Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "16071"
  #_source: array:26 [
    "id" => "16071"
    "slug" => "16071-from-policy-to-practice-research-directions-for-trustworthy-and-responsible-artificial-intelligence-by-design"
    "yearMonth" => "2025-10"
    "year" => "2025"
    "title" => "From Policy to Practice: Research Directions for Trustworthy and Responsible Artificial Intelligence “By Design”"
    "description" => "KRISHNAN, R., LALOR, J.P., PRAT, N. et ABBASI, A. (2025). From Policy to Practice: Research Directions for Trustworthy and Responsible Artificial Intelligence “By Design”. <i>IEEE Intelligent Systems</i>, 40(5), pp. 45-51."
    "authors" => array:4 [
      0 => array:3 [
        "name" => "PRAT Nicolas"
        "bid" => "B00000434"
        "slug" => "prat-nicolas"
      ]
      1 => array:1 [
        "name" => "KRISHNAN Ramayya"
      ]
      2 => array:1 [
        "name" => "LALOR John P."
      ]
      3 => array:1 [
        "name" => "ABBASI Ahmed"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:5 [
      0 => "intelligence artificielle"
      1 => "politique"
      2 => "conception"
      3 => "intelligence artificielle responsable"
      4 => "intelligence artificielle générative"
    ]
    "updatedAt" => "2025-11-20 10:15:04"
    "publicationUrl" => "https://doi.org/10.1109/MIS.2025.3598960"
    "publicationInfo" => array:3 [
      "pages" => "45-51"
      "volume" => "40"
      "number" => "5"
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Les progrès rapides dans le développement et l'adoption de l'intelligence artificielle (IA) ont accéléré le besoin d'une IA fiable et responsable (IAFR). Les politiques et cadres nationaux/internationaux de gouvernance et de gestion des risques liés à l'IA ont identifié un ensemble de principes fondamentaux pour l’IAFR, notamment l'équité, la sûreté, la confidentialité, la sécurité, la transparence, l'explicabilité et le déploiement responsable. Les processus/outils d'IA responsable (PIAR) sont des solutions conçues pour opérationnaliser et mettre en œuvre ces principes, servant de couche intermédiaire entre les principes et les processus réels intégrant l'IA. Ces dernières années, la conception des PIAR est apparue comme une voie importante pour les chercheurs en informatique et sciences sociales, les praticiens et les politiques. Nous mettons en évidence six axes de recherche importants pour la conception des PIAR. A l'aide d'une étude de cas réelle, nous décrivons l'importance de chaque axe de recherche et illustrons les défis actuels."
      "en" => "Rapid advancements in the development and adoption of artificial intelligence (AI) have accelerated the need for trustworthy and responsible AI (TRAI). National/ international AI governance and risk management policies and frameworks have identified a core set of tenets for TRAI, including fairness, safety, privacy, security, transparency, explainability, and responsible deployment. Responsible AI processes/tools (RAPs) are solutions designed to operationalize and implement the tenets, serving as a middle layer between the tenets and real-world AI-embedded processes. In recent years, the design of RAPs has emerged as an important avenue for computational and social science researchers, practitioners, and policymakers. We highlight six important research directions for the design of RAPs. Using a real-world case study, we describe the importance of each research direction and illustrate current challenges."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2025-12-05T13:21:47.000Z"
    "docTitle" => "From Policy to Practice: Research Directions for Trustworthy and Responsible Artificial Intelligence “By Design”"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/prat-nicolas">PRAT Nicolas</a>, KRISHNAN Ramayya, LALOR John P., ABBASI Ahmed"
    "docDescription" => "<span class="document-property-authors">PRAT Nicolas, KRISHNAN Ramayya, LALOR John P., ABBASI Ahmed</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2025</span>"
    "keywordList" => "<a href="#">intelligence artificielle</a>, <a href="#">politique</a>, <a href="#">conception</a>, <a href="#">intelligence artificielle responsable</a>, <a href="#">intelligence artificielle générative</a>"
    "docPreview" => "<b>From Policy to Practice: Research Directions for Trustworthy and Responsible Artificial Intelligence “By Design”</b><br><span>2025-10 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1109/MIS.2025.3598960" target="_blank">From Policy to Practice: Research Directions for Trustworthy and Responsible Artificial Intelligence “By Design”</a>"
  ]
  +lang: "en"
  +"_score": 8.689194
  +"_ignored": array:2 [
    0 => "abstract.en.keyword"
    1 => "abstract.fr.keyword"
  ]
  +"parent": null
}