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.

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 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.

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 What a Philosopher Learned at an AI Ethics Evaluation

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
James Brusseau
Keyword(s):  
Medical Device ◽  
Ethical Principles ◽  
Practical Action ◽  
Ai Ethics ◽  
Ethics Guidelines

AI ethics increasingly focuses on converting abstract principles into practical action. This case study documents nine lessons for the conversion learned while performing an ethics evaluation on a deployed AI medical device. The utilized ethical principles were adopted from the Ethics Guidelines for Trustworthy AI, and the conversion into practical insights and recommendations was accomplished by an independent team composed of philosophers, technical and medical experts.

scholarly journals The social and ethical impacts of artificial intelligence in agriculture: mapping the agricultural AI literature

AI & Society ◽  
2022 ◽  
Author(s):  
Mark Ryan
Keyword(s):  
Artificial Intelligence ◽  
Conference Proceedings ◽  
Thematic Analysis ◽  
Agricultural Sector ◽  
Food Sector ◽  
The Social ◽  
Ai Ethics ◽  
Agricultural Literature ◽  
Ethics Guidelines

AbstractThis paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed.

scholarly journals A criticism of AI ethics guidelines

2020 ◽  
Vol 20 (4) ◽  
pp. 57
Author(s):  
Mihály Héder
Keyword(s):  
Artificial Intelligence ◽  
Social Control ◽  
World Wide ◽  
Positive Potential ◽  
Main Research ◽  
Current Wave ◽  
Ai Ethics ◽  
Research Questions ◽  
Ethics Guidelines ◽  
General Technology

This paper investigates the current wave of Artificial Intelligence Ethics GUidelines (AIGUs). The goal is not to provide a broad survey of the details of such efforts; instead, the reasons for the proliferation of such guidelines is investigated. Two main research questions are pursued. First, what is the justification for the proliferation of AIGUs, and what are the reasonable goals and limitations of such projects? Second, what are the specific concerns of AI that are so unique that general technology regulation cannot cover them? The paper reveals that the development of AI guidelines is part of a decades-long trend of an ever-increasing express need for stronger social control of technology, and that many of the concerns of the AIGUs are not specific to the technology itself, but are rather about transparency and human oversight. Nevertheless, the positive potential of the situation is that the intense world-wide focus on AIGUs will yield such profound guidelines that the regulation of other technologies may want to follow suite.

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