Artificial Intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this chapter AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This chapter offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

The concept of distributed moral responsibility (DMR) has a long history. When it is understood as being entirely reducible to the sum of (some) human, individual and already morally loaded actions, then the allocation of DMR, and hence of praise and reward or blame and punishment, may be pragmatically difficult, but not conceptually problematic. However, in distributed environments, it is increasingly possible that a network of agents, some human, some artificial (e.g. a program) and some hybrid (e.g. a group of (...) people working as a team thanks to a software platform), may cause distributed moral actions (DMAs). These are morally good or evil (i.e. morally loaded) actions caused by local interactions that are in themselves neither good nor evil (morally neutral). In this article, I analyse DMRs that are due to DMAs, and argue in favour of the allocation, by default and overridably, of full moral responsibility (faultless responsibility) to all the nodes/agents in the network causally relevant for bringing about the DMA in question, independently of intentionality. The mechanism proposed is inspired by, and adapts, three concepts: back propagation from network theory, strict liability from jurisprudence and common knowledge from epistemic logic. (shrink)

That AI will have a major impact on society is no longer in question. Current debate turns instead on how far this impact will be positive or negative, for whom, in which ways, in which places, and on what timescale. In order to frame these questions in a more substantive way, in this prolegomena we introduce what we consider the four core opportunities for society offered by the use of AI, four associated risks which could emerge from its overuse or (...) misuse, and the opportunity costs associated with its under use. We then offer a high-level view of the emerging advantages for organisations of taking an ethical approach to developing and deploying AI. Finally, we introduce a set of five principles which should guide the development and deployment of AI technologies. The development of laws, policies and best practices for seizing the opportunities and minimizing the risks posed by AI technologies would benefit from building on ethical frameworks such as the one offered here. (shrink)

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

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such (...) as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

The synthetization of voices, or speech synthesis, has been an object of interest for centuries. It is mostly realized with a text-to-speech system, an automaton that interprets and reads aloud. This system refers to text available for instance on a website or in a book, or entered via popup menu on the website. Today, just a few minutes of samples are enough to be able to imitate a speaker convincingly in all kinds of statements. This article abstracts from actual products (...) and actual technological realization. Rather, after a short historical outline of the synthetization of voices, exemplary applications of this kind of technology are gathered for promoting the development, and potential applications are discussed critically to be able to limit them if necessary. The ethical and legal challenges should not be underestimated, in particular with regard to informational and personal autonomy and the trustworthiness of media. (shrink)

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We 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. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (shrink)

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...) the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly. (shrink)

In a Different Voice is the little book that started a revolution, making women's voices heard, in their own right and with their own integrity, for virtually the first time in social scientific theorizing about women. Its impact was immediate and continues to this day, in the academic world and beyond.

Addressing fake news requires a multidisciplinary effort The rise of fake news highlights the erosion of long-standing institutional bulwarks against misinformation in the internet age. Concern over the problem is global. However, much remains unknown regarding the vulnerabilities of individuals, institutions, and society to manipulations by malicious actors. A new system of safeguards is needed. Below, we discuss extant social and computer science research regarding belief in fake news and the mechanisms by which it spreads. Fake news has a long (...) history, but we focus on unanswered scientific questions raised by the proliferation of its most recent, politically oriented incarnation. Beyond selected references in the text, suggested further reading can be found in the supplementary materials. (shrink)

There is worldwide concern over false news and the possibility that it can influence political, economic, and social well-being. To understand how false news spreads, Vosoughi et al. used a data set of rumor cascades on Twitter from 2006 to 2017. About 126,000 rumors were spread by ∼3 million people. False news reached more people than the truth; the top 1 of false news cascades diffused to between 1000 and 100,000 people, whereas the truth rarely diffused to more than 1000 (...) people. Falsehood also diffused faster than the truth. The degree of novelty and the emotional reactions of recipients may be responsible for the differences observed. Science, this issue p. 1146 A large-scale analysis of tweets reveals that false rumors spread further and faster than the truth. We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98 agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it. (shrink)

This article reviews the reasons scholars hold that driverless cars and many other AI equipped machines must be able to make ethical decisions, and the difficulties this approach faces. It then shows that cars have no moral agency, and that the term ‘autonomous’, commonly applied to these machines, is misleading, and leads to invalid conclusions about the ways these machines can be kept ethical. The article’s most important claim is that a significant part of the challenge posed by AI-equipped machines (...) can be addressed by the kind of ethical choices made by human beings for millennia. Ergo, there is little need to teach machines ethics even if this could be done in the first place. Finally, the article points out that it is a grievous error to draw on extreme outlier scenarios—such as the Trolley narratives—as a basis for conceptualizing the ethical issues at hand. (shrink)

Contemporary society is in the grip of contractual thinking. Realities are interpreted in contractual terms, and goals are formulated in terms of rational contracts. The leading current conceptions of rationality begin with assumptions that human beings are independent, self-interested or mutually disinterested, individuals; they then typically argue that it is often rational for human beings to enter into contractual relationships with each other.

New technologies from artificial intelligence to drones, and biomedical enhancement make the future of the human family increasingly hard to predict and protect. This book explores how the philosophical tradition of virtue ethics can help us to cultivate the moral wisdom we need to live wisely and well with emerging technologies.

Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacenters (e.g., Amazon). It considers the cloud services providers leasing ‘space in the cloud’ from hosting companies (e.g, Dropbox, Salesforce). And it (...) examines the business and private ‘clouders’ using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of cloud computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and cloud services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using cloud services (banks, law firms, hospitals etc. storing client data in the cloud, e.g.) will have to follow rather more stringent regulations. (shrink)

The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.

There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...) designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)

In der "Kritik der praktischen Vernunft" (1787) begründet Kant seinen wohl bekanntesten Lehrsatz, den Kategorischen Imperativ: "Handle so, daß die Maxime deines Willens jederzeit zugleich als Prinzip einer allgemeinen Gesetzgebung gelten könne". Das Bewußtsein dieses Grundgesetzes der praktischen Vernunft ist nach Kant ein "Faktum der reinen Vernunft", dem sich niemand verschließen kann, und in diesem Faktum sieht er den - nicht weiter herleitbaren und keiner weiteren Herleitung bedürftigen - Beweisgrund der Wirklichkeit unserer Freiheit, den die "Kritik der reinen Vernunft" auf (...) dem Felde der theoretischen Vernunft zwar fordern, aber nicht beibringen konnte. Neben den Schriften David Humes, der sich um eine empirische Begründung allgemeingültiger ethischer Grundsätze bemühte, gilt Kants Ansatz eines rein rational begründeten für jedermann verbindlichen Moralgesetzes bis auf den heutigen Tag als ein starkes und maßgebliches Argument für die Grundlegung einer rationalen Kriterien genügenden und daher allgemein verbindlichen Ethik. Diese Neuausgabe des Textes hält sich strikt an die Fassung der ersten Ausgabe von 1787, d.h. Lautstand, Diktion und die - typisch Kantische - Interpunktion des Originals werden auch dort bewahrt, wo sie heutigen Regeln nicht mehr entsprechen. Lediglich veraltete orthographische Schreibungen und offensichtliche Fehler in der Interpunktion wurden korrigiert, da sie die Lesbarkeit des Textes unnötig erschweren. Lesarten und Korrekturvorschläge späterer Ausgaben sowie die Eintragungen in Kants Handexemplar wurden berücksichtigt oder angemerkt, soweit sie nach dem Stand der neueren Kantforschung noch Beachtung verdienen, und im kritischen Apparat ausgewiesen. Die Einleitung gibt Auskunft über die Entstehung und die Verortung der Schrift in Kants Gesamtwerk und ihre Rezeption, Sachanmerkungen, Register und eine ausführliche Bibliographie geben weitere Hilfen zur Erschließung der Bedeutung des Werkes. (shrink)

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of (...) our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. (shrink)

Virtue ethics is perhaps the most important development within late twentieth-century moral philosophy. Rosalind Hursthouse, who has made notable contributions to this development, here presents a full exposition and defense of her neo-Aristotelian version of virtue ethics. She shows how virtue ethics can provide guidance for action, illuminate moral dilemmas, and bring out the moral significance of the emotions.

"One of the major works in the development of contemporary criticism and philosophy." -- J. Hillis Miller, Yale University Jacques Derrida's revolutionary theories about deconstruction, phenomenology, psychoanalysis, and structuralism, first voiced in the 1960s, forever changed the face of European and American criticism. The ideas in De la grammatologie sparked lively debates in intellectual circles that included students of literature, philosophy, and the humanities, inspiring these students to ask questions of their disciplines that had previously been considered improper. Thirty years (...) later, the immense influence of Derrida's work is still igniting controversy, thanks in part to Gayatri Spivak's translation, which captures the richness and complexity of the original. This corrected edition adds a new index of the critics and philosophers cited in the text and makes one of contemporary criticism's most indispensable works even more accessible and usable. (shrink)

A classic collection of interlocking tales chronicles the near-future development of the robot and features models that have the ability to read minds, experience human emotions, and take over the world--and, perhaps, render humankind itself obsolete. Reprint. 25,000 first printing.

Part of understanding the meaning and power of algorithms means asking what new demands they might make of ethical frameworks, and how they might be held accountable to ethical standards. I develop a definition of networked information algorithms as assemblages of institutionally situated code, practices, and norms with the power to create, sustain, and signify relationships among people and data through minimally observable, semiautonomous action. Starting from Merrill’s prompt to see ethics as the study of “what we ought to do,” (...) I examine ethical dimensions of contemporary NIAs. Specifically, in an effort to sketch an empirically grounded, pragmatic ethics of algorithms, I trace an algorithmic assemblage’s power to convene constituents, suggest actions based on perceived similarity and probability, and govern the timing and timeframes of ethical action. (shrink)

The essays in this volume represent the first steps by philosophers and artificial intelligence researchers toward explaining why it is necessary to add an ...

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (shrink)

Contemporary society is in the grip of contractual thinking. Realities are interpreted in contractual terms, and goals are formulated in terms of rational contracts. The leading current conceptions of rationality begin with assumptions that human beings are independent, self-interested or mutually disinterested, individuals; they then typically argue that it is often rational for human beings to enter into contractual relationships with each other.

This books challenges conventional notions of biological life and death in the area of robotics, discussing issues such as machine consciousness, autonomous AI, and representations of robots in popular culture. Using philosophical approaches alongside scientific theory, this book offers a compelling critique on the changing nature of both humanity and biological death in an increasingly technological world.