Clickworkers and crowdsourcing: what are they and why should we rethink this model for AI?
What is a clickworker or crowdsourcing specialist in the world of artificial intelligence?
In today's digital age — and especially in the age of artificial intelligence — data is the new currency of exchange. However, this raw data has no value without being processed and analyzed. That's where clickworkers come in, these digital artisans who transform data into usable information. A clickworker is a self-employed person who performs paid online tasks, usually through platforms of crowdsourcing. Clickworkers can work from home or on the go. They often use an application on their smartphone to access micro-tasks. However, they often encounter challenges in getting their money back, with frustrating rules and conditions that make it difficult to access their funds.
In the collective imagination, data processing tasks are often perceived as repetitive and ungrateful, requiring the mobilization of a workforce that is as hard as it can be, often low-skilled, but also impersonal. When a company uses crowdsourcing or clickworkers, it mobilizes thousands of individuals whose names and backgrounds it does not know.
However, these digital workers play an important role in processing the massive data generated daily by businesses, organizations and individuals. They participate in a variety of projects, ranging from image categorization to data transcription, to online content moderation. A reliable Internet connection is essential for these clickworkers in order to access online work opportunities.
The term “clickworker” is often perceived in a pejorative way, as it reduces the work of these individuals to simple clicks, thus minimizing the complexity and value of their contribution (at Innovatiana, we disagree: we believe that Data Labeler's work would benefit from being valued and recognized at its fair value!). Clickworkers are often referred to as “digital workmen” because of the fragmented and precarious nature of their work.
💡 Despite making significant contributions to powering artificial intelligence, improving search engines, and ensuring the quality of online services, it is increasingly clear that The crowdsourcing model is showing signs of obsolescence. So, before explaining to you why this model is losing momentum, we first want you to present in detail the work of clickworkers, by highlighting the opportunities but also the challenges that these professionals encounter on a daily basis.
How does the work of clickworkers work?
The work of clickworkers is based on the principle of crowdsourcing, which consists in outsourcing tasks to a large number of people via the Internet. Crowdsourcing platforms serve as intermediaries between customers who need work and the clickworkers who perform these tasks.
Here is what the day looks like for someone who lives in Madagascar or India, for example, and decides to work online on these platforms:
1. Registration on a platform
Clickworkers register on one or more crowdsourcing platforms, create a profile, and provide information about their skills and areas of expertise.
2. Selecting tasks
Available tasks are displayed on the platform, and clickworkers can choose the ones that match their skills and availability.
3. Completion of tasks
Once a task is selected, the clickworker performs it according to the instructions provided by the customer. Tasks can be simple, like categorizing images, or more complex, like content writing.
4. Submission and validation
After completing the task, the clickworker submits it for review. Clickworkers have to pass certain tests to access additional tasks, which makes the work more interactive and interesting. These tests, although time-consuming, are very rarely paid. Finally, the client or a moderator checks the quality of the work before approving or rejecting it.
5. Payment
If the work is approved, the clickworker receives remuneration, usually based on the number of tasks completed or the time spent. Depending on the missions, the probability of being paid is not always obvious (Red Flag !) , quality criteria being sometimes ambiguous and subject to interpretation... Some clickworkers are not always paid for all the tasks they do.
👉 Overall, while not perfect, crowdsourcing still allows clickworkers to work flexibly, choosing their own schedules and selecting the tasks that best suit them.
Outsourcing micro-tasks to clickworkers: what are the advantages?
The use of clickworkers has numerous advantages for businesses and organizations that need to process large amounts of data. Here are some of the main benefits:
1. Access to a global workforce
Crowdsourcing platforms provide access to a vast pool of qualified workers from around the world, offering a diversity of skills and perspectives.
2. Cost reduction
By outsourcing tasks to clickworkers, businesses can make substantial savings compared to hiring permanent staff.
3. Flexibility and speed
Clickworkers can be mobilized quickly to meet specific needs or peaks of activity, thus offering businesses great flexibility. Additionally, clickworkers can work from home, allowing them to complete a variety of tasks while staying at home.
4. Guaranteed quality
Crowdsourcing platforms generally have systems for quality control and for scoring clickworkers, thus ensuring quality work.
5. Diversity of skills
Clickworkers have a wide range of skills, from translation and programming to content writing and data analysis.
💡 By taking advantage of this flexible and skilled workforce, businesses can focus on their core businesses while benefiting from access to highly specialized human resources.
The types of tasks performed by clickworkers
The tasks given to clickworkers are extremely varied and cover a wide range of areas. Here are some examples of tasks commonly performed by these digital workers:
- Categorization and data labeling : Clickworkers categorize and tag images, videos, text, or other types of data to feed artificial intelligence and machine learning systems.
- Transcription and subtitling : They transcribe audio or video recordings into text, or create subtitles for multimedia content.
- Content writing and editing : They write, edit, or correct content such as articles, product descriptions, or advertising scripts.
- Research and data collection : Clickworkers search online, collect and organize information on specific topics.
- Content moderation : They review and filter online content to ensure that it complies with current policies and regulations.
- Surveys and market studies : They participate in surveys, usability tests, or market studies by providing their comments and opinions.
- Translation and localization : Multilingual clickworkers translate and adapt content for different markets and cultures.
- Data annotation : They annotate images, videos, or text to improve the performance of machine learning models.
- Data verification and validation : They check the accuracy and consistency of the data to ensure its quality.
This diversity of tasks offers clickworkers the opportunity to work in various fields and to develop new skills.
