scholarly journals Value Pluralism in the AI Ethics Debate – Different Actors, Different Priorities

2021 ◽  
Vol 29 ◽  
Author(s):  
Catharina Rudschies ◽  
Ingrid Schneider ◽  
Judith Simon
Keyword(s):  
Artificial Intelligence ◽  
Common Ground ◽  
Ethical Principles ◽  
Current Debate ◽  
Value Pluralism ◽  
Ai Ethics ◽  
Minimum Requirements ◽  
Ethics Guidelines ◽  
Private Actors ◽  
Shed Light

In the current debate on the ethics of Artificial Intelligence (AI) much attention has been paid to find some “common ground” in the numerous AI ethics guidelines. The divergences, however, are equally important as they shed light on the conflicts and controversies that require further debate. This paper analyses the AI ethics landscape with a focus on divergences across actor types (public, expert, and private actors). It finds that the differences in actors’ priorities for ethical principles influence the overall outcome of the debate. It shows that determining “minimum requirements” or “primary principles” on the basis of frequency excludes many principles that are subject to controversy, but might still be ethically relevant. The results are discussed in the light of value pluralism, suggesting that the plurality of sets of principles must be acknowledged and can be used to further the debate.

SELF-IMPOSED ETHICAL GUIDELINES FOR AI IN EDUCATION

2020 ◽  
Vol 1 ◽  
Author(s):  
Anri Leimanis
Keyword(s):  
Artificial Intelligence ◽  
The Self ◽  
Ethical Principles ◽  
Educational Institutions ◽  
Public Agencies ◽  
Ethical Guidelines ◽  
Ai Ethics ◽  
Global Discourse ◽  
The Common ◽  
Ethics Guidelines

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.

scholarly journals The Ethics of AI Ethics: An Evaluation of Guidelines

2020 ◽  
Vol 30 (1) ◽  
pp. 99-120 ◽  
Author(s):  
Thilo Hagendorff
Keyword(s):  
Artificial Intelligence ◽  
Ethical Principles ◽  
Systematic Evaluation ◽  
Research Development ◽  
Ai Ethics ◽  
Ethics Guidelines

Abstract Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved.

scholarly journals Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

2021 ◽  
Author(s):  
Erik Hermann
Keyword(s):  
Artificial Intelligence ◽  
Well Being ◽  
Ethical Principles ◽  
Ethical Challenges ◽  
Ethical Perspective ◽  
Social Good ◽  
Stakeholder Perspective ◽  
Ai Ethics ◽  
Multi Stakeholder ◽  
Shed Light

AbstractArtificial intelligence (AI) is (re)shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications (will) provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being.

Artificial Intelligence (AI) Ethics

2020 ◽  
Vol 31 (2) ◽  
pp. 74-87 ◽  
Author(s):  
Keng Siau ◽  
Weiyu Wang
Keyword(s):  
Artificial Intelligence ◽  
Data Privacy ◽  
Ethical Issues ◽  
Well Being ◽  
Critical Issue ◽  
Ethical Principles ◽  
Machine Ethics ◽  
Moral Issues ◽  
Ai Ethics ◽  
Self Driving Cars

Artificial intelligence (AI)-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data biases, data security, data privacy, and ethical problems of AI-based technology pose significant risks for users, developers, humanity, and societies. As AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. Even though the concept of “machine ethics” was proposed around 2006, AI ethics is still in the infancy stage. AI ethics is the field related to the study of ethical issues in AI. To address AI ethics, one needs to consider the ethics of AI and how to build ethical AI. Ethics of AI studies the ethical principles, rules, guidelines, policies, and regulations that are related to AI. Ethical AI is an AI that performs and behaves ethically. One must recognize and understand the potential ethical and moral issues that may be caused by AI to formulate the necessary ethical principles, rules, guidelines, policies, and regulations for AI (i.e., Ethics of AI). With the appropriate ethics of AI, one can then build AI that exhibits ethical behavior (i.e., Ethical AI). This paper will discuss AI ethics by looking at the ethics of AI and ethical AI. What are the perceived ethical and moral issues with AI? What are the general and common ethical principles, rules, guidelines, policies, and regulations that can resolve or at least attenuate these ethical and moral issues with AI? What are some of the necessary features and characteristics of an ethical AI? How to adhere to the ethics of AI to build ethical AI?

scholarly journals Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mark Ryan ◽  
Bernd Carsten Stahl
Keyword(s):  
Artificial Intelligence ◽  
Large Degree ◽  
Theoretical Understanding ◽  
Content Type ◽  
Practical Action ◽  
Ai Ethics ◽  
Guidance Documents ◽  
Ethics Guidelines ◽  
Degree Of Convergence ◽  
Normative Implications

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.

scholarly journals Actionable Principles for Artificial Intelligence Policy: Three Pathways

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Charlotte Stix
Keyword(s):  
Artificial Intelligence ◽  
Development Process ◽  
Stakeholder Participation ◽  
Expert Group ◽  
Governmental Policy ◽  
Ai Ethics ◽  
Ethics Guidelines ◽  
Multi Stakeholder ◽  
High Level

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.

