{"id":9442,"date":"2025-11-19T08:44:16","date_gmt":"2025-11-19T13:44:16","guid":{"rendered":"https:\/\/www.confianceia.ca\/scientific-roadmap-framework\/"},"modified":"2026-01-30T22:12:15","modified_gmt":"2026-01-31T03:12:15","slug":"scientific-roadmap-framework","status":"publish","type":"page","link":"https:\/\/www.confianceia.ca\/en\/scientific-roadmap-framework\/","title":{"rendered":"SCIENTIFIC ROADMAP FRAMEWORK"},"content":{"rendered":"\t\t
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A STRUCTURED VISION FOR TRUSTWORTHY AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Confiance IA\u2019s scientific roadmap charts a path to accelerate the adoption and industrialization of sustainable, responsible, and secure artificial intelligence technologies.
Structured over five years, it directs research, development, and transfer activities through well-defined strategic pillars and tangible outputs that benefit companies and organizations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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THREE PRIORITY PILLARS<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Ethical and Responsible AI<\/h3>\nObjective : Embed principles of ethics and responsibility into the development and operation of AI systems.\n
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  • Consent, privacy, and data protection.<\/li>\n \t
  • Model explainability and transparency.<\/li>\n \t
  • Prevention of bias and algorithmic discrimination.<\/li>\n \t
  • Human-centered tools that support social acceptability.<\/li>\n \t
  • Certification and ethical governance frameworks for AI systems.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    Safe and Secure AI<\/h3>Objective: Ensure the robustness and reliability of critical systems that incorporate AI.\n
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    • Defense against attacks and strengthened model resilience.<\/li>\n \t
    • Continuous updates and adaptation to changing environments.<\/li>\n \t
    • Monitoring and anomaly detection to guard against system drift.<\/li>\n
    • Enhancement of data quality and of formal validation techniques.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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      Sustainable AI<\/h3>\nObjective : Reduce AI\u2019s environmental footprint without compromising its capabilities.\n
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      • Tracking and reducing energy consumption across the entire lifecycle.<\/li>\n \t
      • Development of energy-efficient techniques (model compression, distributed learning).<\/li>\n \t
      • Optimization of resource use and balancing sustainability, performance, and fairness.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        AN EVOLVING ROADMAP<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        Each strategic pillar is broken down into timelines<\/strong> with clearly defined deliverables.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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        • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tM\u00e9thodes de compression \u00e9nerg\u00e9tique des mod\u00e8les.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
        • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tInterpretability and explainability tools.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
        • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tBias and algorithmic-fairness indicators.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
        • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tMetrics and monitoring tools for deployed systems.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
        • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tFrugal and hybrid learning methods that adapt to new situations.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          The phased planning approach described here helps move from foundational research to practical solutions for organizations, developed jointly with industry and academic collaborators.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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          a shared initiative<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          The roadmap is meant to be dynamic: it continually evolves to reflect emerging needs, new regulatory challenges, and real-world business use cases. It embodies Confiance IA\u2019s commitment to building AI that is trustworthy by design, for the benefit of society and the economy.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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          \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

          Confiance IA is an industry consortium that was established in 2023. It was initiated by the Montreal industrial ecosystem, with the support of the Minist\u00e8re de l’\u00c9conomie, de l’Innovation et de l’\u00c9nergie (MEIE).<\/p>\n","protected":false},"author":3465,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-9442","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nSCIENTIFIC ROADMAP FRAMEWORK - Confiance IA<\/title>\n<meta name=\"description\" content=\"Confiance IA is an industry consortium that was established in 2023. 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