Crowdsourcing platforms and applications to find clickworkers
Crowdsourcing platforms play a central role in the work of clickworkers, acting as intermediaries between customers and workers. Here are some of the main platforms used to find clickworkers:
- Amazon Mechanical Turk : One of the largest and oldest crowdsourcing platforms, offering a wide variety of tasks to clickworkers around the world.
- Clickworker : A platform specialized in online work, offering tasks such as data categorization, content writing, and content moderation.
- Upwork : A general-purpose freelancing platform that allows clickworkers to find projects in a variety of areas, including writing, translation, and software development.
- Fiverr : An online service platform where clickworkers can offer their skills in various areas, such as graphic design, programming or content writing.
- Prolific : A platform focused on research studies and surveys, offering clickworkers the opportunity to participate in academic and commercial projects.
- Appen : A company specialized in data collection and annotation, employing clickworkers for tasks related to artificial intelligence and machine learning.
- Lionbridge : A language services company that uses clickworkers for translation, localization, and content moderation tasks.
These platforms offer clickworkers a wide variety of tasks and projects, allowing them to choose the ones that best fit their skills and interests.
Working as a clickworker: challenges and opportunities
While working as a clickworker offers numerous advantages in terms of flexibility and diversity, it also comes with some challenges and opportunities to consider:
Challenges related to job security
Unstable earnings
Clickworkers are paid per task, which can lead to irregular and unpredictable earnings.
Lack of job security
Clickworker work is generally considered to be precarious employment, with no guarantee of stable income or benefits.
Increased competition
With the increase in the number of clickworkers, competition for tasks can be fierce, leading to downward pressure on pay.
Risk of rejection of tasks
Clickworkers may have their work rejected due to quality or non-compliance reasons, which can affect their income.
Lack of recognition
The work of clickworkers is often overlooked and underestimated, despite its importance in the digital economy. Clickworkers may also encounter challenges related to the quality and speed of customer service that is supposed to help them get paid, or answer questions about tasks in progress.
Why does crowdsourcing work? What are the opportunities for clickworkers?
Flexibility and autonomy
Clickworkers have the freedom to choose their own hours and to work from anywhere, which gives them great flexibility.
Diversity of tasks
They have access to a wide variety of tasks and projects, allowing them to develop new skills and stay engaged.
Additional income
Clickworker work can be a source of additional income for students, retirees, or people with other jobs.
More and more opportunities
Experienced and talented clickworkers can get more complex and higher-paid tasks, as well as long-term freelance opportunities.
Contribution to innovation
By participating in projects related to artificial intelligence and machine learning, clickworkers are helping to shape the future of technology.
To succeed in this field, clickworkers must be ready to take on these challenges and take advantage of the opportunities that present themselves, developing their skills, managing their time effectively, and building a solid reputation.
Why has the crowdsourcing model become obsolete?
1. A lack of data quality and consistency
The massive use of clickworkers has made it possible to produce large volumes of annotated data, but often at the cost of very unequal or even poor quality. Fragmented tasks, distributed among a multitude of workers, can introduce inconsistencies in annotations. However, today's AI models require consistent and accurate data to work effectively. This variability in data quality represents a major challenge for the performance of algorithms.
To overcome this problem, consensus models have been developed. These models consist in submitting the same tasks to several clickworkers, then comparing their results to arrive at a consensual response. This minimizes individual errors and improves the reliability of annotations. However, this approach involves mobilizing hundreds of clickworkers for each task, which increases costs considerably. This increase in costs can in turn affect the remuneration of clickworkers, which is often insufficient given the work required, thus creating a vicious circle where data quality and fair remuneration struggle to be balanced.
2. Not very suitable for complex tasks
Modern AI projects require increasingly complex annotations, requiring a thorough understanding of specific contexts and linguistic subtleties. Clickworkers, who are often mobilized for simple tasks, do not always have the specialized skills needed to perform these complex tasks accurately. This can lead to costly mistakes and compromise the reliability of artificial intelligence systems.
3. A lack of responsiveness and scalability
The crowdsourcing model, which depends on the mobilization of a large mass of workers, also has limitations in terms of responsiveness and scalability. The delays associated with managing this dispersed workforce can slow data production, which is a problem in an environment where speed is critical. New approaches, such as partial automation and the use of specialized teams, offer more effective solutions.
4. Few ethical considerations
Addiction to clickworkers also raises ethical questions. The precarious, low-paid, and often anonymous work of clickworkers contrasts with growing expectations of corporate social responsibility. For any self-respecting business, it is necessary to adopt more transparent and equitable practices, which requires a change in model.
5. Technological advances that require expertise
Finally, technological advances now offer more efficient alternatives to traditional crowdsourcing. Semi-supervised learning techniques, data augmentation, and the use of AI to assist with data annotation are all methods that reduce dependence on data volume, and therefore on clickworkers. Smaller data sets can be produced by using powerful tools that contribute to improving the quality and speed of annotations. These innovations make it possible to better meet the requirements of modern AI projects.
Conclusion: crowdsourcing is a model that needs to be rethought
Although crowdsourcing has been an effective solution for preparing training data for AI, it is now necessary to rethink this model to meet the new requirements of the sector. Crowdsourcing is a solution of the past! The transition to more adapted methods, which prioritize quality, specialization, ethics and efficiency, is essential to ensure the competitiveness of businesses in a world that is increasingly focused on artificial intelligence.
But, you will tell me, what happens to the clickworkers? Clickworkers, while continuing to play a role in some aspects of data collection, will need to adapt to market changes by acquiring new skills and specializing in specific areas. This transition will allow them to move from a precarious status to more stable and full-time jobs within sustainable structures. In these environments, their work will not only be valued, but also fairly rewarded, recognizing their expertise and their critical contribution to data quality for AI models.
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