Clickworkers and crowdsourcing: what are they and why do we need to rethink this model for AI?
What is a clickworker or crowdsourcing specialist in the world of artificial intelligence?
In today's digital age - and particularly in the age of artificial intelligence - data is the new currency. However, this raw data has no value unless it is processed and analyzed. This is where clickworkers come in, the digital artisans who transform data into usable information. A clickworker is a freelancer who performs paid online tasks, usually via platforms of 🔗 crowdsourcing. Clickworkers can work from home or on the move. They often use an app on their smartphone to access micro-tasks. However, they often encounter challenges related to retrieving their money, 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 thankless, requiring the mobilization of an indentured workforce that is often unskilled and impersonal. When a company uses crowdsourcing or clickworkers, it is mobilizing thousands of individuals whose names and backgrounds it does not know.
Yet these digital workers play an important role in processing the massive data generated daily by businesses, organizations and individuals. They are involved in a wide range of projects, from image categorization to data transcription and online content moderation. A reliable Internet connection is essential for these clickworkers to access online work opportunities.
The term "clickworker" is often seen in a pejorative light, as it reduces the work of these individuals to simple clicks, thus minimizing the complexity and value of their contribution (we at Innovatiana disagree: we believe that the work of Data Labeler would benefit from being valued and recognized at its true worth!). Clickworkers are often referred to as "digital proletarians" due to the fragmented and precarious nature of their work.
Despite significant contributions to powering artificial intelligence, improving search engines and guaranteeing the quality of online services, it's becoming increasingly clear that the crowdsourcing model is showing signs of obsolescence. So, before explaining why this model is on the wane, we'd first like to take a closer look at the work of clickworkers, highlighting the opportunities but also the challenges these professionals face on a daily basis.
How do clickworkers work?
The work of clickworkers is based on the principle of crowdsourcing, which involves outsourcing tasks to a large number of people via the Internet. Crowdsourcing platforms act as intermediaries between customers who need work and the clickworkers who carry it out.
Here's what a 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. Job selection
Available jobs are displayed on the platform, and clickworkers can choose those that match their skills and availability.
3. Task completion
Once a task has been selected, the clickworker carries it out according to the instructions provided by the customer. Tasks can be as simple as image categorization, or as complex as 🔗 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. Although time-consuming, these tests are very rarely paid for. 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, generally based on the number of tasks completed or time spent. Depending on the assignment, the likelihood of being paid is not always obvious(red flag!), as quality criteria are sometimes ambiguous and open to interpretation... Some clickworkers aren't always paid for every task they complete.
Overall, while not perfect, crowdsourcing allows clickworkers to work flexibly, choosing their own hours and selecting the tasks that suit them best.
Outsourcing micro-tasks to clickworkers: what are the benefits?
Using clickworkers has many advantages for companies 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 skilled workers from all over the world, offering a diversity of skills and perspectives.
2. Cost reduction
By outsourcing tasks to clickworkers, companies can make substantial savings compared to hiring permanent staff.
3. Flexibility and speed
Clickworkers can be mobilized quickly to meet one-off needs or peaks in activity, offering companies great flexibility. What's more, clickworkers can work from home, enabling them to accomplish a variety of tasks while remaining at home.
4. Guaranteed quality
Crowdsourcing platforms generally have quality control and clickworker rating systems, 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, skilled workforce, companies can focus on their core activities while benefiting from access to highly specialized human resources.
Types of tasks performed by clickworkers
The tasks entrusted to clickworkers are extremely varied and cover a wide range of fields. Here are a few examples of tasks commonly performed by these digital workers:
- Categorization and 🔗 data labeling : Clickworkers categorize and label 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 proofread content such as articles, product descriptions or advertising scripts.
- Research and data collection: Clickworkers conduct online research, collecting and organizing information on specific topics.
- Content moderation: They review and filter online content to ensure it complies with current policies and regulations.
- Surveys and market research: They take part in surveys, usability tests or market research, 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 data to guarantee its quality.
This diversity of tasks gives clickworkers the opportunity to work in a variety of fields and develop new skills.
Crowdsourcing platforms and applications for finding 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 specializing in online work, offering tasks such as data categorization, content writing and content moderation.
- 🔗 Upwork : A generalist freelancing platform that enables clickworkers to find projects in a variety of fields, including writing, translation and software development.
