When facts are not enough - explainable AI for automated fact-checking, additional insight and trust

Offentlig prosjektsammendrag

The issue of misinformation and disinformation is one of the hottest topics of the day. False information propagates fast, and manual fact-checking methods struggle to manage the current volume of false stories created, needing AI and deep tech solutions to level the battlefield. Factiverse’s mission is to automate detection of misinformation and deliberate disinformation, and provide a credibility check for any online information by using cutting-edge AI and NLP. The proposed project will integrate explanations of AI decisions and data sources into the company’s AI editor and software tools, catering to research, news production, and news consumption – thus adding to two crucial elements: speed and explainability. Today Factiverse’s algorithms are able to show whether a claim is disputed or not, however B2B-decision makers need credible insight into what decisions lie behind AI-models to detect biased data, lack of data or simply to tune algorithms. It is increasingly important for many industries to demystify the black box of AI-models. The foreseen solution will implement ML models which are agnostic to specific NLP tasks but provide explanations and are interpretable by design. When refining the use of AI-powered systems, it is also important to understand the risks of deploying a model even before user interaction. For this purpose, we have identified a gap in existing tools for debugging and monitoring ML models - arguing that explainability should be built into these tools. The project's research challenges are anchored with prospective future clients both from the media and financial industry. A particular focus is directed to curb the negative effects of misinformation and disinformation on sustainability and the green transition.