Descrizione del progetto
Semplificare il processo con cui le macchine spiegano le loro decisioni
Ai sensi dei regolamenti dell’Unione Europea, tutti i cittadini hanno il diritto di ricevere informazioni e spiegazioni su qualsiasi decisione che li riguardi. Ciò include le decisioni prese dai sistemi di intelligenza artificiale (IA) e significa che i sistemi informatici dovrebbero funzionare come previsto e fornire spiegazioni e ragioni trasparenti per le decisioni che prendono. Questo si chiama Explainable AI (XAI). Il progetto NL4XAI, finanziato dall’UE, formerà 11 ricercatori all’inizio della carriera per creare un sistema di supporto per l’IA (XAI), consentendogli di tradurre le sue conoscenze in un linguaggio naturale. Il progetto si baserà sulle potenzialità della generazione e dell’elaborazione del linguaggio naturale, della tecnologia di argomentazione e della tecnologia interattiva per XAI. Il risultato sarà collaudato e i risultati aggiunti al framework open source per XAI.
Obiettivo
According to Polanyi's paradox, humans know more than they can explain, mainly due to the huge amount of implicit knowledge they unconsciously acquire trough culture, heritage, etc. The same applies for Artificial Intelligence (AI) systems mainly learnt automatically from data. However, in accordance with EU laws, humans have a right to explanation of decisions affecting them, no matter who (or what AI system) makes such decision. NL4XAI will train 11 creative, entrepreneurial and innovative early-stage researchers (ESRs), who will face the challenge of making AI self-explanatory and thus contributing to translate knowledge into products and services for economic and social benefit, with the support of Explainable AI (XAI) systems. Moreover, the focus of NL4XAI is in the automatic generation of interactive explanations in natural language (NL), as humans naturally do, and as a complement to visualization tools. As a result, ESRs are expected to leverage the usage of AI models and techniques even by non-expert users. Namely, all their developments will be validated by humans in specific use cases, and main outcomes publicly reported and integrated into a common open source software framework for XAI that will be accessible to all the European citizens. In addition, those results to be exploited commercially will be protected through licenses or patents. It is worthy to note that we have selected some of the most prominent European researchers (from both academy and industry) in each of the related fundamental topics and created a joint high quality training program that can be seen as a pyramid with the main research objective (designing and building XAI models) on top. It will be achieved as result of jointly addressing the research objectives in the pyramid base (NL generation and processing for XAI; Argumentation Technology for XAI; Interactive Interfaces for XAI). ESRs are also to be trained in Ethical and Legal issues, as well as in transversal skills.
Campo scientifico
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Meccanismo di finanziamento
MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)Coordinatore
15782 Santiago De Compostela
Spagna