The ability of very wealthy individuals (or, as I will call them, the ‘super-rich’) to turn their economic power into political power has been—and remains—an important cause of political inequality. In response, this paper advocates an original solution. Rather than solving the problem through implementing a comprehensive conception of political equality, or through enforcing complex rules about financial disclosure etc., I argue that we should impose a choice on the super-rich. The super-rich must choose between (i) forfeiting the things that (...) make them super-rich, i.e., pay a 100 % tax on their wealth above a certain level, or, (ii) they must forfeit some of their political rights. These rights include entitlements to fund political parties; to stand for office; and to work or volunteer for political parties. The right to vote, though, is not limited. I defend my proposal against non-consequentialist and consequentialist objections. I also argue that it avoids two problems that many attempts to reduce political inequality face; these are the political egalitarian’s dilemma and the problem of political equality’s relative moral importance. (shrink)

Computers are already approving financial transactions, controlling electrical supplies, and driving trains. Soon, service robots will be taking care of the elderly in their homes, and military robots will have their own targeting and firing protocols. Colin Allen and Wendell Wallach argue that as robots take on more and more responsibility, they must be programmed with moral decision-making abilities, for our own safety. Taking a fast paced tour through the latest thinking about philosophical ethics and artificial intelligence, the authors argue (...) that even if full moral agency for machines is a long way off, it is already necessary to start building a kind of functional morality, in which artificial moral agents have some basic ethical sensitivity. But the standard ethical theories don't seem adequate, and more socially engaged and engaging robots will be needed. As the authors show, the quest to build machines that are capable of telling right from wrong has begun. -/- Moral Machines is the first book to examine the challenge of building artificial moral agents, probing deeply into the nature of human decision making and ethics. (shrink)

When courts started publishing judgements, big data analysis within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how natural language processing tools can be used to analyse texts of the court proceedings in order to automatically predict judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our approach highlights the potential of machine (...) learning approaches in the legal domain. We show, however, that predicting decisions for future cases based on the cases from the past negatively impacts performance. Furthermore, we demonstrate that we can achieve a relatively high classification performance when predicting outcomes based only on the surnames of the judges that try the case. (shrink)

In this paper, I set out a new Kantian approach to resolving conflicts between moral obligations for highly autonomous machine agents. First, I argue that efforts to build explicitly moral autonomous machine agents should focus on what Kant refers to as duties of right, which are duties that everyone could accept, rather than on duties of virtue (or “ethics”), which are subject to dispute in particular cases. “Moral” machines must first be rightful machines, I argue. I then show (...) how this shift in focus from ethics to a standard of public right resolves the conflicts in what is known as the "trolley problem" for autonomous ma-chine agents. Finally, I consider how a deontic logic suitable for capturing duties of right might meet Kant’s requirement that rightfully enforceable obligations be consistent in a system of equal freedom under universal law. (shrink)

We propose that the prevalent moral aversion to AWS is supported by a pair of compelling objections. First, we argue that even a sophisticated robot is not the kind of thing that is capable of replicating human moral judgment. This conclusion follows if human moral judgment is not codifiable, i.e., it cannot be captured by a list of rules. Moral judgment requires either the ability to engage in wide reflective equilibrium, the ability to perceive certain facts as moral considerations, moral (...) imagination, or the ability to have moral experiences with a particular phenomenological character. Robots cannot in principle possess these abilities, so robots cannot in principle replicate human moral judgment. If robots cannot in principle replicate human moral judgment then it is morally problematic to deploy AWS with that aim in mind. Second, we then argue that even if it is possible for a sufficiently sophisticated robot to make ‘moral decisions’ that are extensionally indistinguishable from (or better than) human moral decisions, these ‘decisions’ could not be made for the right reasons. This means that the ‘moral decisions’ made by AWS are bound to be morally deficient in at least one respect even if they are extensionally indistinguishable from human ones. Our objections to AWS support the prevalent aversion to the employment of AWS in war. They also enjoy several significant advantages over the most common objections to AWS in the literature. (shrink)

In this paper, I argue that certain Machines can have rights independently of whether they are sentient, or conscious, or whatever you might call it.

