Despite the increase in the research field of ethics in artificial intelligence, most efforts have focused on the debate about principles and guidelines for responsible AI, but not enough attention has been given to the “how” of applied ethics. This paper aims to advance the research exploring the gap between practice and principles in AI ethics by identifying how companies are applying those guidelines and principles in practice. Through a qualitative methodology based on 22 semi-structured interviews and two focus groups, (...) the goal of the current study is to understand how companies approach ethical issues related to AI systems. A structured analysis of the transcripts brought out many actual practices and findings, which are presented around the following main research topics: ethics and principles, privacy, explainability, and fairness. The interviewees also raised issues of accountability and governance. Finally, some recommendations are suggested such as developing specific sector regulations, fostering a data-driven organisational culture, considering the algorithm’s complete life cycle, developing and using a specific code of ethics, and providing specific training on ethical issues. Despite some obvious limitations, such as the type and number of companies interviewed, this work identifies real examples and direct priorities to advance the research exploring the gap between practice and principles in AI ethics, with a specific focus on Spanish companies. (shrink)

Ethical reflection on Artificial Intelligence (AI) has become a priority. In this article, we propose a methodological model for a comprehensive ethical analysis of some uses of AI, notably as a replacement of human actors in specific activities. We emphasize the need for conceptual clarification of relevant key terms (e.g., intelligence) in order to undertake such reflection. Against that background, we distinguish two levels of ethical analysis, one practical and one theoretical. Focusing on the state of AI at present, we (...) suggest that regardless of the presence of intelligence, the lack of morally relevant features calls for caution when considering the role of AI in some specific human activities. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective nature of ethical decision-making. (...) The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)

Over the last decade, humans have produced each year as much data as were produced throughout the entire history of humankind. These data, in quantities that exceed current analytical capabilities, have been described as “the new oil,” an incomparable source of value. This is true for healthcare, as well. Conducting analyses of large, diverse, medical datasets promises the detection of previously unnoticed clinical correlations and new diagnostic or even therapeutic possibilities. However, using Big Data poses several problems, especially in terms (...) of representing the uniqueness of each patient and expressing the differences between individuals, primarily gender and sex differences. The first two sections of the paper provide a definition of “Big Data” and illustrate the uses of Big Data in medicine. Subsequently, the paper explores the struggle to represent exhaustively the uniqueness of the patient through Big Data is highlighted prior to a deeper investigation of the digital representation of gender in personalized medicine. The final part of the paper put forward a series of recommendations for better approaching the complexity of gender in medical and clinical research involving Big Data for the creation or enhancement of personalized medicine services. (shrink)

Over the last decade, humans have produced each year as much data as were produced throughout the entire history of humankind. These data, in quantities that exceed current analytical capabilities, have been described as “the new oil,” an incomparable source of value. This is true for healthcare, as well. Conducting analyses of large, diverse, medical datasets promises the detection of previously unnoticed clinical correlations and new diagnostic or even therapeutic possibilities. However, using Big Data poses several problems, especially in terms (...) of representing the uniqueness of each patient and expressing the differences between individuals, primarily gender and sex differences. The first two sections of the paper provide a definition of “Big Data” and illustrate the uses of Big Data in medicine. Subsequently, the paper explores the struggle to represent exhaustively the uniqueness of the patient through Big Data is highlighted prior to a deeper investigation of the digital representation of gender in personalized medicine. The final part of the paper put forward a series of recommendations for better approaching the complexity of gender in medical and clinical research involving Big Data for the creation or enhancement of personalized medicine services. (shrink)

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use (...) AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers. (shrink)

Monitoring and assistive technologies (MATs) are being used more frequently in healthcare. A central ethical concern is the compatibility of these systems with the moral preferences of their users—an issue especially relevant to participatory approaches within the ethics-by-design debate. However, users’ incapacity to communicate preferences or to participate in design processes, e.g., due to dementia, presents a hurdle for participatory ethics-by-design approaches. In this paper, we explore the question of how the value preferences of users in the field of dementia (...) care can be integrated into AI-based MATs. First, we briefly introduce different ethics-by-design approaches and explain the challenges they face in dementia care. Next, we introduce a novel approach for addressing these challenges. Through a qualitative content analysis of interviews with persons with dementia and their family caregivers (n = 27), we identified multiple ideal–typical value preference profiles. We then applied these profiles in a computer simulation, by which we also introduce the concept of ethical compliance quantification to scale the moral preferences of the interviewees for the simulation. Finally, we discuss study results, the advantages of using computer simulations, and general study limitations before drawing conclusions for further research. The study contributes to the ongoing debate on participatory ethics-by-design by defining on the basis of empirical data ideal–typical value preference frameworks that can be used to guide MAT actions and their outcomes. Going forward, MAT end-users with dementia and other communication-impaired persons could be enabled to choose a value profile that best fits their moral preferences. (shrink)

The ethics of artificial intelligence 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. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Applications of artificial intelligence (AI) bear great transformative potential in the economic, technological and social sectors, impacting especially future work environments. Ethical regulation of AI requires a relational understanding of the technology by relevant stakeholder groups such as researchers, developers, politicians, civil servants, affected workers or other users applying AI in their work processes. The purpose of this paper is to support relational AI discourse for an improved ethical framing and regulation of the technology. The argumentation emphasizes a widespread reembodied (...) understanding of AI technology as critical requirement for capable ethical and regulatory frameworks. A sociotechnical perspective encourages the material interpretation of AI as reembodied adaptation of biological intelligence. Reviewing Cartesian dualism as motivating the disembodiment of human intelligence for its transfer to machines, the argumentation develops an integrated embodiment concept of AI in its mechanistic, naturalistic, combined AI and neuroethical, and relational contexts. This concept is discussed in relation to basic phenomenological and postphenomenological assumptions, and is applied to the example of AI-based neurotechnology potentially disrupting future work processes. Strengthening a human-centered approach, the presented concept for a reembodied understanding of AI technology enables better integrated ethical and regulatory debates, and improves social discourse and human agency in developing and regulating AI technology. (shrink)