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May 12, 2022

Best Data Labeling solutions with social impact

May 12, 2022

In every industry, AI-powered products will deliver the results you want only if you train them properly. This is exactly where image labeling comes in. 

How do you outsource your data annotation projects?

The manual labeling of data is a costly and labor-intensive process but it is the best way to create High Quality Training Data. It's best to find a firm that provides human expertise on their workforce and the ability to scale. This will help optimize for costs and time. 

3 Reasons to Outsource Your Data/Image Annotation Projects

Better quality of work

Outsourcing gives you access to skilled expertise and increase production leading to more flexibility. Working with professional data annotators will guarantee that you get the highest quality of work. This makes a lot of difference because there are usually so many sensitive factors involved.

Scalability

After creating an AI model, you may not be able to predict when you will need more data  or when you have to stop training data preparation for a while. Scalability is how you make sure that your AI development process runs smoothly and most times, this can only be achieved with professional data annotators who can respond to dynamic demands and consistently deliver the data you require.

Removes internal biais

Training datasets are one of the first places where bias can creep and this could be bad for your company's reputation. This is why you need a pair of fresh eyes from external sources to constantly monitor sensitive topics and identify and eliminate biases in the system where they exist.

How to choose the right data labeling partner

  1. Identify your needs: First of all you need to know exactly what it is you plan to achieve with your project. This will help you outline your exact data labeling needs which you can use as a guideline when searching for the right vendor. Always be clear when outlining your objectives. 
  1. Do your research and choose your vendor: Always do your research! This is a step that cannot be overlooked. Before going with or hiring a vendor, endeavor to look at previous projects they have handled and companies they have worked with to see if they will be a good fit for you. Always make sure that they have the capacity to deliver at the levels you require before initiating a deal. 
  1. Monitor and manage for success: Create a plan or an outline in accordance with your goals or expectations for the project that will help you assess if the right objectives are being met consistently. This will help you hit deadlines and will also create a way for you to check if quality standards are being met. 

 Top data annotation firms

Isahit:

First on the list is Isahit which is a world class data labeling and annotation platform and a one stop shop for all your data labeling needs. Their mission is to bridge the gap between human and artificial intelligence through digital task outsourcing and they are doing just that with their team of proficient data annotators. With a 97% recommendation rate we can say that Isahit is one of the best companies in the industry. By keeping a "Human in the loop" approach, they have been able to build a solid AI training platform. Isahit also has a real social mission with these annotators and is the first European artificial intelligence company certified B Corp. 

Appen:

Appen is a company that provides data management for different stages of the AI lifecycle. They offer a range of data annotation jobs that are mostly related to AI training tasks or evaluation of services provided by search engines and social media platforms. 

Cogito Tech LLC:

Cogito aims to provide training data for machine learning and AI based applications that require high quality data sets with accuracy. They have a strong presence in the USA and a delivery centre in India and they collaborate with clients to build high quality data sets that are used in various innovative business applications.

Labelbox:

Labelbox is a training data platform that is positioned to help you improve your training data mutation loop. It is designed around the ability to annotate data, diagnose model performance, and prioritize actions based on your results. 

Outsourcing your data annotation project could help you increase your internal productivity, give you a much faster time to market your product, and also give you more time to test your results and optimize your algorithms.

Hiring a reputable firm like Isahit with dedicated employees for data collection, labeling and quality assurance will also guarantee you getting the best quality of work.

The quality of data is very important for Artificial Intelligence and model performance. Interestingly, data labeling performs a lot in terms of positively impacting the society. The easy and accessible nature of data labeling is a great way to create jobs for those who may need it the most, especially those that may be facing a lot of barriers to employment. Such people may include but are not limited to the following: the underprivileged, people with disabilities and refugees.

At isahit ,we believe when it comes to choosing the best data labeling provider, you must find one that has an impact on the society such as providing annotation work to the vulnerable in the society while providing high-quality data.

Below are 5 data labeling solutions with social impact in 2022:

1. Isahit

Isahit is the first European ethical data labeling company that is certified by B Corp. It can be described as a socially responsible outsourcing platform which is based in France but provides employment opportunities for young ladies from developing countries. With Isahit, companies can source digital tasks for artificial intelligence and data processing. By dividing tasks to microtasks, Isahit offers integrated quality control mechanisms and a secure API. They offer data annotation for computer vision as well as for NLP, including in French, English and other languages.

Isahit is one of the best data labeling solutions with social impact in 2022. This is because Isahit currently has over 1000 HITers, who are all women and are in the global south (including Africa, Asia, and Latin America). Isahit is a socially responsible company in the sense that they have provided jobs for young women in the global south. Most of these women would not have been capable of financing their higher education or earning a supplementary income if they were not employed by Isahit.

2. DignifAI

DignifAI is an AI data services company with a social impact in Colombia, Latin America. One special thing about DignifAI is that it deals with the recruitment, training, and distribution of annotation tasks to vulnerable populations such as the migrant populations and the vulnerable communities in Colombia. Their area of specialization is in Spanish language NLP labeling, computer vision dataset curation and annotation.

DignifAI performs its social responsibility by working with Venezuelan refugees and this is their own way of responding to the Venezuelan refugee crisis. In 2017, their project officially began with a successful pilot in a refugee camp in Greece.

3. Humains in the loop

They are based in Bulgaria. It is an award-winning social enterprise that is biased free and provides ethical model training and validation services for Machine Learning. Their focus is on providing a continuous model improvement through human input. They are one of the few EU-based data labeling companies. They work on 2D, and 3D image and video annotation, output verification, dataset collection, and error analysis. Through their work, they aim to connect conflict-torn communities to digital work. By providing them with work opportunities, training, and upskilling, they seek to make a long-lasting impact on their livelihoods. Humains in the loop partners with organizations in Turkey, Syria, and Iraq and work with internally displaced people, asylum-seekers, and locals.

4. Daivergent

Daivergent focuses on providing data services such as annotation, labeling and end-to-end project management. They are a Public Benefit Corporation that is based in the United States.

Daivergent collaborates with the government, community, and educational partners in order to match their employees with suitable learning and work opportunities.

5. Sama

Sama was previously known as Sama source. It is a B-corporation and currently works on data entry and labeling tasks for computer vision. They offer additional features like data selection and filtering, model optimization, and detailed reports through their Sama Hub annotation platform.

Sama is a proponent of the “Give work” idea and they have provided dignified jobs to vulnerable communities in Kenya, Uganda, India, Haiti, Pakistan, Ghana, and South Africa.

How to choose your data labeling partner with social impact in 2022?

It is very important to know which kind of data labeling partner to choose. Choosing a data labeling partner that values social impact is very vital. To choose the best data labeling partner with social impact, you must:

1: You must choose a data labeling partner that works with vulnerable groups in the society. This data labeling partner must also provide the best supervision and career development opportunities for their workers.

2: Again, you must also choose a data labeling partner that is interested in upskilling their annotation workers and equipping them with transferable skills.

3: It is also your social responsibility to work with an annotation partner that guarantees dignified work conditions and fair remuneration for their workers. By doing all the above, then you can be sure that you will work with partners that are socially responsible and are making positive social impacts within their communities.

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