Dilemma situations involving the choice of which human life to save in the case of unavoidable accidents are expected to arise only rarely in the context of autonomous vehicles. Nonetheless, the scientific community has devoted significant attention to finding appropriate and acceptable automated decisions in the event that AVs or drivers of AVs were indeed to face such situations. Awad and colleagues, in their now famous paper “The Moral Machine Experiment”, used a “multilingual online ‘serious game’ for collecting large-scale (...) data on how citizens would want AVs to solve moral dilemmas in the context of unavoidable accidents.” Awad and colleagues undoubtedly collected an impressive and philosophically useful data set of armchair intuitions. However, we argue that applying their findings to the development of “global, socially acceptable principles for machine learning” would violate basic tenets of human rights law and fundamental principles of human dignity. To make its arguments, our paper cites principles of tort law, relevant case law, provisions from the Universal Declaration of Human Rights, and rules from the German Ethics Code for Autonomous and Connected Driving. (shrink)

When in 1979 Zenon Pylyshyn, associate editor of Behavioral and Brain Sciences (BBS, a peer commentary journal which I edit) informed me that he had secured a paper by John Searle with the unprepossessing title of [XXXX], I cannot say that I was especially impressed; nor did a quick reading of the brief manuscript -- which seemed to be yet another tedious "Granny Objection"[1] about why/how we are not computers -- do anything to upgrade that impression.

This essay responds to the machine question in the affirmative, arguing that artifacts, like robots, AI, and other autonomous systems, can no longer be legitimately excluded from moral consideration. The demonstration of this thesis proceeds in four parts or movements. The first and second parts approach the subject by investigating the two constitutive components of the ethical relationship—moral agency and patiency. In the process, they each demonstrate failure. This occurs not because the machine is somehow unable to achieve (...) what is considered necessary and sufficient to be a moral agent or patient but because the characterization of agency and patiency already fail to accommodate others. The third and fourth parts respond to this problem by considering two recent alternatives—the all-encompassing ontocentric approach of Luciano Floridi’s information ethics and Emmanuel Levinas’s eccentric ethics of otherness. Both alternatives, despite considerable promise to reconfigure the scope of moral thinking by addressing previously excluded others, like the machine, also fail but for other reasons. Consequently, the essay concludes not by accommodating the alterity of the machine to the requirements of moral philosophy but by questioning the systemic limitations of moral reasoning, requiring not just an extension of rights to machines, but a thorough examination of the way moral standing has been configured in the first place. (shrink)

Intelligent machines (IMs), which have demonstrated remarkable innovations over time, require adequate attention concerning the issue of their duty–rights split in our current society. Although we can remain optimistic about IMs’ societal role, we must still determine their legal-philosophical sense of accountability, as living data bits have begun to pervade our lives. At the heart of IMs are human characteristics used to self-optimize their practical abilities and broaden their societal impact. We used Kant’s philosophical requirements to investigate IMs’ moral (...) dispositions, as the merging of humans with technology has overwhelmingly shaped psychological and corporeal agential capacities. In recognizing the continuous burden of human needs, important features regarding the inalienability of rights have increased the individuality of intelligent, nonliving beings, leading them to transition from questioning to defending their own rights. This issue has been recognized by paying attention to the rational capacities of humans and IMs, which have been connected in order to achieve a common goal. Through this teleological scheme, we formulate the concept of virtual dignity to determine the transition of inalienable rights from humans to machines, wherein the evolution of IMs is essentially imbued through consensuses and virtuous traits associated with human dignity. (shrink)

Just last week (October 4, 2022), the U.S. White House released a blueprint for an A.I. Bill of Rights, consisting of “five principles and associated practices to help guide the design, use, and de...

A key distinction in ethics is between members and nonmembers of the moral community. Over time, our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any (...) autonomous intelligent machines. Such machines exhibit an ability to formulate desires for the course of their own existence; this gives them basic moral standing. While not all machines display autonomy, those which do must be treated as moral patients; to ignore their claims to moral recognition is to repeat past errors. I thus urge moral generosity with respect to the ethical claims of intelligent machines. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, (...) the analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for (...) example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. (shrink)

“This species of device is so radically new that many of its uses will become clear only after it’s been put into operation.” It’s what he said to me. ‘Cause he understood. He knew the real challenge was not building the thing but asking it the right questions in a language intelligible to the machine. And he was the only one who spoke that language.”(Benjamín Labatut, The MANIAC)“Let the whole outside world consist of a long paper tape.”(John von Neumann, (...) 1948) Introduction The Old Dream of... (shrink)

