{"id":7946,"date":"2025-12-12T10:18:06","date_gmt":"2025-12-12T09:18:06","guid":{"rendered":"https:\/\/www.kode-solutions.net\/?p=7946"},"modified":"2026-01-30T09:55:43","modified_gmt":"2026-01-30T08:55:43","slug":"from-black-box-to-glass-box-rendere-ia-trasparente-e-comprensibile","status":"publish","type":"post","link":"https:\/\/www.kode-solutions.net\/it\/from-black-box-to-glass-box-rendere-ia-trasparente-e-comprensibile\/","title":{"rendered":"From Black Box to Glass Box: rendere l\u2019IA trasparente e comprensibile"},"content":{"rendered":"\r\n\t
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From Black Box to Glass Box: rendere l\u2019IA trasparente e comprensibile<\/h1>\n\n\t\t
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Kode s.r.l.<\/div>\r\n\t\t\t\t<\/div>\r\n\t\t\t\t
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12.12.2025<\/div>\r\n\t\t\t\t<\/div>\r\n\t\t\t\t\t\t\t\t\t
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Alla FAIR General Conference presentat il progetto  From Black Box to Glass Box\u201d<\/strong> (BigBox), sviluppato da Kode s.r.l.<\/strong> in collaborazione con il KDD Lab \u2013 Universit\u00e0 di Pisa<\/strong> nell\u2019ambito dei bandi a cascata FAIR del PNRR<\/strong><\/p><\/div>\r\n\t\t\t<\/div>\r\n\t\t<\/div>\r\n\t<\/div>\n\n\n\n

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Roma, 12 Dicembre 2025 – Ieri alla FAIR General Conference 2025 Andrea Spinelli e Chiara Baraglia di Kode hanno presentato il progetto \u201cFrom Black Box to Glass Box\u201d<\/strong> (BigBox), sviluppato da Kode<\/strong> in collaborazione con il KDD Lab \u2013 Universit\u00e0 di Pisa<\/strong> nell\u2019ambito dei bandi a cascata FAIR del PNRR \u2013 SPOKE 1 Human-Centered AI<\/strong>, ha come obiettivo principale la realizzazione di FairXAI<\/strong>, un framework modulare e scalabile per la spiegabilit\u00e0 dei modelli di IA.<\/p>\n\n\n\n

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In un contesto in cui i modelli di intelligenza artificiale complessi sono sempre pi\u00f9 utilizzati in settori industriali, sanitari e finanziari, la trasparenza e la spiegabilit\u00e0 dei modelli<\/strong> diventano requisiti essenziali.<\/p>\n\n\n\n

Il progetto ha l\u2019obiettivo di fornire un framework modulare e scalabile che consente di spiegare, attraverso spiegazioni controfattuali basate su regole logiche, il funzionamento di modelli di intelligenza artificiale complessi, spesso percepiti come \u201cblack box\u201d.<\/p>\n\n\n\n

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Grazie a FairXAI<\/strong>, il framework sviluppato nell\u2019ambito del progetto, \u00e8 possibile ottenere spiegazioni chiare e verificabili dei processi decisionali dei modelli di IA<\/strong>, attraverso strumenti di ottimizzazione dei modelli XAI esistenti (in particolare LORE e derivati), anche da parte di utenti non esperti.<\/p>\n\n\n\n


L\u2019innovazione di FairXAI consiste non solo nella spiegabilit\u00e0 dei modelli, ma anche nella possibilit\u00e0 di integrare diversi metodi di interpretazione in un unico sistema flessibile, pronto per applicazioni industriali e di ricerca. La piattaforma si distingue per:<\/p>\n\n\n\n

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  • la sua architettura modulare ed estensibile,<\/strong><\/li>\n\n\n\n
  • la compatibilit\u00e0 multi-dominio<\/strong>, in grado di lavorare su dati tabellari, immagini e serie temporali,<\/li>\n\n\n\n
  • un\u2019interfaccia utente guidata<\/strong>, pensata per semplificare l\u2019interazione con algoritmi complessi, per facilitare l\u2019uso anche da parte di operatori non esperti.<\/li>\n<\/ul>\n\n\n\n
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    Tra i principali benefici attesi, il progetto favorisce la fiducia e l\u2019adozione dei sistemi di IA<\/strong> in ambiti sensibili come sanit\u00e0, finanza e manutenzione industriale, promuovendo la trasparenza e l\u2019uso responsabile<\/strong> dell\u2019intelligenza artificiale. Inoltre, FairXAI contribuisce alla diffusione di una cultura dell\u2019IA accessibile e interpretabile<\/strong>, includendo operatori e decisori nel processo di comprensione dei modelli.<\/p>\n\n\n\n

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    Il progetto dimostra come la ricerca e l\u2019innovazione possano trasformare la cosiddetta \u201cblack box\u201d dell\u2019IA in una glass box<\/strong>, accessibile e comprensibile, pronta per un uso sicuro e affidabile nei processi decisionali reali.<\/p>\n<\/div>\n\n\n\n

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

    From Black Box to Glass Box: progetto FAIR per rendere l’IA trasparente<\/p>\n","protected":false},"author":6,"featured_media":7947,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[157],"tags":[164,163,172],"class_list":["post-7946","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-it","tag-ai-2","tag-industry-5-0-2","tag-manufacturing"],"yoast_head":"\nKode alla FAIR General Conference<\/title>\n<meta name=\"description\" content=\"From Black Box to Glass Box: presentato il progetto di Kode nell\u2019ambito dei bandi a cascata FAIR per rendere l'AI trasparente\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kode-solutions.net\/it\/from-black-box-to-glass-box-rendere-ia-trasparente-e-comprensibile\/\" \/>\n<meta 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