{"id":136883,"date":"2026-06-23T21:03:54","date_gmt":"2026-06-23T20:03:54","guid":{"rendered":"https:\/\/univga.org\/ia-donnees-personnelles-questions\/"},"modified":"2026-06-25T09:56:12","modified_gmt":"2026-06-25T08:56:12","slug":"ai-personal-data-questions","status":"publish","type":"post","link":"https:\/\/univga.org\/en\/ia-donnees-personnelles-questions\/","title":{"rendered":"Are your personal data safe with AI?"},"content":{"rendered":"<h2>Why read this article?<\/h2>\n<p>Imagine a bank advisor copying a client's statement into an artificial intelligence (AI) assistant to summarize their credit profile. The summary arrives quickly, and it seems useful. But one question remains open: is the client's information retained by the tool? Can it be read by someone else? Can it be used to improve the service without clear consent?<\/p>\n<p>Also imagine a hospital or university wanting to classify patient or student files. Should names, grades, diagnoses, identification documents, and addresses be masked before use? Who verifies that these files are not stored longer than necessary? Before asking an AI to 'save time,' one must know what it does with your data.<\/p>\n<h2>What is it, concretely?<\/h2>\n<p>Knowing whether an AI protects your data means checking if it treats your information like a bank treats its clients' money. A simple phrase: before using an AI, ask seven questions about what it receives, why it receives it, who can access it, where the data is stored, how long it remains, how it is rendered unreadable to unauthorized persons, and whether it is used to train the tool. The issue is not only technical: it is also a legal, financial, and trust risk.<\/p>\n<h2>Why this is important for you<\/h2>\n<ul>\n<li><strong>Banks:<\/strong> A statement, transaction history, or client identification document should be treated as sensitive assets, not just as simple text to copy and paste.<\/li>\n<li><strong>Administrations:<\/strong> Civil status, tax, or land files require clear traceability: who accesses what, when, and for what reason?<\/li>\n<li><strong>Universities:<\/strong> Grades, disciplinary records, unpublished theses, and student information must be anonymized before analysis.<\/li>\n<li><strong>Hospitals:<\/strong> A diagnosis or test result can expose a person to medical, social, insurance, or legal harm.<\/li>\n<li><strong>Small and medium-sized enterprises (SMEs):<\/strong> Human resources data, salaries, CVs, evaluations, or geolocation should not feed opaque decisions.<\/li>\n<\/ul>\n<aside class=\"veille-keytakeaway\">\n<p class=\"veille-keytakeaway__label\">To remember<\/p>\n<ul>\n<li>A useful AI can become risky if it receives too much data or retains it for too long.<\/li>\n<li>The seven key questions focus on purpose, access, storage, duration, protection, training, and compliance.<\/li>\n<li>The best protection starts before sending the file: minimize, mask, and frame the uses.<\/li>\n<\/ul>\n<\/aside>\n<h2>Views from Gabon and Africa<\/h2>\n<p>In Gabon, imagine an SME in Libreville wanting to use an online AI to analyze client files, or a university wishing to sort enrollment files. The first question should not be: 'Is the tool efficient?' but: 'Where do the data go?'. Gabonese law provides for an authority responsible for the protection of personal data and privacy, the Authority for the Protection of Personal Data and Privacy (APDPVP). It also stipulates that a transfer of personal data to another state requires authorization and a sufficient level of protection. For Francophone Africa, the issue is clear: an imported AI must comply with local rules, not just the supplier's conditions.<\/p>\n<aside class=\"veille-univga-voice\">\n<p class=\"veille-univga-voice__label\">UNIVGA Viewpoint<\/p>\n<p>For the Virtual University of Gabon (UNIVGA), the right question is not to reject AI, but to learn how to use it methodically. In management, finance, health, logistics, or human resources, the key skill becomes the ability to ask the right questions before sharing sensitive files.