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

2020 ◽  
Vol 26 (5) ◽  
pp. 2749-2767
Author(s):  
Mark Ryan
Keyword(s):  
Artificial Intelligence ◽  
Interpersonal Trust ◽  
Expert Group ◽  
Human Relationships ◽  
Ai Ethics ◽  
Ethics Guidelines ◽  
High Level ◽  
Relationship Of

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.

scholarly journals The interrelation between data and AI ethics in the context of impact assessments

AI and Ethics ◽  
2020 ◽  
Author(s):  
Emre Kazim ◽  
Adriano Koshiyama
Keyword(s):  
Artificial Intelligence ◽  
Data Protection ◽  
Ethical Principles ◽  
Natural Place ◽  
Trade Offs ◽  
Ai Ethics ◽  
The Relationship

AbstractIn the growing literature on artificial intelligence (AI) impact assessments, the literature on data protection impact assessments is heavily referenced. Given the relative maturity of the data protection debate and that it has translated into legal codification, it is indeed a natural place to start for AI. In this article, we anticipate directions in what we believe will become a dominant and impactful forthcoming debate, namely, how to conceptualise the relationship between data protection and AI impact. We begin by discussing the value canvas i.e. the ethical principles that underpin data and AI ethics, and discuss how these are instantiated in the context of value trade-offs when the ethics are applied. Following this, we map three kinds of relationships that can be envisioned between data and AI ethics, and then close with a discussion of asymmetry in value trade-offs when privacy and fairness are concerned.

scholarly journals Organisational responses to the ethical issues of artificial intelligence

AI & Society ◽  
2021 ◽  
Author(s):  
Bernd Carsten Stahl ◽  
Josephina Antoniou ◽  
Mark Ryan ◽  
Kevin Macnish ◽  
Tilimbe Jiya
Keyword(s):  
Artificial Intelligence ◽  
Case Studies ◽  
Ethical Issues ◽  
Case Analysis ◽  
Mitigation Strategies ◽  
Current Debate ◽  
Ai Ethics ◽  
The Cross ◽  
Cross Case Analysis ◽  
Conceptual Work

AbstractThe ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous initiatives that aim to develop the principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generally unclear is how organisations that make use of AI understand and address these ethical issues in practice. While there is an abundance of conceptual work on AI ethics, empirical insights are rare and often anecdotal. This paper fills the gap in our current understanding of how organisations deal with AI ethics by presenting empirical findings collected using a set of ten case studies and providing an account of the cross-case analysis. The paper reviews the discussion of ethical issues of AI as well as mitigation strategies that have been proposed in the literature. Using this background, the cross-case analysis categorises the organisational responses that were observed in practice. The discussion shows that organisations are highly aware of the AI ethics debate and keen to engage with ethical issues proactively. However, they make use of only a relatively small subsection of the mitigation strategies proposed in the literature. These insights are of importance to organisations deploying or using AI, to the academic AI ethics debate, but maybe most valuable to policymakers involved in the current debate about suitable policy developments to address the ethical issues raised by AI.

scholarly journals In A Different Code: Artificial Intelligence and The Ethics of Care

2020 ◽  
Vol 28 ◽  
Author(s):  
Jonathan Cohn
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Social Media ◽  
Ethics Of Care ◽  
Current Debate ◽  
Ai Ethics ◽  
Ethical Reflections

The following essay explores the intersection of care with ethical reflections on artificial intelligence (AI). The current debate around AI ethics focuses on questions of moral AI judgment and the general criteria for maximizing the fairness, accountability, and transparency of these judgments. While this discussion is important, it all too often obfuscates the actual purpose and intention behind the use of the algorithmic or AI technology. Where the rationale for developing these technologies focuses on increasing optimization and innovation, concern must be shifted to ensure that AI will be used primarily to address current inequities and harms, from exacerbating climate change to manipulating voters via social media to creating “better” weapons.

Sign in / Sign up

Export Citation Format

Share Document