Responsible AI

An ethical approach to
AI-powered automation

Technology, like all technical tools, can serve multiple purposes. At Deepomatic, we create solutions that enable our customers to increase their productivity, and are committed to ensuring that they have the most positive impact possible on the social ecosystem they belong to. To guarantee this added social value, we have made tangible commitments.
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A detailed action plan

The main principles of our code of ethics

Open to all industries, but not all use cases
Visual automation can make it possible to achieve considerable gains in a large number of sectors. That is why we are ready to collaborate with most industries. However, we have identified a small number of use cases that seem incompatible with our desire to make artificial intelligence beneficial and profitable for the greatest number of people. This is why we refuse to:
No to military uses
Contribute directly or indirectly to the development of weapons, that is to say any object or device designed with the aim of killing, injuring, striking, neutralizing, or incapacitating.
No to mass surveillance
Develop facial recognition solutions for those whose explicit objective would be mass surveillance or behavioral surveillance of our customers’ employees.
No to tobacco expansion
Contribute to the extension of the tobacco market.

GET TO KNOW OUR STAKEHOLDERS

What is data annotation?

In order to work, our algorithms must first be trained on a curated set of structured data, that is to say, data annotated by hand. The annotation phase assigns one or more labels to the elements of a dataset to make it possible to train the models used in our applications. It is therefore a service that we systematically use during the configuration phase of our new customers.

The need for annotation services is growing exponentially in line with the success of artificial intelligence, sometimes leading to abuses. The working conditions of these “click workers” have also recently gained visibility through academic publications and general public reports.

Focusing on the quality of local entrepreneurship

The relevance and performance of a solution strongly depends on the quality of the data and the quality of the labels. Deepomatic therefore paid particular attention to the choice of our annotation partner.

Taking a closer look at this market, we discovered that it rarely benefits the local economies in which it is established. This is why, as soon as it was possible for us, we supported the creation of local businesses.

This choice allows us to maintain a privileged relationship with one of our main stakeholders. Today we are proud to partner with Shakti Outsourcing.

Stimulating research on the working conditions of annotators

In addition to the search for quality, knowing our employees allows us to fully exercise our duty of vigilance. In other words, to ensure that our requirements in terms of working conditions and human rights are fully met.

Today we want to contribute to a more global reflection on the issues specific to the development of this new form of subcontracting in a globalized world. This is why we have chosen to open our doors to a large French laboratory working on these questions.

Revolutionize the way you work – on and off the field.

Want to learn more about Deepomatic?
Let’s discuss.

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