete the task for monetary compensation, and instead did the work for enjoyment and self-fulfillment. '
Fraud
The Nation magazine said in 2014 that some requesters had taken advantage of workers by having them do the tasks, then rejecting their submissions in order to avoid paying them.
In the Facebook-Cambridge Analytica data scandal, Mechanical Turk was one of the means of covertly gathering private information for a massive database. The system paid persons a dollar or two to install a Facebook connected app and answer personal questions. The survey task, as a work for hire, was not used for a demographic or psychological research project as it might have seemed. The purpose was instead to bait the worker to reveal personal information about the worker's identity that was not already collected by Facebook or Mechanical Turk.
Labor relations
Others have criticized that the marketplace does not have the ability for the workers to negotiate with the employers. In response to the growing criticisms of payment evasion and lack of representation, a group has developed a third party platform called Turkopticon which allows workers to give feedback on their employers allowing other users to avoid potentially shady jobs and to recommend superior employers. Another platform called Dynamo was created to allow the workers to collect anonymously and organize campaigns to better their work environment, including the Guidelines for Academic Requesters and the Dear Jeff Bezos Campaign.
Related systems
Amazon coined the term artificial artificial intelligence for processes outsourcing some parts of a computer program to humans, for those tasks carried out much faster by humans than computers. Jeff Bezos was responsible for the concept that led to Amazon's Mechanical Turk being developed to realize this process.
MTurk is comparable in some respects to the now discontinued Google Answers service. However, the Mechanical Turk is a more general marketplace that can potentially help distribute any kind of work tasks all over the world. The Collaborative Human Interpreter (CHI) by Philipp Lenssen also suggested using distributed human intelligence to help computer programs perform tasks that computers cannot do well. MTurk could be used as the execution engine for the CHI.
See also
- CAPTCHA, which challenges and verifies human work at a simple online task
- Citizen science
- Microwork
References
Further reading
- Business Week article on Mechanical Turk by Rob Hof, November 4, 2005.
- Wired Magazine story about "Crowdsourcing," June 2006.
- Salon.com article on Mechanical Turk by Katharine Mieszkowski, July 24, 2006.
- New York Times article on Mechanical Turk by Jason Pontin, March 25, 2007.
- Technology Review article on Mechanical Turk, "How Mechanical Turk is Broken," by Christopher Mims, January 3, 2010.
- J. Nathan Matias (June 8, 2015), "Tragedy of the Digital Commons", The Atlantic (discusses labor relations)
External links
- Official website
- Requester Best Practices Guide, Updated February 2015.
- Matt Lease (ed.). "Amazon Mechanical Turk". Crowdsourcing News, Events, and Resources. USA - via University of Texas at Austin School of Information.
Source of article : Wikipedia
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