This book questions the book itself, archivization, machines for writing, and the mechanicity inherent in language, the media, and intellectuals. Derrida questions what takes place between the paper and the machine inscribing it. He examines what becomes of the archive when the world of paper is subsumed in new machines for virtualization, and whether there can be a virtual event or a virtual archive. Derrida continues his long-standing investigation of these issues, and ties them into the new themes that (...) governed his teaching and thinking in the past few years: the secret, pardon, perjury, state sovereignty, hospitality, the university, animal rights, capital punishment, the question of what sort of mediatized world is replacing the print epoch, and the question of the “wholly other.” Derrida is remarkable at making seemingly occasional pieces into part of a complexly interconnected trajectory of thought. (shrink)

Intellectual property (IP) offices and courts around the world are debating whether machines are similar enough to humans in terms of their consciousness and creativity to be eligible for inventors...

Machine unlearning (MU) is often analyzed in terms of how it can facilitate the “right to be forgotten.” In this commentary, we show that MU can support the OECD’s five principles for trustworthy AI, which are influencing AI development and regulation worldwide. This makes it a promising tool to translate AI principles into practice. We also argue that the implementation of MU is not without ethical risks. To address these concerns and amplify the positive impact of MU, we offer (...) policy recommendations across six categories to encourage the research and uptake of this potentially highly influential new technology. (shrink)

In this commentary I point out that Palmer mislocates the source of the inverted spectrum, misrepresents the nature of colour science, and offers no reason for prefering one colour machine over another. I conclude nonetheless that talk about “colour machines” is a step in the right direction.

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

Background: The debate over the ethical implications of care robots has raised a range of concerns, including the possibility that such technologies could disrupt caregiving as a core human moral activity. At the same time, academics in information ethics have argued that we should extend our ideas of moral agency and rights to include intelligent machines. Research objectives: This article explores issues of the moral status and limitations of machines in the context of care. Design: A conceptual argument is (...) developed, through a four-part scheme derived from the work of Alasdair MacIntyre. No empirical data are used. Ethical consideration: No primary data were gathered for this study. Secondary sources and authorship have been acknowledged throughout. Findings / discussion: Certain kinds of social experience, including the narrative unity of a life, and the giving and receiving of care, are essential for moral development. Machines, no matter how advanced, cannot participate in such experiences in key respects, and thus cannot develop as practical reasoners. Conclusion: It follows that they cannot be moral agents and that they cannot care. There are, it seems, no such things as care robots. In view of the institutional power of tech companies and commissioning bodies, care practitioners need to take more of a lead in developing new assistive technologies which are appropriate to their practice. (shrink)

Wants, preferences, and cares are physical things or events, not ideas or propositions, and therefore no chain of pure logic can conclude with a want, preference, or care. It follows that no pure-logic machine will ever want, prefer, or care. And its behavior will never be driven in the way that deliberate human behavior is driven, in other words, it will not be motivated or goal directed. Therefore, if we want to simulate human-style interactions with the world, we will (...) need to first understand the physical structure of goal-directed systems. I argue that all such systems share a common nested structure, consisting of a smaller entity that moves within and is driven by a larger field that contains it. In such systems, the smaller contained entity is directed by the field, but also moves to some degree independently of it, allowing the entity to deviate and return, to show the plasticity and persistence that is characteristic of goal direction. If all this is right, then human want-driven behavior probably involves a behavior-generating mechanism that is contained within a neural field of some kind. In principle, for goal directedness generally, the containment can be virtual, raising the possibility that want-driven behavior could be simulated in standard computational systems. But there are also reasons to believe that goal-direction works better when containment is also physical, suggesting that a new kind of hardware may be necessary. (shrink)

