Conversational AI: Mind The Knowledge Gap
Using NLP, NLG, Knowledge Graphs and Deep learning technologies makes it possible to build Conversational AI systems. Gaps in knowledge used by such a system are a critical challenge in achieving high accuracy and realistic Conversational AI. The knowledge gaps exist due to the lack of knowledge about the subject of conversation, or the knowledge the AI systems are built on becomes outdated. In this talk, Prof Thakker will present his research as part of an Innovate UK-funded project for building a Conversational AI system to support UK Immigration casework. Immigration law advice is a specialist domain, and underlying subject knowledge frequently changes due to changes in the immigration rules. Such knowledge dynamism is a common characteristic in other specialist domains such as other areas of law advice, financial advice, and medical advice. Prof Thakker will present work as part of this project in building NLP, NLG and Knowledge graph pipelines for conversational AI and explore techniques to overcome knowledge gap challenges. He will share lessons learnt with broader applicability in other domains.
Professor Dhaval Thakker is a Full Professor in Artificial Intelligence and the Internet of Things (IoT) at the University of Hull, UK. Dhaval has over fifteen years of working experience in the European Union(EU) and industrial projects researching and delivering innovative solutions. He has been a PI on projects with over €1m funding from Innovate UK, and European Commission. This includes the SCORE (Smart Cities and Open Data REuse) project with nine European cities and three other Universities and an Innovate UK-funded project on “Artificial Intelligence and UK Immigration law”, where his research focuses on Conversational AI.