This article argues that an ethical framework will help to harness the potential of AI while keeping humans in control.

Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence. According to an article in The New York Times, the course on artificial intelligence is (...) “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom. Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®. (shrink)

This paper focuses on the potential of “equitech”—AI technology that improves equity. Recently, interventions have been developed to reduce the harm of implicit bias, the automatic form of stereotype or prejudice that contributes to injustice. However, these interventions—some of which are assisted by AI-related technology—have significant limitations, including unintended negative consequences and general inefficacy. To overcome these limitations, we propose a two-dimensional framework to assess current AI-assisted interventions and explore promising new ones. We begin by using the case of human (...) resource recruitment as a focal point to show that existing approaches have exploited only a subset of the available solution space. We then demonstrate how our framework facilitates the discovery of new approaches. The first dimension of this framework helps us systematically consider the analytic information, intervention implementation, and modes of human-machine interaction made available by advancements in AI-related technology. The second dimension enables the identification and incorporation of insights from recent research on implicit bias intervention. We argue that a design strategy that combines complementary interventions can further enhance the effectiveness of interventions by targeting the various interacting cognitive systems that underlie implicit bias. We end with a discussion of how our cognitive interventions framework can have positive downstream effects for structural problems. (shrink)

The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that are (...) essential for future AI4SG initiatives. The analysis is supported by 27 case examples of AI4SG projects. Some of these factors are almost entirely novel to AI, while the significance of other factors is heightened by the use of AI. From each of these factors, corresponding best practices are formulated which, subject to context and balance, may serve as preliminary guidelines to ensure that well-designed AI is more likely to serve the social good. (shrink)

Current advances in research, development and application of artificial intelligence 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. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a ‘good (...) AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, even if it were to (...) be ‘solved’ at a technical level, would be insufficient to ensure positive social outcomes from intelligent systems. (shrink)

The question of whether AI systems such as robots can or should be afforded moral agency or patiency is not one amenable either to discovery or simple reasoning, because we as societies constantly reconstruct our artefacts, including our ethical systems. Consequently, the place of AI systems in society is a matter of normative, not descriptive ethics. Here I start from a functionalist assumption, that ethics is the set of behaviour that maintains a society. This assumption allows me to exploit the (...) theoretical biology of sociality and autonomy to explain our moral intuitions. From this grounding I extend to consider possible ethics for maintaining either human- or of artefact-centred societies. I conclude that while constructing AI systems as either moral agents or patients is possible, neither is desirable. In particular, I argue that we are unlikely to construct a coherent ethics in which it it is ethical to afford AI moral subjectivity. We are therefore obliged not to build AI we are obliged to. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To (...) achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

As with other emerging technologies, advanced robotics brings with it new ethical and policy challenges. This paper will describe the flourishing role of robots in society—from security to sex—and survey the numerous ethical and social issues, which we locate in three broad categories: safety & errors, law & ethics, and social impact. We discuss many of these issues in greater detail in our forthcoming edited volume on robot ethics from MIT Press.

Este artigo tem por objetivo essencial contribuir para o esclarecimento teórico-filosófico do uso de conceitos como ética, moral, axiologia e valores, habitualmente empregues para nos referirmos a uma mesma realidade. Para tal, começaremos por analisar as respetivas etimologias que os caracterizam, examinaremos os diversos matizes dos seus sentidos diferenciados, bem como a sua relação de complementaridade, e terminaremos referindo o que entendemos por valores e qual a sua natureza e importância, principais características, bem como o universo a que se reportam. (...) Ao longo do texto, aduziremos e concluiremos pelo uso preferencial do conceito de "ética" a "moral", para o qual estão reservados os termos "normas" e "regras", e o de "valor" a "norma", a par de uma perspetiva crítica daquela. This article essentially aims to contribute to the philosophical-theoretical clarification of the use of concepts such as ethics, morals, axiology and values, usually used to refer to the same reality. To this end, we will begin by analyzing the respective etymologies that feature them, we will examine the various nuances of their senses, as well as their relationship of complementarity, and we will finish by referring to what we mean by values and what is their nature and importance, key features, as well as the universe to which they relate. Throughout the text, we will conclude by the preferential use of the concept from "ethics" to "morals", for which the terms "standards" and "rules" are reserved, and that from "value" to "standard", together with a critical perspective. (shrink)

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This paper pertains to research works aiming at linking ethics and automated reasoning in autonomous machines. It focuses on a formal approach that is intended to be the basis of an artificial agent’s reasoning that could be considered by a human observer as an ethical reasoning. The approach includes some formal tools to describe a situation and models of ethical principles that are designed to automatically compute a judgement on possible decisions that can be made in a given situation and (...) explain why a given decision is ethically acceptable or not. It is illustrated on three ethical frameworks—utilitarian ethics, deontological ethics and the Doctrine of Double effect whose formal models are tested on ethical dilemmas so as to examine how they respond to those dilemmas and to highlight the issues at stake when a formal approach to ethical concepts is considered. The whole approach is instantiated on the drone dilemma, a thought experiment we have designed; this allows the discrepancies that exist between the judgements of the various ethical frameworks to be shown. The final discussion allows us to highlight the different sources of subjectivity of the approach, despite the fact that concepts are expressed in a more rigorous way than in natural language: indeed, the formal approach enables subjectivity to be identified and located more precisely. (shrink)