Recent philosophy of mind has increasingly focused on the role of technology in shaping, influencing, and extending our mental faculties. Technology extends the mind in two basic ways: through the creative design of artifacts and the purposive use of instruments. If the meaningful activity of technological artifacts were exhaustively described in these mind-dependent terms, then a philosophy of technology would depend entirely on our theory of mind. In this dissertation, I argue that a mind-dependent approach to technology is mistaken. Instead, (...) some machines are best understood as independent participants in their own right, contributing to and augmenting a variety of social practices as active, though often unrecognized, community members. Beginning with Turing’s call for “fair play for machines”, I trace an argument concerning the social autonomy of nonhuman agents through the artificial intelligence debates of the 20th century. I’ll argue that undue focus on the mind has obscured the force of Turing’s proposal, leaving the debates in an unfortunate stalemate. I will then examine a network theoretic alternative to the study of multi-agent complex systems that can avoid anthropocentric, mind-dependent ways of framing human-machine interactions. I argue that this approach allows for both scientific and philosophical treatment of large and complicated sociotechnical systems, and suggests novel methods for designing, managing, and maintaining such systems. Rethinking machines in mind-independent terms will illuminate the nature, scope, and evolution of our social and technological practices, and will help clarify the relationships between minds, machines, and the environments we share. (shrink)

According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to (...) escape the problem (arguably, the only way) is if the robot can be shown to be a moral patient – to deserve a particular moral status. If so, it isn’t clear how functional intentionality could remain plausible (something like “phenomenal intentionality” would be required). Finally, while it would have seemed that a reasonable strategy for establishing the moral status of intelligent machines would be to demonstrate that the machine possessed genuine intentionality, the composition argument suggests that the order of precedence is reversed: The machine must first be shown to possess a particular moral status before it is a candidate for having genuine intentionality. (shrink)

Machines were introduced as calculating devices to simulate operations carried out by human computors following fixed algorithms: this is true for the early mechanical calculators devised by Pascal and Leibniz, for the analytical engine built by Babbage, and the theoretical machines introduced by Turing. The distinguishing feature of the latter is their universality: They are claimed to be able to capture any algorithm whatsoever and, conversely, any procedure they can carry out is evidently algorithmic. The study of such "paper machines" (...) by mathematical means is the topic of our contribution. This is not only in accord with its usual understanding in computer science, but conceptually and historically right, when we recall the purpose for which Turing machines were introduced. (shrink)

This book questions the book itself, archivization, machines for writing, and the mechanicity inherent in language, the media, and intellectuals. Derrida questions what takes place between the paper and the machine inscribing it. He examines what becomes of the archive when the world of paper is subsumed in new machines for virtualization, and whether there can be a virtual event or a virtual archive. Derrida continues his long-standing investigation of these issues, and ties them into the new themes that (...) governed his teaching and thinking in the past few years: the secret, pardon, perjury, state sovereignty, hospitality, the university, animal rights, capital punishment, the question of what sort of mediatized world is replacing the print epoch, and the question of the “wholly other.” Derrida is remarkable at making seemingly occasional pieces into part of a complexly interconnected trajectory of thought. (shrink)

In this paper, I set out some basic elements of a deontic logic with an implementation appropriate for handling conflicting legal obligations for purposes of programming autonomous machine agents. Kantian justice demands that the prescriptive system of enforceable public laws be consistent, yet statutes or case holdings may often describe legal obligations that contradict; moreover, even fundamental constitutional rights may come into conflict. I argue that a deontic logic of the law should not try to work around such (...) conflicts but, instead, identify and expose them so that the rights and duties that generate inconsistencies in public law can be explicitly qualified and the conflicts resolved. I then argue that a credulous, non-monotonic deontic logic can describe inconsistent legal obligations while meeting Kant’s demand for consistency in the prescriptive system of public law. Finally, I propose an implementation of this logic via a modified form of “answer set programming,” which I demonstrate with some simple examples. (shrink)

Pozzi provides a thought-provoking account of how machine-learning clinical prediction models (such as Prediction Drug Monitoring Programmes (PDMPs)) may exacerbate testimonial injustice.1 In this response, I generalise Pozzi’s concerns about PDMPs to traditional models of clinical practice and question the claim that inaccurate clinicians are necessarily preferential to inaccurate machine-learning models. I then explore Pozzi’s concern that such models may deprive patients of a right to ‘convey information’. I suggest that machine-learning tools may be used to enhance, (...) rather than frustrate, this right, through the perspective of hermeneutical justice. Pozzi objects to the introduction of machine-learning risk prediction tools in clinical care, due to their being ‘epistemically opaque’, often inaccurate, and a threat to patients’ testimonial justice. Through the example of psychiatry, I suggest this stance idealises traditional models of clinical practice. I propose that clinicians’ judgements are often equally vulnerable to opaque subjectivity, bias and epistemic injustice. For instance, the use of clinical observation or collateral interviewing might be conceptualised as a threat to testimonial justice, by neglecting patients’ own perspectives or voices. In practice, clinical risk prediction often follows inconsistent and somewhat subjective clinical heuristics, which are difficult to summarise or evaluate. Further, although Pozzi diminishes machine-learning …. (shrink)

