« Facilitateur en Intelligence Artificielle/en » : différence entre les versions
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Dernière version du 9 juillet 2024 à 14:46
== What is the role of the AI facilitator? The role of the AI facilitator is to bring together cybersecurity teams and data scientists:
- Leading the cross-functional cyber and data science community (AI for and through cyber);
- Identify ML opportunities and benefits for cyber teams in their activities (cyber and non-cyber);
- Raise awareness of cyber issues among data scientists, and even facilitate access to or generation of cyber data;
- Promote the implementation of IA Security champions on the operational side and provide them with intelligence.
== His day-to-day activities Working directly with the CISO, you will be responsible for facilitating exchanges, interaction and collaboration with the community of data scientists. His or her cross-disciplinary knowledge of cybersecurity and interpersonal skills will enable him or her to :
- Using a community of data scientists and cybersecurity teams to promote exchanges and news on cyber needs in the field
- Make an inventory of the skills required and the cyber security expectations of the data scientist community in order to make them operational (training, tools, contacts, etc.)
- Make cyber security teams aware of the specific issues/capabilities related to AI (attacks on companies' AI or possible uses of AI on the cyber side);
- Facilitate the creation and implementation of cyber security measures to protect AI systems. Then promote their implementation.
- Contribute to the implementation of "cyber" business metrics for evaluating the performance of ML models;
- Relaying intelligence on incidents and public research papers - finding and promoting associated training - on attack techniques exploiting AI to AI sec champions and the community.
Expected skills
Organisational skills
- Control of the organisation ;
- Mastery of the company's processes;
- Ability to analyse cyber issues, quantify their impact and draw up a project budget;
- Ability to communicate with the cyber business at multiple levels (Operations / Management / Strategy / Budget / CISO).
Data science skills
- Understanding the data used for cyber security
- Data manipulation and transformation
- Practical ML knowledge (ML development and integration)
Cybersecurity skills
- Be a cybersecurity professional
- Have skills in the field of data security
- Secure data pipelines