- 🔗 Fiverr : An online service platform where clickworkers can offer their skills in various fields, 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 specializing 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 those that best match their skills and interests.
Working as a clickworker: challenges and opportunities
While working as a clickworker offers many advantages in terms of flexibility and diversity, it also brings certain challenges and opportunities to consider:
Job security challenges
Unstable income
Clickworkers are paid by the job, which can lead to irregular and unpredictable income.
Lack of job security
Clickwork is generally considered a precarious job, with no guarantee of a stable income or social benefits.
Increased competition
As the number of clickworkers increases, competition for work can be fierce, putting downward pressure on pay.
Risk of job rejection
Clickworkers can have their work rejected for reasons of quality or non-conformity, 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 can also face challenges related to the quality and speed of customer service that is supposed to help them get paid, or answer their questions about tasks in progress.
Why does crowdsourcing work? What opportunities are there for clickworkers?
Flexibility and autonomy
Clickworkers have the freedom to choose their own hours and work from anywhere, giving them great flexibility.
Diversity of tasks
They have access to a wide variety of tasks and projects, enabling them to develop new skills and stay engaged.
Additional income
Clickwork can be a source of additional income for students, retirees or people with other jobs.
More and more opportunities
Experienced and talented clickworkers can obtain more complex and better-paid tasks, as well as long-term freelance opportunities.
Contribution to innovation
By taking part in projects linked to artificial intelligence and machine learning, clickworkers are helping to shape the future of technology.
To succeed in this field, clickworkers need to be ready to meet these challenges and seize the opportunities that arise, by developing their skills, managing their time effectively and building a solid reputation.
Why has the crowdsourcing model become obsolete?
1. 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 uneven or even poor quality. Fragmented tasks, spread across a multitude of workers, can introduce inconsistencies in 🔗 annotations. Yet today's AI models require flawlessly consistent and accurate data to operate effectively. This variability in data quality represents a major challenge for algorithm performance.
To overcome this problem, consensus models have been developed. These involve submitting the same tasks to several clickworkers, then comparing their results to arrive at a consensus answer. This minimizes individual errors and improves the reliability of annotations. However, this approach involves mobilizing hundreds of clickworkers for each task, which significantly increases costs. This in turn can affect the remuneration of clickworkers, which often remains insufficient for the work required, creating a vicious circle where data quality and fair remuneration struggle to strike the right balance.
2. Unsuitable for complex tasks
Modern AI projects call for increasingly complex annotations, requiring an in-depth understanding of specific contexts and linguistic subtleties. Clickworkers, often mobilized for simple tasks, do not always possess the specialized skills needed to perform these complex tasks with precision. This can lead to costly errors and compromise the reliability of artificial intelligence systems.
3. Lack of responsiveness and scalability
The crowdsourcing model, which depends on the mobilization of a large mass of workers, also presents limitations in terms of responsiveness and scalability. The delays associated with managing this dispersed workforce can slow down data production, which is problematic in an environment where speed is of the essence. New approaches, such as partial automation and the use of specialized teams, offer more efficient solutions.
4. Few ethical considerations
Dependence on clickworkers also raises ethical questions. The precarious, poorly-paid and often anonymous work of clickworkers contrasts with growing expectations of corporate social responsibility. For any self-respecting company, it is necessary to adopt more transparent and equitable practices, which requires a change of model.
5. Technological advances requiring expertise
Last but not least, technological advances today offer more efficient alternatives to traditional crowdsourcing. Semi-supervised learning techniques, data augmentation and the use of AI to assist data annotation are all methods that reduce dependence on data volume, and therefore on clickworkers. Less voluminous data sets can be produced, using high-performance tools that help to improve the quality and speed of annotations. These innovations enable us 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 demands of the sector. Crowdsourcing is a solution of the past! The transition to more appropriate methods, which prioritize quality, specialization, ethics and efficiency, is essential to ensure that companies remain competitive in a world increasingly driven by artificial intelligence.
But, you might ask, what happens to clickworkers? Clickworkers, while continuing to play a role in certain aspects of data collection, will have to adapt to market changes by acquiring new skills and specializing in specific areas. This transition will enable them to move from a precarious status to more stable, full-time jobs within permanent structures. In these environments, their work will not only be valued, but also remunerated at its fair value, recognizing their expertise and their essential contribution to data quality for AI models.