<\/p>\n<\/aside>\n<aside class=\"veille-univga-encart\">\n<p class=\"veille-univga-encart__label\">Training at UNIVGA<\/p>\n<p>Students and professionals can enhance their skills in management, digital technology, and information protection to better navigate the use of AI in their organizations.<\/p>\n<p><a href=\"\/en\/formations\/\">Discover the training<\/a><\/aside>\n<h2>To go further<\/h2>\n<div class=\"veille-tech-deep\">\n<p>For digital teams, several benchmarks exist. The National Institute of Standards and Technology Artificial Intelligence Risk Management Framework (NIST AI RMF) helps structure risks. The International Organization for Standardization\/International Electrotechnical Commission (ISO\/IEC) 42001 standard organizes AI management. The Open Worldwide Application Security Project (OWASP) Top 10 for Large Language Model Applications addresses the risks of large language models (LLM), including prompt injection. Microsoft Presidio and Google Cloud Sensitive Data Protection, also known as Data Loss Prevention Application Programming Interface (DLP API), detect or mask sensitive data. Open Policy Agent (OPA) automates certain access rules.<\/p>\n<\/div>\n<h2>Sources<\/h2>\n<ol>\n<li><a href=\"https:\/\/www.cnil.fr\/fr\/tenir-compte-de-la-protection-des-donnees-dans-la-collecte-et-la-gestion-des-donnees\">CNIL \u2014 AI: consider data protection in data collection and management<\/a><\/li>\n<li><a href=\"https:\/\/cnil.fr\/sites\/default\/files\/2024-03\/cnil_guide_securite_personnelle_2024.pdf\">CNIL \u2014 Guide to Personal Data Security 2024<\/a><\/li>\n<li><a href=\"https:\/\/www.nist.gov\/publications\/artificial-intelligence-risk-management-framework-ai-rmf-10\">NIST \u2014 Artificial Intelligence Risk Management Framework AI RMF 1.0<\/a><\/li>\n<li><a href=\"https:\/\/www.iso.org\/standard\/42001\">ISO \u2014 ISO\/IEC 42001:2023 AI management systems<\/a><\/li>\n<li><a href=\"https:\/\/owasp.org\/www-project-top-10-for-large-language-model-applications\">OWASP \u2014 Top 10 for Large Language Model Applications<\/a><\/li>\n<li><a href=\"https:\/\/www.ibm.com\/reports\/data-breach?ce=ISM0484\">IBM \u2014 Cost of a Data Breach Report 2025<\/a><\/li>\n<li><a href=\"https:\/\/extranet.who.int\/cpcd\/sites\/default\/files\/public_file_repository\/GAB_Gabon_Loi-No-025-2023-portant-modification-de-la-loi-no-001-2011-du-25-septembre-2011-relative-a-la-protection-des-donnees-a-caractere-personnel_2023.pdf\">Official Journal of Gabon \u2014 Law No. 025\/2023 on Personal Data<\/a><\/li>\n<li><a href=\"https:\/\/au.int\/pt\/node\/29560\">African Union \u2014 Convention on Cyber Security and Personal Data Protection<\/a><\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"<p>Bank, hospital, university: before entrusting a file to artificial intelligence, here are the key questions to avoid a data leak.<\/p>","protected":false},"author":6945,"featured_media":136884,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1969],"tags":[1971,1981,1979,1982,1980],"offerexpiration":[],"class_list":["post-136883","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-veille-technologique","tag-cybersecurite","tag-donnees-personnelles","tag-gabon","tag-gouvernance","tag-intelligence-artificielle"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.9 (Yoast SEO v28.6) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Donn\u00e9es personnelles et IA : les questions \u00e0 poser | UNIVGA<\/title>\n<meta name=\"description\" content=\"Avant d&#039;utiliser une intelligence artificielle, d\u00e9couvrez les 7 questions simples \u00e0 poser pour prot\u00e9ger clients, patients, \u00e9tudiants et salari\u00e9s au quotidien.\" 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