Responsible Artificial Intelligence : ethics and regulation: Articles

In an attempt to address the ethical challenges in AI, we currently have several ethical AI frameworks in place worldwide, with more being released or in development around the world every day. From the European Commission's Guidelines for Trustworthy AI, to the Asilomar AI Principles, the message is usually similar: more transparency and explicability. However, navigating the broad number of resources currently available is not a simple process. So, how do we find common ground when it comes to ethics in AI?

In this paper, the author examines the reasons that ethical deployment of AI has been so elusive for so many high-profile organizations, and will explain why there have been such egregious examples of unethical AI built and deployed into the world. The author will draw on examples and lessons from other fields, such as medical ethics and systems theory, to demonstrate that AI ethics simply cannot exist without a broader culture of ethics. He will make the case that only organizations with a firm grounding in ethics, and an appreciation for the way complex systems behave can succeed at ethical deployment of AI.

Many Artificial Intelligence (e.g., Machine Learning) tools are being developed with ethical debt. They are created and deployed without fully examining and addressing the potential ethical consequences. This paper looks more closely at the concept of ethical debt in Artificial Intelligence and its consequences. The analysis focuses on two prevalent use cases: Artificial Intelligence as a vehicle for screening job applicants and Artificial Intelligence as a predictor for those patients who will require extra healthcare services. The analysis also compares and contrasts the similarities and differences surrounding the concepts of ethical debt versus technical debt. The paper concludes with a discussion on the misalignment between those who decide to incur ethical debt and those who end up paying for that decision.

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.

The ethics and law of AI address the same domain, namely, the present and future impacts of AI on individuals, society, and the environment. Both are meant to provide normative guidance, proposing rules and values on which basis to govern human action and determine the constrains, structures and functions of AI-enabled socio-technical systems. This article examines the way in which AI is addressed by ethical and legal rules, principles and arguments. It considers the extent to which the demands of law and ethics may pull in different directions or rather overlap, and examines how they can be coordinated, while remaining in a productive dialectical tension. In particular, it argues that human/fundamental rights and social values are central to both ethics and law. Even though they can be framed in different ways, they can provide a useful normative reference for linking ethics and law in addressing the normative issues arising in connection with AI.

AI Ethics is a burgeoning and relatively new field that has emerged in response to growing concerns about the impact of artificial intelligence (AI) on human individuals and their social institutions. In turn, AI ethics is a part of the broader field of digital ethics, which addresses similar concerns generated by the development and deployment of new digital technologies. Here, we tackle the important worry that digital ethics in general, and AI ethics in particular, lack adequate philosophical foundations. In direct response to that worry, we formulate and rationally justify some basic concepts and principles for digital ethics/AI ethics, all drawn from a broadly Kantian theory of human dignity. Authors' argument, which is designed to be relatively compact and easily accessible, is presented in ten distinct steps.

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.

The aim of the paper is to find an answer to the question “Who or what is responsible for the benefits and harms of using artificial intelligence in radiology?” When human beings make decisions, the action itself is normally connected with a direct responsibility by the agent who generated the action. You have an effect on others, and therefore, you are responsible for what you do and what you decide to do. But if you do not do this yourself, but an artificial intelligence system, it becomes difficult and important to be able to ascribe responsibility when something goes wrong. Future legislation must outline the contours of the professional’s responsibility, with respect to the provision of the service performed autonomously by AI, balancing the professional’s ability to influence and therefore correct the machine, limiting the sphere of autonomy that instead technological evolution would like to recognize to robots.

As part of the consultation process on the European Commission’s "White Paper on Artificial Intelligence - a European approach," AI Now Institute submitted this document highlighting its key responses and recommendations. AI Now Institute's work examines the rapid proliferation of AI systems through social domains such as criminal justice, healthcare, employment, and education. It focuses on concerns in the areas of bias and inclusion, safety and critical infrastructure, rights and liberties, and labor. As it identifies problems in each of these spaces, it works to address them through robust research, community engagement, and key policy interventions.

On 28 March 2019, the AI Now Institute at New York University (NYU), the NYU Center for Disability Studies, and Microsoft convened disability scholars, AI developers, and computer science and human-computer interaction researchers to discuss the intersection of disability, bias, and AI, and to identify areas where more research and intervention are needed. This report captures and expands on some of the themes that emerged during discussion and debate. In particular, it identifies key questions that a focus on disability raises for the project of understanding the social implications of AI, and for ensuring that AI technologies don’t reproduce and extend histories of marginalization.

This guide, written for department and delivery leads in the UK public sector and adopted by the British Government in its publication, 'Using AI in the Public Sector,' identifies the potential harms caused by AI systems and proposes concrete, operationalisable measures to counteract them. It stresses that public sector organisations can anticipate and prevent these potential harms by stewarding a culture of responsible innovation and by putting in place governance processes that support the design and implementation of ethical, fair, and safe AI systems. It also highlights the need for algorithmically supported outcomes to be interpretable by their users and made understandable to decision subjects in clear, non-technical, and accessible ways. Finally, it builds out a vision of human-centred and context-sensitive implementation that gives a central role to communication, evidence-based reasoning, situational awareness, and moral justifiability.

This article investigates both the claims made for, and the dangers or opportunities posed by, the development of (allegedly), aspiring or “would-be” autonomous vehicles and other artificially superintelligent machines. It also examines the dilemmas posed by the fact that these individuals might develop ideas above their station. These ideas may also limit or challenge the legitimacy of the proposed management and safety strategies that might be devised to limit the ways in which they might function or malfunction.

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. The authors introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other stakeholders.

