Artificial Intelligence for Curbing the Economic Impact of COVID-19
New findings show how Knowledge Graph technology can address the impact of the COVID-19 outbreak on the network of Italian companies.
Together with his team, Emanuel Sallinger, head of the Knowledge Graph Lab and incoming Assistant Professor (from June 2020) of our research unit Databases and Artificial Intelligence, presents findings of the application of Automated Reasoning and Knowledge Graph technology to address the impact of the COVID-19 outbreak on the network of Italian companies and support the application of legal instruments for the protection of strategic companies from takeovers. This is part of several initiatives of the Central Bank of Italy in response to COVID-19 and involves prominent academic institutions such as the University of Oxford and Politecnico di Milano. It utilizes AI technology developed by TU Wien, the University of Oxford, and DeepReason.ai.
Addressing the Economic Crisis with AI
With rapidly rising unemployment rates, it has become clear that the economic effect of COVID-19 has impacted many people’s lives. Yet the economic problems of one company do not only affect their employees and shareholders; we know that companies form a complex network defined by a variety of relationships, among them ownership and control. Do these intricate relationships of companies lead to resilience that is the power to resist crises like we are observing right now, or do they lead to increased risk? The answer depends on a variety of factors, among them the diversity of economic activities, geography, and supply chains. For example, a conglomerate of companies where one of them is severely affected by the current crisis may be resilient. In contrast, a conglomerate of companies specialized in a particular economic sector may fail as a whole. How do we distinguish between such cases in general?
Answering such a question requires sophisticated information systems that bring together a wide variety of information. Critically, it also requires such systems to reason on top of these massive amounts of data intelligently. Knowledge Graphs are one such artificial intelligence system. Google initially coined the term Knowledge Graphs, but in recent years it has become a staple both in academia and in industry. Knowledge Graphs can represent knowledge about complex economic networks and their complex interactions. Also, they allow for automated reasoning at a large scale, allowing a person to gain insights from this knowledge.
Covid-19 and Economic Knowledge Graphs
In the COVID-19 outbreak, governments have applied progressive restrictions to production activities, permitting only those that are considered strategic or that provide essential services. This is particularly apparent in countries that have been stricken hard by the virus, with Italy being a significant example. Yet we know that companies are not just isolated entities: They organize themselves into intricate shareholding structures - forming company networks - distributing decision power and dividends in sophisticated schemes for various purposes. One tool from the Artificial Intelligence (AI) toolbox that is particularly effective in performing reasoning tasks on domains characterized by many entities highly interconnected with one another is Knowledge Graphs (KG). In this work, the researchers present a visionary opinion and report on ongoing work about the application of Automated Reasoning and Knowledge Graph technology to address the impact of the COVID-19 outbreak on the network of Italian companies and support the application of legal instruments for the protection of strategic companies from takeovers.
The Knowledge Graph Lab at TU Wien Informatics is part of the Database and Artificial Intelligence (DBAI) research unit at the Institute of Logic and Computation of the Faculty of Informatics. It is funded by the Vienna Science and Technology Fund WWTF under the Vienna Research Group scheme - “Vienna Research Group on Scalable Reasoning in Knowledge Graphs” (VRG18-013).