With their prospect for causing both novel and known forms of damage, harm and injury, the issue of responsibility has been a recurring theme in the debate concerning autonomous vehicles. Yet, the discussion of responsibility has obscured the finer details both between the underlying concepts of responsibility, and their application to the interaction between human beings and artificial decision-making entities. By developing meaningful distinctions and examining their ramifications, this article contributes to this debate by refining the underlying concepts that together (...) inform the idea of responsibility. Two different approaches are offered to the question of responsibility and autonomous vehicles: targeting and risk distribution. The article then introduces a thought experiment which situates autonomous vehicles within the context of crash optimisation impulses and coordinated or networked decision-making. It argues that guiding ethical frameworks overlook compound or aggregated effects which may arise, and which can lead to subtle forms of structural discrimination. Insofar as such effects remain unrecognised by the legal systems relied upon to remedy them, the potential for societal inequalities is increased and entrenched, situations of injustice and impunity may be unwittingly maintained. This second set of concerns may represent a hitherto overlooked type of responsibility gap arising from inadequate accountability processes capable of challenging systemic risk displacement. (shrink)

There is an increasing need for norms to be embedded in technology as the widespread deployment of applications such as autonomous driving, warfare and big data analysis for crime fighting and counter-terrorism becomes ever closer. Current approaches to norms in multi-agent systems tend either to simply make prohibited actions unavailable, or to provide a set of rules which the agent is obliged to follow, either as part of its design or to avoid sanctions and punishments. In this paper we argue (...) for the position that agents should be equipped with the ability to reason about a system’s norms, by reasoning about the social and moral values that norms are designed to serve; that is, perform the sort of moral reasoning we expect of humans. In particular we highlight the need for such reasoning when circumstances are such that the rules should arguably be broken, so that the reasoning can guide agents in deciding whether to comply with the norms and, if violation is desirable, how best to violate them. One approach to enabling this is to make use of an argumentation scheme based on values and designed for practical reasoning: arguments for and against actions are generated using this scheme and agents choose between actions based on their preferences over these values. Moral reasoning then requires that agents have an acceptable set of values and an acceptable ordering on their values. We first discuss how this approach can be used to think about and justify norms in general, and then discuss how this reasoning can be used to think about when norms should be violated, and the form this violation should take. We illustrate how value based reasoning can be used to decide when and how to violate a norm using a road traffic example. We also briefly consider what makes an ordering on values acceptable, and how such an ordering might be determined. (shrink)

The persuasiveness of an argument depends on the values promoted and demoted by the position defended. This idea, inspired by Perelman’s work on argumentation, has become a prominent theme in artificial intelligence research on argumentation since the work by Hafner and Berman on teleological reasoning in the law, and was further developed by Bench-Capon in his value-based argumentation frameworks. One theme in the study of value-guided argumentation is the comparison of values. Formal models involving value comparison typically use either qualitative (...) or quantitative primitives. In this paper, techniques connecting qualitative and quantitative primitives recently developed for evidential argumentation are applied to value-guided argumentation. By developing the theoretical understanding of intelligent systems guided by embedded values, the paper is a step towards ethical systems design, much needed in these days of ever more pervasive AI techniquesThe persuasiveness of an argument depends on the values promoted and demoted by the position defended. This idea, inspired by Perelman’s work on argumentation, has become a prominent theme in artificial intelligence research on argumentation since the work by Hafner and Berman on teleological reasoning in the law, and was further developed by Bench-Capon in his value-based argumentation frameworks. One theme in the study of value-guided argumentation is the comparison of values. Formal models involving value comparison typically use either qualitative or quantitative primitives. In this paper, techniques connecting qualitative and quantitative primitives recently developed for evidential argumentation are applied to value-guided argumentation. By developing the theoretical understanding of intelligent systems guided by embedded values, the paper is a step towards ethical systems design, much needed in these days of ever more pervasive AI techniques. (shrink)

How are we to appraise new technological developments that may bring revolutionary social changes? Currently this is often done by trying to predict or anticipate social consequences and to use these as a basis for moral and regulatory appraisal. Such an approach can, however, not deal with the uncertainties and unknowns that are inherent in social changes induced by technological development. An alternative approach is proposed that conceives of the introduction of new technologies into society as a social experiment. An (...) ethical framework for the acceptability of such experiments is developed based on the bioethical principles for experiments with human subjects: non-maleficence, beneficence, respect for autonomy, and justice. This provides a handle for the moral and regulatory assessment of new technologies and their impact on society. (shrink)

Autonomous vehicles are one of the most spectacular recent developments of Artificial Intelligence. Among the problems that still need to be solved before they can fully autonomously participate in traffic is the one of making their behaviour conform to the traffic laws. This paper discusses this problem by way of a case study of Dutch traffic law. First it is discussed to what extent Dutch traffic law exhibits features that are traditionally said to pose challenges for AI & Law models, (...) such as exceptions, rule conflicts, open texture and vagueness, rule change, and the need for commonsense knowledge. Then three approaches to the design of law-conforming AV are evaluated in light of the challenges posed by Dutch traffic law, which includes an assessment of the usefulness of AI & Law models of nonmonotonic reasoning, argumentation and case-based reasoning. (shrink)

How are we to appraise new technological developments that may bring revolutionary social changes? Currently this is often done by trying to predict or anticipate social consequences and to use these as a basis for moral and regulatory appraisal. Such an approach can, however, not deal with the uncertainties and unknowns that are inherent in social changes induced by technological development. An alternative approach is proposed that conceives of the introduction of new technologies into society as a social experiment. An (...) ethical framework for the acceptability of such experiments is developed based on the bioethical principles for experiments with human subjects: non-maleficence, beneficence, respect for autonomy, and justice. This provides a handle for the moral and regulatory assessment of new technologies and their impact on society. (shrink)