Abstract

The Web of Data, the Internet of Things, and Industry 4.0 are converging, and society is challenged to ensure that appropriate regulatory responses can uphold the rule of law fairly and effectively in this emerging context. The challenge extends beyond merely submitting digital processes to the law. We contend that the 20th century notion of ‘legal order’ alone will not be suitable to produce the social order that the law should bring. The article explores the concepts of rule of law and of legal governance in digital and blockchain environments. We position legal governance from an empirical perspective, i.e., as an explanatory and validation concept to support the implementation of the rule of law in the new digital environments. As a novel contribution, this article (i) progresses some of the work done on the metarule of law and complements the SMART middle-out approach with an inside-out approach to digital regulatory systems and legal compliance models; (ii) sets the state-of-the-art and identifies the way to explain and validate legal information flows and hybrid agents’ behaviour; (iii) describes a phenomenological and historical approach to legal and political forms; and (iv) shows the utility of separating enabling and driving regulatory systems.

Highlights

  • This is a paper on the concept of legal governance and the convergence of technologies represented by the Web of Data (WoD), the Internet of Things (IoT), and Industry 4.0

  • Legal governance in the IoT and Industry 4.0 environments entails that (i) concepts such as ‘enforcement’, ‘implementation’, ‘effectivity’, ‘application’ and so forth, i.e., the concepts linked to the practical realization or performance of the law, and (ii) the concepts related to the system as a whole—for example, ‘validity’ or ‘legality’—should be empirically defined and used to create a specific regulatory mindset and toolkit for the IoT

  • Akata et al [132] recently launched a research agenda for hybrid intelligence, augmenting human intellect with collaborative, adaptive, responsible, and explainable Artificial Intelligence (AI). They define hybrid intelligence (HI) as “the combination of human and machine intelligence, augmenting human intellect and capabilities instead of replacing them and achieving goals that were unreachable by either humans or machines” [132] (p. 19) and formalize four challenges: (i) Collaborative HI: How do we develop AI systems that work in synergy with humans? (ii) Adaptive HI: How can these systems learn from and adapt to humans and their environment? (iii) Responsible HI: How do we ensure that they behave ethically and responsibly? (iv) Explainable HI: How can AI

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Legal governance in the IoT and Industry 4.0 environments entails that (i) concepts such as ‘enforcement’, ‘implementation’, ‘effectivity’, ‘application’ and so forth, i.e., the concepts linked to the practical realization or performance of the law, and (ii) the concepts related to the system as a whole—for example, ‘validity’ or ‘legality’—should be empirically defined and used to create a specific regulatory mindset and toolkit for the IoT. This allows metrics to be applied, offering in return more information about the system’s ability to adapt to its environment, to create a new one, and to sustain legal ecosystems.

A Changing Regulatory Framework
New Regulatory Challenges
The Emergence of LawTech Web Services
Socio-Legal Ecosystems
Legal Governance and the Limits of Legal Instruments
Phenomenology and Political History
Rule and Metarule of Law
Socio-Legal Governance for Hybrid Intelligence
Legal Compliance
Beyond the AI4People SMART Model for Legal Governance
Driving and Enabling Systems
Conclusions
Findings
A Research Agenda for Hybrid Intelligence
Full Text
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