Home PublicationsData Innovators 5 Q’s for Bénédicte de Raphélis Soissan, CEO of Clustree

5 Q’s for Bénédicte de Raphélis Soissan, CEO of Clustree

by Eline Chivot
Bénédicte de Raphélis Soissan

The Center for Data Innovation spoke with Bénédicte de Raphélis Soissan, chief executive officer and founder of Clustree, a platform based in Paris that developed an AI system for career management and recruitment purposes. De Raphélis Soissan discussed the various ways AI can support human resources, including by increasing efficiency and reducing bias.

This interview has been edited.

Eline Chivot: How did you come up with the idea behind Clustree?

Bénédicte de Raphélis Soissan: After studying mathematics and spending four years as a consultant, I decided to change jobs in 2013. To identify all possible career evolutions, I analyzed hundreds of profiles similar to mine manually and realized how difficult and time-consuming the task was. This experience created the idea behind Clustree: an AI-based Career Coach, that leverages bias-free algorithms and machine learning to detect employees’ skills and appetencies in order to automatically recommend tailor-made internal job opportunities, training courses, mentors, and career paths throughout their professional journey.

When the company was created, we collected over 250 million profiles with job titles, skills, organizations…and learnt from it. Through these profiles, our solution acquired a deep understanding of skills and jobs through all sectors. We invest more than 4,000 working days in R&D to deliver a universal, open, and dynamic skills referential. Our referential counts over 55,000 skills which are usable and relevant in any country or vertical, and that is why our solution is so powerful.

Chivot: Why is AI useful in the field of human resources? In what ways does it help recruiters and applicants?

De Raphélis Soissan: Human resource management is a complex activity. Understanding each person’s skills, experiences, and appetencies is not easy. A career management associate can usually assist 50 individuals each year. Having an HR professional to help you build your career and explore all possibilities has been a privilege few have access to. AI can scale up this service and deliver a tailor-made and dedicated service to each employee, so HR managers can support more people and focus on high-value missions.

According to a 2016 Accenture report, AI has the potential to boost labor productivity by up to 40 percent in 2035 and allows human to make more efficient use of their time. With less repetitive tasks, you can be more creative, innovative…

In my opinion, AI is deeply changing recruitment processes overall. AI empowers employees. It gives full visibility on all internal possibilities to all. Everyone has the same amount of information and can drive their career according to their professional ambitions and personal plans. A person’s network has always been a really important thing. AI is able to change rules and create a fairer system.

HR managers can finally have a tool to support their strategic goals, by providing them with full visibility on their talent and skills pool, staff missions, and jobs, and reducing the time dedicated to recruitment, which makes this process more cost-efficient. HR managers can focus more on their organization, and on their employees’ journey and experience.

Last but not least, AI also has a deep impact on managers. Being a manager used to be about driving decision-making, controlling, and reporting. Now it is more about coaching, helping, and supporting. Managers are here to support you in your job as well as in your career. Yet they are not HR managers. They don’t know about all possible jobs and career paths within the company. AI can help them fully embrace their new roles as skills cultivators.

Chivot: What are the most important elements of an individual’s professional profile on today’s labor markets, and how does your technology take them into account?

De Raphélis Soissan: Skills, without a doubt. Skills is for us the new currency of the labor market. I personally believe in a market where you don’t hire someone because of previous or current job titles or degrees, but for skills.

Career changes are quite common now. People won’t do the same job until retirement, within the same company. How can a company deal with this shift and with the quest of sense and of self at work? By putting skills at the center of their processes and organization.

Being a manager used to be the ultimate goal, but not everyone wants to be a manager. Building an HR department around skills means that you take into account people’s experience, knowledge, and appetencies, that you promote horizontal mobility and career changes, while freeing yourself from bias such as gender, schools, or age. And that is what Clustree enables organizations to do.

Chivot: How would you like to expand Clustree in the future?

De Raphélis Soissan: We don’t want mobility to be a yearly thinking. Career must be seen as something that you can really work on and build nearly on a daily basis. Want do I want to do? What skills do I lack of? Which courses should I take? Who should I meet? That’s the kind a question we provide an answer for.

In a world where anything can be tailored-made and customizable, we want to empower each employee so they can build a career that looks like them, that can change and grow along with their ambitions and aspirations.

Chivot: How can AI be used to address issues such as discrimination and gender bias in hiring practices?

De Raphélis Soissan: Le Monde, a well-known French newspaper, published an article a few weeks ago about discrimination and gender bias in hiring. According to the journalist, it is almost impossible for a human being to assess skills without any bias. Yet it is possible for AI.

Even though you remove names, diplomas, pictures, and addresses, a study has proved that bias still exist. The words that you choose, the hobbies that you have—that’s enough for a human to build a mental picture of you and of your social background. Algorithms are blind to all that.

You asked what kind of information we feed our algorithms with. The real question here is what we don’t give them. Name, gender, age, addresses, pictures, or school names are never taken into account for any recommendation. Our matches are blind to bias. They are based on skills only.

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