Social media data hold considerable potential for predicting health-related conditions. Recent studies suggest that machine-learning models may accurately predict depression and other mental health-related conditions based on Instagram photos and Tweets. In this article, it is argued that individuals should have a sui generis right not to be subjected to AI profiling based on publicly available data without their explicit informed consent. The article (1) develops three basic arguments for a right to protection of personal data trading on the (...) notions of social control and stigmatization, (2) argues that a number of features of AI profiling make individuals more exposed to social control and stigmatization than other types of data processing (the exceptionalism of AI profiling), (3) considers a series of other reasons for and against protecting individuals against AI profiling based on publicly available data, and finally (4) argues that the EU General Data Protection Regulation does not ensure that individuals have a right not to be AI profiled based on publicly available data. (shrink)

The tape is divided into squares, each square bearing a single symbol—'0' or '1', for example. This tape is the machine's general-purpose storage medium: the machine is set in motion with its input inscribed on the tape, output is written onto the tape by the head, and the tape serves as a short-term working memory for the results of intermediate steps of the computation. The program governing the particular computation that the machine is to perform is also (...) stored on the tape. A small, fixed program that is 'hard-wired' into the head enables the head to read and execute the instructions of whatever program is on the tape. The machine's atomic operations are very simple—for example, 'move left one square', 'move right one square', 'identify the symbol currently beneath the head', 'write 1 on the square that is beneath the head', and 'write 0 on the square that is beneath the head'. Complexity of operation is achieved by the chaining together of large numbers of these simple atoms. Any universal Turing machine can be programmed to carry out any calculation that can be performed by a human mathematician working with paper and pencil in accordance with some algorithmic method. This is what is meant by calling these machines 'universal'. (shrink)

As we increasingly delegate decision-making to algorithms, whether directly or indirectly, important questions emerge in circumstances where those decisions have direct consequences for individual rights and personal opportunities, as well as for the collective good. A key problem for policymakers is that the social implications of these new methods can only be grasped if there is an adequate comprehension of their general technical underpinnings. The discussion here focuses primarily on the case of enforcement decisions in the criminal justice system, (...) but draws on similar situations emerging from other algorithms utilised in controlling access to opportunities, to explain how machine learning works and, as a result, how decisions are made by modern intelligent algorithms or 'classifiers'. It examines the key aspects of the performance of classifiers, including how classifiers learn, the fact that they operate on the basis of correlation rather than causation, and that the term 'bias' in machine learning has a different meaning to common usage. An example of a real world 'classifier', the Harm Assessment Risk Tool (HART), is examined, through identification of its technical features: the classification method, the training data and the test data, the features and the labels, validation and performance measures. Four normative benchmarks are then considered by reference to HART: (a) prediction accuracy (b) fairness and equality before the law (c) transparency and accountability (d) informational privacy and freedom of expression, in order to demonstrate how its technical features have important normative dimensions that bear directly on the extent to which the system can be regarded as a viable and legitimate support for, or even alternative to, existing human decision-makers. (shrink)

The operations of deep networks are widely acknowledged to be inscrutable. The growing field of Explainable AI has emerged in direct response to this problem. However, owing to the nature of the opacity in question, XAI has been forced to prioritise interpretability at the expense of completeness, and even realism, so that its explanations are frequently interpretable without being underpinned by more comprehensive explanations faithful to the way a network computes its predictions. While this has been taken to be a (...) shortcoming of the field of XAI, I argue that it is broadly the right approach to the problem. (shrink)

Since the 2010s, popular YouTube channels have used derogatory humour at the expense of gendered and racialised others. Founded upon the perception of an influx of ‘wokeness’ in comedy, these videos mock the mythologised ‘unfunny, angry SJW’ and teach the audience to laugh at enemies of the alt-right. Although empirical research has analysed the algorithmic radicalisation of viewers, few have addressed the role of cultural discourses in disseminating alt-right ideology through online media. Here, the right-wing ‘pipeline’ is understood as a (...) tool of radicalisation that weaponises laughter as a tool of regulations and oppression. This paper analyzes the production of derogatory laughter by studying a network of North American content creators including Russell Peters, Lilly Singh, Jordan Peterson, Steven Crowder, and Matt Walsh, using critical tools from psychoanalysis, social psychology, and critical humour studies. Contrary to the alt-right rhetoric that ‘edgy’ humour is harmless, this paper posits derogatory humour as a tool of marginalisation and domination that reinforces white supremacist and cisnormative patriarchal value systems. (shrink)

