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Stampa Stampa
29

LE ALLUCINAZIONI DELL’IA GENERATIVA: QUANDO L’INTELLIGENZA ARTIFICIALE “INVENTA” LE FONTI


Il fenomeno delle citazioni fantasma nei modelli linguistici di ultima generazione

 di REDAZIONE

–  TORRE DI RUGGIERO (CZ) –  23 OTTOBRE 2024 –  Il fenomeno delle “allucinazioni” rappresenta una delle sfide più significative nell’ambito dell’intelligenza artificiale generativa, in particolare per quanto riguarda la produzione di testi accademici e scientifici.

Lo ha ribadito il prof. Francesco Pungitore, direttore tecnico dell’Osservatorio Nazionale Minori e IA che ha sede a Torre di Ruggiero, nel corso di un podcast online proposto ad una ampia platea di uditori.

Questo comportamento “problematico” dell’IA – ha spiegato Pungitore – che si manifesta quando i modelli linguistici generano informazioni apparentemente plausibili ma incorrette o inesistenti, sta sollevando serie riflessioni sia in ambito tecnologico che educativo.

IL MECCANISMO DELLE ALLUCINAZIONI

Le allucinazioni nei sistemi di IA generativa “non sono semplici errori casuali” ha affermato l’esperto, ma emergono dalle caratteristiche intrinseche dei modelli linguistici di grande scala (Large Language Models, LLM).

Questi sistemi, addestrati su vastissime quantità di dati testuali, apprendono pattern e correlazioni che permettono loro di generare testi coerenti e apparentemente autorevoli, ma non necessariamente veritieri.

“Il problema fondamentale – ha spiegato il prof. Pungitor – risiede nel fatto che questi modelli sono ottimizzati per produrre output plausibili e sintatticamente corretti, ma non sono intrinsecamente vincolati alla verità fattuale”.

IL CASO SPECIFICO DELLE CITAZIONI BIBLIOGRAFICHE

Particolarmente problematico è il fenomeno della generazione di citazioni bibliografiche fittizie. Gli LLM possono produrre riferimenti che sembrano perfettamente legittimi, completi di:

  • Autori plausibili
  • Titoli convincenti
  • Nomi di riviste esistenti
  • Anni di pubblicazione verosimili
  • Numeri di pagine e volumi coerenti

Tuttavia, quando si procede alla verifica, queste citazioni si rivelano spesso inesistenti.

IMPLICAZIONI PER LA RICERCA E L’EDITORIA

Le conseguenze di questo fenomeno sono potenzialmente serie per il mondo accademico e della ricerca. L’automatizzazione della produzione di testi scientifici, se non adeguatamente controllata, potrebbe portare alla proliferazione di:

  • Citazioni non verificabili
  • Collegamenti errati tra concetti e fonti
  • Attribuzioni incorrette di idee e scoperte

STRATEGIE DI MITIGAZIONE

La comunità scientifica sta sviluppando diverse strategie per affrontare questo problema:

  • Approcci tecnici
  • Implementazione di sistemi di verifica automatica delle citazioni
  • Sviluppo di modelli con maggiore “fedeltà alle fonti”
  • Creazione di database di riferimento per la validazione delle citazioni

LINEE GUIDA PROCEDURALI

  • Verifica manuale obbligatoria delle fonti citate
  • Documentazione esplicita dell’utilizzo di strumenti di IA
  • Protocolli di revisione specifici per contenuti generati da IA

PROSPETTIVE FUTURE

Nonostante le sfide attuali, gli esperti rimangono cautamente ottimisti. “Le allucinazioni nelle citazioni rappresentano un problema serio ma non insormontabile” ha concluso Francesco Pungitore.

“Lo sviluppo di nuove tecniche di addestramento e validazione potrebbe ridurre significativamente questo fenomeno nei prossimi anni”.

CONCLUSIONI

Il fenomeno delle allucinazioni generate dall’IA rappresenta una sfida significativa – è la riflessione posta dal prof. Francesco Pungitore – che richiede un approccio multiplo: tecnologico, procedurale e culturale.

La consapevolezza di questo problema è “il primo passo verso una sua gestione efficace, ma resta fondamentale mantenere un approccio critico e verificare sempre le fonti, indipendentemente dalla loro apparente autorevolezza”. 

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