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 Addressing Ethical Issues in AI

2021 ◽  
pp. 55-79
Author(s):  
Bernd Carsten Stahl
Keyword(s):  
Case Studies ◽  
Ethical Issues ◽  
Social Reality ◽  
Mitigation Strategies ◽  
Mitigation Options ◽  
Stakeholder Groups ◽  
The Social ◽  
Policy Level ◽  
Ai Ethics

AbstractThis chapter reviews the proposals that have been put forward to address ethical issues of AI. It divides them into policy-level proposals, organisational responses and guidance for individuals. It discusses how these mitigation options are reflected in the case studies exemplifying the social reality of AI ethics. The chapter concludes with an overview of the stakeholder groups affected by AI, many of whom play a role in implementing the mitigation strategies and addressing ethical issues in AI.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

scholarly journals Ethics as a Service: A Pragmatic Operationalisation of AI Ethics

2021 ◽  
Author(s):  
Jessica Morley ◽  
Anat Elhalal ◽  
Francesca Garcia ◽  
Libby Kinsey ◽  
Jakob Mökander ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Ethics Codes ◽  
Practical Design ◽  
Ethical Design ◽  
Ai Ethics ◽  
Algorithmic Design ◽  
Almost All ◽  
Technical Guidance ◽  
Tools And Methods

AbstractAs the range of potential uses for Artificial Intelligence (AI), in particular machine learning (ML), has increased, so has awareness of the associated ethical issues. This increased awareness has led to the realisation that existing legislation and regulation provides insufficient protection to individuals, groups, society, and the environment from AI harms. In response to this realisation, there has been a proliferation of principle-based ethics codes, guidelines and frameworks. However, it has become increasingly clear that a significant gap exists between the theory of AI ethics principles and the practical design of AI systems. In previous work, we analysed whether it is possible to close this gap between the ‘what’ and the ‘how’ of AI ethics through the use of tools and methods designed to help AI developers, engineers, and designers translate principles into practice. We concluded that this method of closure is currently ineffective as almost all existing translational tools and methods are either too flexible (and thus vulnerable to ethics washing) or too strict (unresponsive to context). This raised the question: if, even with technical guidance, AI ethics is challenging to embed in the process of algorithmic design, is the entire pro-ethical design endeavour rendered futile? And, if no, then how can AI ethics be made useful for AI practitioners? This is the question we seek to address here by exploring why principles and technical translational tools are still needed even if they are limited, and how these limitations can be potentially overcome by providing theoretical grounding of a concept that has been termed ‘Ethics as a Service.’

scholarly journals Ethics of Corporeal, Co-present Robots as Agents of Influence: a Review

2021 ◽  
Author(s):  
AJung Moon ◽  
Shalaleh Rismani ◽  
H. F. Machiel Van der Loos
Keyword(s):  
Artificial Intelligence ◽  
Physical Environment ◽  
Ethical Issues ◽  
Human Robot Interaction ◽  
Physical Interaction ◽  
Ethical Challenges ◽  
Natural Tendency ◽  
Ai Ethics ◽  
Recent Trends ◽  
The Impact

Abstract Purpose of Review To summarize the set of roboethics issues that uniquely arise due to the corporeality and physical interaction modalities afforded by robots, irrespective of the degree of artificial intelligence present in the system. Recent Findings One of the recent trends in the discussion of ethics of emerging technologies has been the treatment of roboethics issues as those of “embodied AI,” a subset of AI ethics. In contrast to AI, however, robots leverage human’s natural tendency to be influenced by our physical environment. Recent work in human-robot interaction highlights the impact a robot’s presence, capacity to touch, and move in our physical environment has on people, and helping to articulate the ethical issues particular to the design of interactive robotic systems. Summary The corporeality of interactive robots poses unique sets of ethical challenges. These issues should be considered in the design irrespective of and in addition to the ethics of artificial intelligence implemented in them.

The Overtraining Syndrome: A Multicontextual Assessment

2004 ◽  
Vol 18 (2) ◽  
pp. 154-171 ◽  
Author(s):  
Heidi L. Meehan ◽  
Stephen J. Bull ◽  
Dan M. Wood ◽  
David V.B. James
Keyword(s):  
Case Studies ◽  
Case Analysis ◽  
Individual Case ◽  
Medical Examination ◽  
Endurance Athletes ◽  
Semistructured Interview ◽  
Coping Response ◽  
Daily Hassle ◽  
Overtraining Syndrome ◽  
Cross Case Analysis

The present study explored the experiences of five competitive endurance athletes (1 female, 4 male) diagnosed with the overtraining syndrome (OTS). A multicontextual method of inquiry was used, which first involved a medical examination whereby OTS was diagnosed according to established criteria. In addition, 2 questionnaires were administered: the Athlete Daily Hassle Scale (Albinson & Pearce, 1998) and the Coping Response Inventory (Moos, 1992), and a semistructured interview was conducted. Individual case studies were then developed and cross-case analysis carried out. Findings from the present study illustrate that together with sport stress, nonsport stress appears to make an important contribution to the experience of those athletes diagnosed with the OTS. This finding provides evidence to support anecdotes in previous reports.

