Artificial intelligence in the European Union

Ulnicane, Inga

doi:10.4324/9780429262081-19

Cited by 36 publications

(22 citation statements)

References 24 publications

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“…Over the past few years, several state authorities and international and supranational organizations have begun to address how to govern AI through law and law-like measures. For instance, the European Commission (EC) has begun to elaborate on an approach that “places people at the centre of the development of AI (human centric AI) and encourages the use of this powerful technology to help solve the world’s biggest challenges” ( Ulnicane, 2022 , p.261). In a White paper on AI published in February 2020, EC outlined a risk-based common European regulatory framework to ensure “that new technologies are at the service of all Europeans—improving their lives while respecting their rights.” ( European Commission, 2020 , p.1).…”

Section: Resultsmentioning

confidence: 99%

“Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term

2022

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Introduction: “Democratizing” artificial intelligence (AI) in medicine and healthcare is a vague term that encompasses various meanings, issues, and visions. This article maps the ways this term is used in discourses on AI in medicine and healthcare and uses this map for a normative reflection on how to direct AI in medicine and healthcare towards desirable futures.Methods: We searched peer-reviewed articles from Scopus, Google Scholar, and PubMed along with grey literature using search terms “democrat*”, “artificial intelligence” and “machine learning”. We approached both as documents and analyzed them qualitatively, asking: What is the object of democratization? What should be democratized, and why? Who is the demos who is said to benefit from democratization? And what kind of theories of democracy are (tacitly) tied to specific uses of the term?Results: We identified four clusters of visions of democratizing AI in healthcare and medicine: 1) democratizing medicine and healthcare through AI, 2) multiplying the producers and users of AI, 3) enabling access to and oversight of data, and 4) making AI an object of democratic governance.Discussion: The envisioned democratization in most visions mainly focuses on patients as consumers and relies on or limits itself to free market-solutions. Democratization in this context requires defining and envisioning a set of social goods, and deliberative processes and modes of participation to ensure that those affected by AI in healthcare have a say on its development and use.

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Section: Resultsmentioning

confidence: 99%

“Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term

2022

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“…As AI has become a widely used technology in more industries, states have noticed the need to outline a legal framework indicating further directions for its development. This is how AI development strategies began to emerge, along with subsequent policies at both the EU and national level (Ulnicane, 2022). The main purpose of the article is to analyze national policies for AI development in the 27 EU countries as a complete overview of all EU countries active in the field of AI development policy.…”

Section: Methodsmentioning

confidence: 99%

The European map of artificial intelligence development policies: a comparative analysis

Woszczyna

Mania

2023

International Journal of Contemporary Management

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Objective The aim of this paper is to discuss the management aspect of artificial intelligence development policy by the national regulators of the 27 European Union (EU) member states. The solutions formulated by three of them—Germany, France (as a pioneers), and Poland—are analyzed in depth. Conclusions The obtained results allow us to conclude that out of 27 EU countries, only one has not yet prepared its strategic project on artificial intelligence (AI) development, while among the existing policies one can find significant differences in the approach to the matter of strategic management. Methodology The research methods used are content analysis and comparative analysis of selected source documents. In the course of the deliberations presented, key legal acts concerning the areas of AI and modern technologies are cited. Practical applications The presented work formulates a starting point for further research and directions of changes in the management of AI development policy. The attention of subsequent researchers should focus on the possibility of a detailed analysis of other documents published by EU member states, a comparison of policies of other countries across the world, and even an attempt to examine the global dimension of AI strategies. Originality The article addresses the problem of creating law only following, rather than preceding, the emergence of technological changes, the lack of systemic regulation of AI tools and mechanisms, as well as the absence of integrated forms of international cooperation with a strategic and long-term dimension.

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“…Researchers have considered the relative merits of legislatures, which are democratically responsive but have limited technical competency; government agencies, where the reverse is true; the common law tort system, which is reactive and factspecific, and international organizations, which could create a harmonized, global regulatory structure, but would have the limited dexterity that attempting to standardize global rules implies [55], [56]. Moreover, the underlying regulatory institutions may differ geographically, particularly if those regions are motivated by different geopolitical values (such as international competition or human-rights values) [57]- [59]. In short, there is no universally applicable governing institution for autonomous systems.…”

Section: Related Workmentioning

confidence: 99%

A Path Dependent Approach for Characterizing the Legal Governance of Autonomous Systems

Borson

2022

IEEE Access

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Autonomous systems promise significant improvements in many fields. These systems will be subject to legal governance requirements. The literature has largely focused on "autonomous governance" as a framework that is broadly applicable to autonomous devices regardless of the type of system (e.g., aviation or motor vehicles) at issue. While there are regulatory principles applicable to autonomous systems generally, an "autonomy-focused" approach is an inadequate lens to consider the governance of these systems. Rather, because autonomous systems are improvements of currently regulated complex systems, the regulation of autonomous elements will occur within those systems' preexisting regulatory framework. Accordingly, the nature of future autonomous regulation will likely depend on the preexisting features of that substantive system, rather than on an optimal approach divorced from that history, an attribute known in the social science literature as path dependency. In order to characterize diverse regulated systems with an eye toward assessing future autonomous developments, we develop a framework of regulatory approaches to identify specific features of the preexisting regulatory scheme for a given system. We then analyze that approach by examining three different regulatory regimes (aviation, motor vehicles, and medical devices), across two different continents, and consider how the same type of requirement, e.g., fail-safe systems, can lead to different types of regulations depending on the differing baseline framework.

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Artificial intelligence in the European Union

Cited by 36 publications

References 24 publications

“Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term

“Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term

The European map of artificial intelligence development policies: a comparative analysis

A Path Dependent Approach for Characterizing the Legal Governance of Autonomous Systems

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