Core Projects - Human-Machine Interaction

The digital transformation sweeping across various sectors in the European Union (EU) presents both opportunities and challenges, particularly in the realm of cybersecurity. This research project aims to explore the intricate relationship between digital transformation and cybersecurity practices within strategic sectors in the EU. These sectors, including energy, defence, telecommunications, and healthcare, are crucial to the infrastructure and economy and carry significant geopolitical risks. The project is motivated by the urgent need to understand how digital transformation affects cybersecurity strategies and practices, especially in the context of evolving geopolitical landscapes.

Three central research questions guide this inquiry:

1) How does digital transformation influence cybersecurity practices in EU firms?

2) What are the potential risks and opportunities that digital transformation brings in relation to cybersecurity?

3) How do cybersecurity practices vary among EU countries, and what are the broader implications for the EU community?

This research project explores the influence of feedback complexity on learning outcomes in interactive settings, comparing the effectiveness of feedback from artificial intelligence (AI) algorithms with that from human counterparts. With the increasing use of AI algorithms for training in complex scenarios, the debate surrounding their efficacy necessitates a nuanced examination. The central hypothesis posits that, in certain contexts, feedback from an efficient algorithm may be too intricate for effective learning, potentially resulting in misinterpretation.

The study aims to identify essential characteristics that an algorithm should possess to provide optimal feedback. It challenges the assumption that feedback from an efficient algorithm is always informative, suggesting that feedback simplicity should be tailored to the strategic sophistication of the agent.

In practical terms, the project focuses on repeated strategic interactions involving two or more agents, where timely feedback influences learning outcomes. Experimental data will be collected through online experiments. The research builds on previous findings indicating that the type of feedback significantly impacts the learning process.

The project's outcomes are expected to provide valuable insights into the design of effective AI algorithms for educational and interactive applications. Understanding how feedback complexity influences learning is crucial in optimizing algorithmic interventions in human interactions.

Modern economies are shaped by global networks of firms collaborating across national borders. The so-called Global Value Chain can be decomposed into tasks performed by firms that engage in supplier-customer relationships, which can be managed only thanks to digital technologies. In fact, digital technologies paved the way for global economic integration since the mid-'80s. Nowadays, Artificial Intelligence (AI) is becoming essential to innovate supply chain management. According to a survey by IBM, 46% of supply chain executives anticipate that AI/cognitive computing and cloud applications will be their greatest investment areas in digital operations over the next three years.

Yet, most recently, changing geopolitical and economic scenarios show the fragility of global supply chains. The European Union elaborated the notion of an open strategic autonomy that informs many European policies, in which the resilience of supply chains is considered crucial. The need to secure strategic knowledge shared in global webs of buyer-supplier relationships is evident in the emergence of ICT services offered by private actors. Eventually, supply chains rely on a complex ecosystem of information, communications, and operational technology (ICT/OT), which entails various entities with multiple tiers of outsourcing, distribution routes, technology standards, laws, procedures, and practices that interact to design, manufacture, deploy, and maintain products and production processes on a global scale.

The aim of this project is:

- To acknowledge cyber-resilience status in Italy-based supply chains made of foreign and domestic companies often intertwined in complex webs of buyer-supplier relationships.

- To investigate the economic rationale for an organizational optimal response to cybersecurity along global supply chains with a theoretical and empirical perspective.

- To understand under which conditions a protocol can assess and mitigate cybersecurity risks while allowing for companies’ information sharing and maintaining competitive autonomy in the ICT/OT ecosystem.