The development of artificial intelligence (AI) in the daily operations of businesses raises ethical challenges related to its use. The need for a responsible and ethical approach to AI has become imperative for companies wishing to innovate while maintaining the trust of their customers, employees, and partners. In this context, Sofrecom was called upon to assist an operator in its AI transformation journey while addressing ethical concerns.
Customer's need
In anticipation of European AI regulations and as part of its AI transformation plan, our client aimed to mitigate the ethical risks associated with implementing AI solutions. The main objective was to integrate ethical practices into the development and use of AI to ensure that the solutions deployed are not only effective but also responsible. This involved:
- Addressing crucial questions related to transparency, model robustness, privacy protection, and fairness.
- Developing a deep understanding of ethical issues.
- Evaluating available tools to ensure compliance and security for AI projects.
Methodology set up by our experts
To meet the specific needs of our client, Sofrecom established a structured methodology within an agile co-construction approach with the client's teams:
1. Needs analysis
An initial analysis phase identified the specific AI-related challenges within the client's organization, involving extensive discussions with all internal stakeholders to identify ongoing AI projects and associated ethical challenges.
2. Tool benchmarking
Sofrecom conducted tests and benchmarks of various ethical AI tools, identifying the best solutions tailored to the operator's specific context and use cases.
3. Development of explainability modules
To enhance the transparency of AI projects, explainability modules were developed and integrated into existing AI models, making algorithmic decisions more understandable for end-users.
4. Documentation
This included recommendations on best practices to ensure ethical compliance throughout the project lifecycle.
5. Risk assessment
A thorough study of new risks associated with AI was conducted, with Sofrecom presenting identified risks and proposing relevant tools for proactive risk management.
6. Training & awareness
Dinally, training sessions were organized to raise awareness among teams about the ethical challenges of AI and the practices to adopt for responsible technology use.
Benefits of Sofrecom's support
Sofrecom's support enabled our client to achieve significant progress in its ethical approach. Here are some key benefits:
- Strengthening trust: by integrating ethical practices into its AI projects, the company reinforced the trust of its customers and partners, demonstrating its commitment to responsible technology use.
- Improved transparency: thanks to the explainability modules, algorithmic decisions are now more transparent, facilitating understanding and acceptance of AI solutions by users.
- Compliance with ethical standards: the proposed methodology ensured that AI projects adhered to key ethical principles, anticipating upcoming regulations.
- Ethical culture and risk management: by raising awareness among teams about ethical issues, Sofrecom contributed to establishing an ethical culture within the organization and mitigating potential risks, promoting a responsible approach in all technological initiatives.
- Responsible innovation: by integrating ethical practices into its AI projects, the client positions itself as a responsible and innovative player in its sector, enhancing its reputation and competitiveness.
In conclusion, Sofrecom's support in the field of ethical AI illustrates the company's commitment to assisting its clients in their digital transformation. By combining expertise in data science with an understanding of ethical issues, Sofrecom enables its clients to successfully navigate a constantly evolving environment.
In this project, several areas of Sofrecom's expertise were highlighted:
- Data Science expertise: advanced skills in developing AI models and algorithm explainability.
- Knowledge of ethical AI tools: ability to test and benchmark various tools to ensure ethical AI use.
- Risk management: identification and assessment of AI-related risks, with recommendations for their management.
- Training and awareness: implementation of training programs to raise awareness of ethical challenges.
- Documentation and methodology: development of clear methodologies for documenting AI projects.
