Artificial Intelligence

The use of Artificial Intelligence (AI) in financial markets requires a balanced and proactive approach. The distinction between weak and strong AI systems highlights the need to adapt the sector legislation with respect to the sudden growth of the autonomy of the algorithms. The challenge is to balance natural technological development with market security. The balancing of human responsibility with the socialization of damages and with daring innovative solutions, such as the recognition of the legal personality of advanced AI systems or “smart law” hypotheses, would help jurists to manage, with less uncertainty, the new dynamics of financial markets.

This article summarises the approval process of the Artificial Intelligence Act Proposal, particularly concerning high-risk predictive algorithms, to assess the effect of this legislative change.

This contribution summarises the main amendments adopted by the European Parliament during its first reading of the EU’s Proposal for a Regulation on Artificial Intelligence (AI Act). It outlines the impact of this Act, if adopted with such amendments, on automated administrative decision-making (“adm-ADM”), and examines the margin Member States will have to supplement such provisions in their respective national administrative procedure acts. It concludes that the AI Act is a necessary piece of legislation and that, if adopted with some of the Parliament’s amendments, it will adequately regulate the development and use of AI systems by European public authorities, setting a high regulatory standard that can be reinforced by national legislators.

This paper examines the implementation of artificial intelligence in decision-making processes within public administration, with a focus on addressing the challenges of transparency, accountability, and the intelligibility of AI-generated decisions. The paper discusses the importance of imputability in decisions made with deep learning algorithms. It emphasises that by granting public administrations full control over the training dataset, source code, and knowledge base, the imputability of the decision can be ensured. This control enables administrations to validate the relevancy and accuracy of the algorithm's training data, address potential biases, and comply with legal and ethical requirements. The paper then proposes the use of Large Language Models (LLM) as a solution to enhance the transparency and motivation behind AI-assisted decisions. It highlights that LLMs can generate articulate and comprehensible textual outputs that closely resemble human-generated decisions, allowing for a deeper understanding of the decision-making process. Furthermore, the paper emphasises the significance of providing access to the training dataset, source code, and individual administrative precedents to enhance transparency and accountability. It argues that by offering these components, stakeholders can evaluate the validity and reliability of AI-assisted decisions, fostering trust in the decision-making process.

Public administration is immersed in a major technological disruption that raises interesting questions and legal debates. The use of artificial intelligence is undoubtedly one of them. However, this phenomenon must be analysed in the context of the general transformation that the public sector is undergoing, the so-called “public governance”, with all that this implies, in short, a new relationship between citizens and public authorities, which marks the scenario in which the current Administration must act. Bearing in mind that the very essence of administrative law hinges on a constant duality, this paper analyses the use of artificial intelligence in the public sector, seeking the eternal balance between efficiency and guarantees.

This article addresses the legal order of the digital sphere, focusing on the constitutional dimension. In particular, the new freedoms that have come into being with the advent of technology, especially digital platforms. There are doubts about the effectiveness of regulatory intervention, such as that attempted by the EU whose purpose seems to focus on sanctions for violations rather than on promoting freedoms. The article emphasizes the positives rather than the negatives of a digital legal order, while recognizing the problems with the digital market where the large companies exercise a dominant and anti-competitive position. The article also addresses the issue of democracy on the Internet and the challenge of misinformation.

This contribution analyses the German legal framework concerning automated decision-making systems. Public administration in Germany uses automated decision-making systems primarily to adopt partially or fully automated administrative acts. Accordingly, this paper focuses on automated administrative acts, however, it also discusses the first comprehensive regulation of artificial intelligence enacted by a German “Bundesland”. The paper approaches the topic from three different perspectives: The German legislative framework, case-law and soft-law concerning automated decision-making systems.

Automated decision-making has been discussed in Austrian administrative law for more than 40 years. The focus has always been on the administrative act (in the sense of a formal individual decision) and the pertaining procedure. In this area, there are established principles, although new technologies raise new questions. Beyond the administrative act, we are still very much in the dark.

This article aims at analysing the decision-automation-systems currently used by public administrations in Italy. After an analysis of the legal framework, the different systems are classified and illustrated: in particular, the case of the so-called “good school” algorithm is discussed. The conclusions dwell on the reason for the scarce use of these tools in the Italian landscape, also due to the slow and uneven digitisation of the public sector.

Jurisdictions within the EU and countries around the world are beginning to regulate the use of public Automated Decision Making (ADM). The legal framework thereof differs considerably, and its development is at an early stage. This contribution sets out a possible comparative research framework, with other words elements to compare the different solutions developed by the legal systems in the face of challenges of ADM.