How to choose your data annotation specialist for your AI projects?
In recent years, the field of AI has advanced in leaps and bounds. To stay ahead of the curve, companies need access to the best technology has to offer: the best equipment, the best tools, and crucially, the best specialists. In data annotation especially, where expertise and skill count above all, the success of your project can hinge on whether or not you have the right expert on the job. How do you find the perfect specialist for your needs? Well, first you need to know exactly what data annotation is, and what a data annotation specialist does.
Data annotation is the backbone of machine learning models. By providing large quantities of tagged and labelled datasets, AI models can ‘learn’ to detect, recognise and understand various inputs (such as text, images or video) and come up with appropriate responses to those inputs. The accuracy of the AIs decisions increases over time as it is fed with more and more data. Clearly, large quantities of data are needed, and that's where your data annotation specialist comes in.
Your data annotation specialist will, essentially, provide your system with the dataset it learns from. It takes a team of people to label, tag, categorise and validate the data the machines learn from. To have high quality data then, you need a data annotation specialist that is accurate, able to handle large volumes of data and is trustworthy security-wise, among many other characteristics. The advancements in the AI, machine learning and deep learning field means you will be spoilt for choice; to narrow your choice down, it will be prudent to first select one of the three main types of specialist services available.
Hiring and forming your own in-house team of data annotation specialists may be a good option, especially if you require large amounts of control over the project.
-Security is assured, since your own company will be producing and reviewing the data protection protocols.
-Better understanding of the needs of the project
-Consistency in annotation, since you rely on the same team every time
-More resources have to be devoted to human resources and team compensation
-Managing large scale projects requires more specialised skill than your company may have internally without third party support.
Outsourcing to data annotation experts relieves much of the burden from the company, allowing the professional to handle the heavy lifting. It is the best solution for speedy, cost effective results.
-Pre existing infrastructure (facilities and services)
-The benefit of professional expertise
-Unscrupulous companies may undermine the security of data
-Quality may not be assured
This type uses end-to-end labelling technology, combining the best of human effort and Ai, while allowing data scientists to use their time for other matters
-Task annotation is delegated to users of the platform
-Platforms are usually specific to certain industries
Now that you’ve narrowed exactly what type of specialist you need, there are many characteristics to consider before you settle on a final choice.
You must consider whether the company has the ability to do the job right to the highest degree of quality possible. Looking at examples of their past work, unbiased reviews from customers and the QA processes they have can give you the right idea about their data annotation expertise.
Important projects usually come with sensitive data. Most foward thinking companies are hesistant to entrust this data to outsiders without assurance of safe keeping, and rightly so. Compliance with international security standards can be easily verified. If your specialist has the requisite documents, such as an ISO 2700 certificate, you can proceed knowing your data is in secure hands.
Each project has its specific timelines and generally, the earlier the data annotation can be done the better. However high turnover rate may mean decreased quality, so you want to be able to discuss the full scale of the project and get a realistic timeline.
The dynamic nature of the industry may mean the project may have to be scaled up or down in the midst of ongoing work. Your specialist should give you the flexibility to make these changes.
Sometimes, after checking all these factors it is still difficult to tell if a specialist service meets your needs. A good quality data annotation specialist will offer you a free trial to have a better idea of how they run projects.
Isahit is an ethical data labelling company that uses crowdsourcing, giving a strong guarantee of quality and control. Since 2015, Isahit has worked with numerous teams, companies and data scientists, building up expertise for your specific project needs.
Each team receives specialised training for each project, and quality control is integrated in the very fabric of the project. The technical infrastructure is state-of-the-art- the platform has the ability to adapt to the unique needs of your project. In terms of security, Isahit has the latest ISO certifications. As a customer, you will also be able to follow the progress of each project in real-time, retaining control of your own data.
Beyond all these qualifications, Isahit is about impact sourcing- socially responsible impact creation. Each contractor in their crowdsourced program is a young woman from a developing country being aided to become financially and digitally emancipated. If your company cares about their impact on the social world, Isahit is the data annotation specialist for you.
We strongly believe that humans will continue to play a crucial role in the Generative AI production process. What we call the Human-in-the-Loop in our Data Labeling/Processing industry. Humans possess unique qualities, including precision, contextual understanding, judgment, creativity, and background knowledge, which machines cannot fully replace but rather complement and enhance... The key lies in strategically integrating Generative AI into our daily operations, leveraging its potential to assist us in producing relevant content, developing outstanding products, and making informed decisions.
Explore the advantages and disadvantages of outsourcing and insourcing micro-tasks. Make informed decisions for your business with our comprehensive analysis.
We have a wide range of solutions and tools that will help you train your algorithms. Click below to learn more!