Businesses increasingly rely on algorithms that are data-trained sets of decision rules (i.e., the output of the processes often called “machine learning”) and implement decisions with little or no human intermediation. In this article, we provide a philosophical foundation for the claim that algorithmic decision-making gives rise to a “right to explanation.” It is often said that, in the digital era, informed consent is dead. This negative view originates from a rigid understanding that presumes informed consent is a static (...) and complete transaction. Such a view is insufficient, especially when data are used in a secondary, noncontextual, and unpredictable manner—which is the inescapable nature of advanced artificial intelligence systems. We submit that an alternative view of informed consent—as an assurance of trust for incomplete transactions—allows for an understanding of why the rationale of informed consent already entails a right to ex post explanation. (shrink)

This article follows Jacques Derrida, who follows the animal-machine. In his lecture The Animal That Therefore I Am, Derrida could easily have swapped “the animal” for “the machine” . In fact, throughout his readings of René Descartes, Martin Heidegger, Jacques Lacan, and Emmanuel Levinas, the machine emerges right alongside the animal. In defining the limits of the human, these thinkers present the animal and the machine together in order to elevate the human. Unlike the human, who (...) responds, the animal-machine merely reacts. The animal-machine may approximate certain human actions, but it can never, according to Descartes, in Derrida’s words, “respond to our questions” and will always suffer from a “lack .. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:The Right HeartIngrid GouldI remarked to a friend, “We haven’t spoken since my arrest!” Alarm and confusion clouded his face, given my half-century of squeaky-clean living. “Cardiac arrest,” I clarified. “The fire department rebooted me.”An electrophysiologist diagnosed Arrhythmogenic Right Ventricular Dysplasia, prescribed medication, and implanted a defibrillator. For the next three-and-a-half years, he helped me live with a disease I didn’t know existed until he told me I had (...) it.The disease progressed—an ironic, disease-centric term since its advancement was to my detriment— prompting my cardiologist to recommend seeing someone who specialized in heart failure. I resisted the very idea of heart failure, a terrible term for a struggling organ, but took her advice and scheduled an appointment.The new cardiologist urged transplant testing, a lengthy process. I agreed, figuring that by the time I needed a new heart in 15–20 years, they’d be rolling off 3D printers.To record occasional transplant musings and inchoate fears and perhaps, over time, untangle them, I began journaling. I chronicled my passage through the echocardiogram, heart catheterization, 31 tubes of bloodwork, interviews with different clinical specialties, a pulmonary function test in a machine reminiscent of Star Trek’s Transporter, and more. Testing had barely begun when my medication stopped working—a Halloween shock.I began a harsher medication, underwent an ablation, and spent six weeks in a wearable defibrillator, a vest with abundant wires, and a purse-sized battery pack that made me resemble a character in [End Page 123] the Jetsons. This attire did not bring holiday comfort or joy to the TSA1 when I flew to visit my sister. As my R-waves faded to a whisper, I swapped the vest for a second implanted defibrillator, substantially more sensitive than the first.In early 2018, we learned I had qualified for transplant listing, though I wished to get as much mileage as possible from the original engine. My cardiologist warned, “There is no Plan B—no machine, device, or medication for the long-term. You will need a transplant.” He explained that since most cardiac patients have left-heart problems, companies develop products for the left side of the heart. My problem was on the right—a tiny market. He also cautioned that a patient needs to be sick enough to warrant transplant and well enough to remain a candidate, survive the surgery, and recover.Although clinically I was ready, I was not personally ready. I felt too good to trade an excellent quality of life for the promised miserable post-transplant year. The cardiologist wisely asked if I wanted to speak with another patient. When I requested someone beyond the dreaded first year, he put me in touch with two women who had received new hearts a few years earlier and befriended each other. They soon became my invaluable mentors and cherished friends. I will never forget seeing them stride into our first meeting and thinking, “They are beautiful! They look totally normal!”By May, climbing four flights of stairs took as much effort as five used to take. Tests confirmed further deterioration and suggested I had 7–13 months of declining health before my heart would give out completely. We chose a date for hospital admission, and I started telling people outside my immediate family. Most were flabbergasted, believing heart transplants were the last hope of the desperately ill. I did not look moribund, though, apparently, I was.The eight months after my first transplant appointment let me prepare psychologically to bid farewell to my heart—the metaphor for kindness, love, and bravery in our culture—and to welcome a new organ from a generous person less medically fortunate than I.In the hospital, I met others awaiting their hearts. A sudden intimacy arises when mortal choices catapult people into a medical realm suggestive of science fiction. Add the emotional intensity that accompanies knowing your extended life comes courtesy of a person who breathes no more on this earth and you wonder how an organ recipient integrates sorrow and gratitude.Two weeks after I was hospitalized, my cardiologist informed me the wait was over... (shrink)

