The Positive AI label

The Positive AI label aims to recognize the work undertaken by the association’s member companies, certify their approach to continuous progress and ensure responsibility for their data governance and algorithms. The label is open to Positive AI members regardless of their level of maturity, sector of activity and size.

A specific approach built on the basis of a technical framework around the 6 fundamental principles of Responsible AI

The label was built by the data scientists of the founding members of Positive AI in order to respond as closely as possible to the realities that data experts experience on a daily basis while responding to the challenges of business leaders. Thus, it is part of a global approach to evaluate both corporate governance and AI systems.

These training courses are provided by DataScientest, a training school specializing in data science. Each formulation module includes a common core with practical exercises and concrete use cases in companies to promote understanding of the risks that uncontrolled AI could generate and the proposed solutions (concepts of ethics and applicable law, examples of proven AI risks, the regulatory expectations of the AI ACT and its financial penalties, best practices and tools available, etc.).

Who are these training courses for?

Open to members of the Positive AI association, these training courses are intended for all companies and their employees who wish to improve and acquire the knowledge and skills required to use/develop artificial intelligence responsibly.

By training in ethical and responsible AI today, you anticipate future regulations (AI ACT) and limit the financial risks of bringing your organization’s AI systems into compliance.

The Positive AI Label:

• Takes into account all 6 fundamental principles of the Responsible AI framework
• Part of a holistic approach to assessing and aligning both the organization and AI systems
• Detailedly assesses Responsible AI maturity
• Identifies concrete levers to implement to progress effectively and implement a Responsible AI policy
• Covers both governance and technique of AI systems
• Enables the alignment of the organization’s teams to develop an ethical and responsible AI culture around values common to all teams

In addition, the label is based on a technical framework equipped with a library of questions, actions and tools, regularly enriched by our community, and covers the 6 fundamental key principles of Responsible Artificial Intelligence, defined by the European Commission :

1. Technical robustness and security
2. Responsibility
3. Private life
4. Human intervention
5. Transparency and explainability
6. Justice and equity
7. Social and environmental impact

Why initiate a labeling process for your business?

The Positive AI label offers organizations and companies the means to:

• to assess your level of maturity on Responsible AI,
• to identify concrete levers for progress as well as the actions and tools to respond to them,
• to promote your continuous improvement approach to Responsible AI,
• to implement data and algorithm governance that guarantees the fundamental rights of your employees and customers,
• to disseminate a culture of ethical AI around common values within the company and among future talents sharing these convictions.

Obtaining the label is delivered via an independent audit, while respecting confidentiality.