Leveled Literacy Intervention

2015 ◽  
pp. 118-138
Author(s):  
Kelli Campbell
Keyword(s):  
Case Studies ◽  
Case Analysis ◽  
Literacy Intervention ◽  
Future Research ◽  
Reading Levels ◽  
Leveled Literacy Intervention ◽  
Teacher Survey ◽  
Student Interviews ◽  
Student Reading ◽  
Cross Case Analysis

In this chapter, the qualitative study will investigate and evaluate the effectiveness of the Leveled Literacy Intervention (LLI) framework with English Language Learners (ELL) newcomers and their literacy achievement using the case study method and cross case analysis. Student case studies will consist of LLI pre and post assessment data, guided reading data, and information gathered from student interviews. The triangulation of student interviews, teacher surveys, and extant literature provide the foundation for answering questions regarding the effectiveness of LLI with the ELL newcomers. Findings are presented through student case studies, resulting from cross case analysis that identified themes, patterns, and commonalities in student reading achievement data and teacher survey results. Results show that ELL newcomers needed to develop social, academic, and content-related language. Findings from the study show that the students made progress while participating during the intervention but have not maintained or increased their reading levels after the intervention that provides opportunities for future research. Recommendation for future studies and conclusion are discussed.

Artificial Intelligences Are Subsets of Human Beings, Mainly in Fictions and Films

2021 ◽  
pp. 598-618
Author(s):  
Nandini Sen
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Human Being ◽  
Human Beings ◽  
Human Race ◽  
Emotional Quotient ◽  
New Knowledge ◽  
Ai Ethics

This chapter aims to create new knowledge regarding artificial intelligence (AI) ethics and relevant subjects while reviewing ethical relationship between human beings and AI/robotics and linking between the moral fabric or the ethical issues of AI as used in fictions and films. It carefully analyses how a human being will love robot and vice versa. Here, fictions and films are not just about technology but about their feelings and the nature of bonding between AIs and the human race. Ordinary human beings distrust and then start to like AIs. However, if the AI becomes a rogue as seen in many fictions and films, then the AI is taken down to avoid the destruction of the human beings. Scientists like Turing are champions of robot/AI's feelings. Fictional and movie AIs are developed to keenly watch and comprehend humans. These actions are so close to empathy they amount to consciousness and emotional quotient.

Successes and Failures in E-Partnering

2011 ◽  
pp. 145-174
Author(s):  
Fang Zhao
Keyword(s):  
Case Studies ◽  
Case Analysis ◽  
Lessons Learned ◽  
Small Manufacturer ◽  
Key Issues ◽  
Multiple Case ◽  
Multiple Case Studies ◽  
Cross Case Analysis ◽  
Comprehensive Discussion ◽  
Successes And Failures

The previous chapters have included a comprehensive discussion of general issues concerning e-partnership management from both technology and people perspectives, and, continuing this theme, this chapter presents extended and systematic multiple case studies which allow a more profound exploration of the way in which companies have partnered in e-business. It also contains an in-depth examination of specific issues and problems raised in e-partnerships. The cases selected for the case studies represent a broad range of interests, from big brand dotcoms like Yahoo! and Google to a small manufacturer that has embraced e-business and e-partnership technologies and practices. The case studies are followed by a cross-case analysis of the key issues in relation to the development of e-partnerships. Key successful factors are identified from the successful cases, along with the hard lessons learned from failure.

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?

The Islamist Cyberpropaganda Threat and Its Counter-Terrorism Policy Implications

2019 ◽  
pp. 118-143
Author(s):  
Nigel Jones ◽  
Paul Baines ◽  
Russell Craig ◽  
Ian Tunnicliffe ◽  
Nicholas O'Shaughnessy
Keyword(s):  
Case Studies ◽  
Policy Maker ◽  
Case Analysis ◽  
Policy Implications ◽  
Al Qaeda ◽  
Islamic State ◽  
Online Interaction ◽  
Boko Haram ◽  
Counter Terrorism ◽  
Cross Case Analysis

This chapter examines Islamist cyberpropaganda case studies live in 2014, namely Al Qaeda, Islamic State, Boko Haram and Al Shabaab. The authors define cyberpropganda as the exploitation of the generative characteristics of online interaction for the production and reproduction of propaganda. The cross-case analysis identifies key messages and themes, how cyberpropaganda is generated and spread, and how it is made attractive to those who may act on it. In the discussion that follows implications for the policy-maker are identified and addressed. These include whether to tackle symptoms or causes of the problems and whether to treat the problems as essentially global or local. The final issue is how the counter-propagandist can make themselves heard.

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