scholarly journals In AI We Trust: Ethics, Artificial Intelligence, and Reliability

2020 ◽  
Vol 26 (5) ◽  
pp. 2749-2767
Author(s):  
Mark Ryan

Abstract One of the main difficulties in assessing artificial intelligence (AI) is the tendency for people to anthropomorphise it. This becomes particularly problematic when we attach human moral activities to AI. For example, the European Commission’s High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI (HLEG AI Ethics guidelines for trustworthy AI, 2019, p. 35). Trust is one of the most important and defining activities in human relationships, so proposing that AI should be trusted, is a very serious claim. This paper will show that AI cannot be something that has the capacity to be trusted according to the most prevalent definitions of trust because it does not possess emotive states or can be held responsible for their actions—requirements of the affective and normative accounts of trust. While AI meets all of the requirements of the rational account of trust, it will be shown that this is not actually a type of trust at all, but is instead, a form of reliance. Ultimately, even complex machines such as AI should not be viewed as trustworthy as this undermines the value of interpersonal trust, anthropomorphises AI, and diverts responsibility from those developing and using them.

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Charlotte Stix

AbstractIn the development of governmental policy for artificial intelligence (AI) that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: (1) preliminary landscape assessments; (2) multi-stakeholder participation and cross-sectoral feedback; and, (3) mechanisms to support implementation and operationalizability.


Author(s):  
Andrea Renda

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.


First Monday ◽  
2021 ◽  
Author(s):  
Gry Hasselbalch

This article makes a case for a data interest analysis of artificial intelligence (AI) that explores how different interests in data are empowered or disempowered by design. The article uses the EU High-Level Expert Group on AI’s Ethics Guidelines for Trustworthy AI as an applied ethics approach to data interests with a human-centric ethical governance framework and accordingly suggests ethical questions that will help resolve conflicts between data interests in AI design


2020 ◽  
pp. 1-15
Author(s):  
Stefan LARSSON

Abstract This article uses a socio-legal perspective to analyze the use of ethics guidelines as a governance tool in the development and use of artificial intelligence (AI). This has become a central policy area in several large jurisdictions, including China and Japan, as well as the EU, focused on here. Particular emphasis in this article is placed on the Ethics Guidelines for Trustworthy AI published by the EU Commission’s High-Level Expert Group on Artificial Intelligence in April 2019, as well as the White Paper on AI, published by the EU Commission in February 2020. The guidelines are reflected against partially overlapping and already-existing legislation as well as the ephemeral concept construct surrounding AI as such. The article concludes by pointing to (1) the challenges of a temporal discrepancy between technological and legal change, (2) the need for moving from principle to process in the governance of AI, and (3) the multidisciplinary needs in the study of contemporary applications of data-dependent AI.


Author(s):  
Anri Leimanis

Advances in Artificial Intelligence (AI) applications to education have encouraged an extensive global discourse on the underlying ethical principles and values. In a response numerous research institutions, companies, public agencies and non-governmental entities around the globe have published their own guidelines and / or policies for ethical AI. Even though the aim for most of the guidelines is to maximize the benefits that AI delivers to education, the policies differ significantly in content as well as application. In order to facilitate further discussion about the ethical principles, responsibilities of educational institutions using AI and to potentially arrive at a consensus concerning safe and desirable uses of AI in education, this paper performs an evaluation of the self-imposed AI ethics guidelines identifying the common principles and approaches as well as drawbacks limiting the practical and legal application of the policies.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mark Ryan ◽  
Bernd Carsten Stahl

Purpose The purpose of this paper is clearly illustrate this convergence and the prescriptive recommendations that such documents entail. There is a significant amount of research into the ethical consequences of artificial intelligence (AI). This is reflected by many outputs across academia, policy and the media. Many of these outputs aim to provide guidance to particular stakeholder groups. It has recently been shown that there is a large degree of convergence in terms of the principles upon which these guidance documents are based. Despite this convergence, it is not always clear how these principles are to be translated into practice. Design/methodology/approach In this paper, the authors move beyond the high-level ethical principles that are common across the AI ethics guidance literature and provide a description of the normative content that is covered by these principles. The outcome is a comprehensive compilation of normative requirements arising from existing guidance documents. This is not only required for a deeper theoretical understanding of AI ethics discussions but also for the creation of practical and implementable guidance for developers and users of AI. Findings In this paper, the authors therefore provide a detailed explanation of the normative implications of existing AI ethics guidelines but directed towards developers and organisational users of AI. The authors believe that the paper provides the most comprehensive account of ethical requirements in AI currently available, which is of interest not only to the research and policy communities engaged in the topic but also to the user communities that require guidance when developing or deploying AI systems. Originality/value The authors believe that they have managed to compile the most comprehensive document collecting existing guidance which can guide practical action but will hopefully also support the consolidation of the guidelines landscape. The authors’ findings should also be of academic interest and inspire philosophical research on the consistency and justification of the various normative statements that can be found in the literature.


2020 ◽  
Vol 11 (3) ◽  
pp. 683-692
Author(s):  
Giovanni SILENO

This short paper aims to unpack some of the assumptions underlying the “Policy and Investment Recommendation for Trustworthy AI” provided by the High-Level Expert Group on Artificial Intelligence (AI) appointed by the European Commission. It elaborates in particular on three aspects: on the technical-legal dimensions of trustworthy AI; on what we mean by AI; and on the impact of AI. The consequent analysis results in the identification, amongst others, of three recurrent simplifications, respectively concerning the definition of AI (sub-symbolic systems instead of “intelligent” informational processing systems), the interface between AI and institutions (neatly separated instead of continuity) and a plausible technological evolution (expecting a plateau instead of a potentially near-disruptive innovation).


2019 ◽  
Author(s):  
Michael Veale

Cite as Michael Veale, ‘A Critical Take on the Policy Recommendations of the EU High-Level Expert Group on Artificial Intelligence’ (2020) __ European Journal of Risk Regulation __. doi:10/ggjdjsThe European Commission recently published the policy recommendations of its ‘High-Level Expert Group on Artificial Intelligence’: a heavily anticipated document, particularly in the context of the stated ambition of the new Commission President to regulate in that area. This essay argues that these recommendations have significant deficits in a range of areas. It analyses a selection of the Group’s proposals in context of the governance of artificial intelligence more broadly, focussing on issues of framing, representation and expertise, and on the lack of acknowledgement of key issues of power and infrastructure underpinning modern information economies and practices of optimisation.


2020 ◽  
pp. 1-10 ◽  
Author(s):  
Michael VEALE

The European Commission recently published the policy recommendations of its “High-Level Expert Group on Artificial Intelligence”: a heavily anticipated document, particularly in the context of the stated ambition of the new Commission President to regulate in that area. This article argues that these recommendations have significant deficits in a range of areas. It analyses a selection of the Group’s proposals in context of the governance of artificial intelligence more broadly, focusing on issues of framing, representation and expertise, and on the lack of acknowledgement of key issues of power and infrastructure underpinning modern information economies and practices of optimisation.


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