Best Data Labeling solutions with social impact in 2022
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.
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.
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.
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.
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.
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.
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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