Artificial intelligence (AI) systems are increasingly being used in our everyday life and in almost every kind of human activity, for instance in areas such as education and welfare, information society, judicial and law enforcement systems and recently to fight the Covid-19 pandemic. Very often referred to as “game changers”, AI systems can bring about many benefits, but they can also raise complex and important legal, ethical, policy and economic issues.

The COVID-19 crisis has prompted many countries to experiment with Artificial Intelligence (AI) systems more widely in order to bring the situation under control. As the main trendsetters for tech regulation and experimentation, the EU, the US, and China have shown examples of both best practices and less successful scenarios, raising important questions in terms of the ethical use of the latest technologies, data privacy, and fundamental rights. This analysis raises awareness of both government practices and discrepancies between private and public sector approaches. Given the tremendous opportunities AI can provide for all societies, this analysis calls for a more active role of the international community by developing a clear and detailed ethical regulatory and sanctioning framework.

This study examines the impact on fundamental rights of Artificial Intelligence in the field of law enforcement and criminal justice, from a European Union perspective. It presents the applicable legal framework (notably in relation to data protection), and analyses major trends and key policy discussions. The study also considers developments following the Covid-19 outbreak.

This study addresses the relationship between the general data protection regulation and artificial intelligence. After introducing some basic concepts of AI, it reviews the state of the art in AI technologies and focuses on the application of AI to personal data. It considers challenges and opportunities for individuals and society, and the ways in which risks can be countered and opportunities enabled through law and technology.

Not only text messages and photos can be faked. With the help of artificial intelligence, videos can also be manipulated in such a way that truth and deception can no longer be easily distinguished. This has far-reaching consequences for society and politics. Technical and legislative measures are necessary to counteract this negative development.

In recent times, states have become increasingly dependent on programs and algorithms to exercise their public powers. However, it has been shown that the digital transformation of states has unresolved aspects. Artificial intelligence (AI) questions the role of human conviction underlying administrative decisions, which are subject to uncertainty and complex constraints. How should AI guide such decisions? And how can the requirements of the rule of law be reconciled with the practical advantages of automating public decisions?

Superpowers, states and companies around the world are all pushing hard to win the AI race. Artificial intelligence (AI) is of strategic importance for the EU, with the Commission recently stating that ‘artificial intelligence with a purpose can make Europe a world leader’. For this to happen, the EU needs to put in place the right ethical and legal framework. This brief argues that such a framework must be solidly founded on regulation and that it must pay specific attention to the protection of workers. Workers are in a subordinate position in relation to their employers, and in the EU’s eagerness to win the AI race, their rights may be overlooked.

This study addresses the new challenges and opportunities for digital services provided by artificial intelligence, which regard to consumer protection, data protection, and providers’ liability. It addresses also the way in which digital services rely on AI for processing consumer data and for targeting consumers with ads and other messages, with a focus on risks to consumer privacy and autonomy, as well as on the possibility of developing consumer-friendly AI applications.

There is a clear link between the overarching strategy with regard to the EU’s intention to become a global leader in responsible AI, and the uptake of technologically robust and responsible AI that respects basic human rights and is engineered to mitigate potential harm. The EU’s brand of ‘Trustworthy AI’, by laying the groundwork for ethical guidelines for its creation and use, could indeed become the so-called silver bullet in the EU’s strategy to ‘catch up’ with the USA or China.

The widespread use of AI as a solution to economic and social problems is as terrifying as it is exciting. The search is on for the right combination of legal, regulatory, ethical and technological approaches that constitute effective AI governance. This article looks at the debates on AI governance and at the particular social effects AI could have in India, where the automation of work will impact on job creation in a young and growing population.

One of the most important foundations for the success and acceptance of artificial intelligence technologies is trust. This paper makes the case for a forceful European regulatory and political answer to establish trust in emerging technologies. It examines three areas where AI will have disruptive effects: IT-security and product safety, re-skilling of workers affected by automation and the governance of automated decision-making systems.

This report explores some of the risks that could arise as the use of artificial intelligence (AI) becomes increasingly prevalent in financial services – not just at the fringes, but at mainstream institutions that touch billions of people worldwide.

In the coming decade, as many as 50% of work tasks will be subject to automation by the use of Artificial Intelligence (AI). This paper looks at what steps can help ensure a responsible use of AI, concluding with a practical roadmap for policymakers, executives and researchers, merging recommendations from across a wide range of disciplines and discussions

For better or worse, artificial intelligence (AI) is predicted to have a huge impact on the future of humanity. As new promises and concerns reach increasingly mainstream audiences, the debate is starting to capture the public imagination. In this publication, the authors present four opinion pieces, each responding to the question: should we fear AI? The four authors come from different disciplinary backgrounds and present diverging perspectives on whether we should fear the future of AI, and how we should proceed with its development.

Although AI could enhance the EU’s Common Security and Defence Policy, a number of unintended legal, ethical and operational consequences could occur. The implications of AI for EU security and defence are largely unknown, but it could help the EU enhance its security and defence threat and risk detection, protection and preparation capabilities, as well as improve the Union’s defence production capacities. While the EU is collectively one of the world leaders on academic research about AI, more attention is needed on translating basic research into applied research and innovation in the civil and defence sectors.

Many experts argue that focusing on how automated cars will solve the dilemma known as the 'trolley problem' isn't going to get us very far in the debate about the ethics of artificial intelligence. But it's hard to resist if you are a philosopher, an ethicist, a futurist, or simply a geek - and it's fun. Still, this dilemma can reveal a number of outstanding policy issues that are often neglected in the public debate.