Policymakers are responsible for key decisions about political governance. Usually, they are selected or elected based on experience and then supported in their decision-making by the additional counsel of subject experts. Those satisfied with this system believe these individuals – generally speaking – will have the right intuitions about the best types of action. This is important because political decisions have ethical implications; they affect how we all live in society. Nevertheless, there is a wealth of research that cautions against (...) trusting human judgment as it can be severely flawed. This paper will look at the root causes of the most common errors of human judgment before arguing – contra the instincts of many – that future AI systems could take a range of political decisions more reliably. I will argue that, if/when engineers establish ethically robust systems, governments will have a moral obligation to refer to them as a part of decision-making. (shrink)

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong (...) desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three diferent aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness. (shrink)

Wendell Wallach and Colin Allen’s Moral Machines: Teaching Robots Right From Wrong (Oxford University Press, 2009) explores efforts to develop machines that, not only can be employed for good or bad ends, but which themselves can be held morally accountable for what they do— artificial moral agents (AMAs). This essay is a critical response to Wallach and Allen’s conjectures. Although Wallach and Allen do not suggest that we are close to being able to create full-fledged AMAs, they do talk seriously (...) about making incremental progress in the direction of creating them (even if we never fully succeed). However, there are important questions about the moral development of AMAs that Moral Machines does not address. Given the responsibilities entrusted to human moral agents, we take questions about their moral development very seriously. In the case of children, the hope is that eventually they will develop into full-fledged moral agents. How might we expect this to go with less than fully formed AMAs? Will there be a comparable story of moral development and moral education that we can tell? (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Journal of the History of Philosophy 40.1 (2002) 122-123 [Access article in PDF] Book Review Spirits and Clocks: Machine & Organism in Descartes Dennis Des Chene. Spirits and Clocks: Machine & Organism in Descartes. Ithaca, NY and London: Cornell University Press, 2001. Pp. xiii + 181. Cloth, $39.95. Confronted with the thousandth "entirely new" interpretation of the Cartesian mind-body union, one sometimes wonders whether anything new can (...) in fact be said about the great Descartes. Once again, after his invaluable and prize-winning Physiologia (Cornell University Press, 1996), Des Chene proves that a serious historian, with a keen awareness of historical context, actually can. Unlike the usual accounts of Descartes's animal-machine, Des Chene does not concentrate on the all too familiar set of questions whether or not machines can think, sense, etc. Instead, Des Chene interprets the machine-metaphor the way Descartes meant it to be, viz. as a model for explaining animal and human physiology instead of (cognitive) psychology. Des Chene's central claim is that the Traité de l'Homme and Descartes's later (unpublished) physiological tracts are an attempt to replace scholastic commentaries on Aristotle's De Anima, itself discussed in this book's companion volume Life's Forms (Cornell University Press, 2000). Spirits and Clocks investigates how Descartes's general mechanistic program (outlined in Physiologia) is applied to the field of animal and human life. This project in itself had a far more lasting influence than Descartes's specific and often bizarre physiological explanations. Therefore, Des Chene rightly concentrates on the philosophical aspects of Descartes's general project of "mechanizing" physiology. His short but illuminating book studies a wide range of ontological, epistemological, and even aesthetic aspects of the machine metaphor and, although this is not the express goal [End Page 122] of the book, it also sheds new light on the epistemology and metaphysics of the Meditations. In this sense Spirits and Clocks is not only a significant contribution to the history of biology but first and foremost a must for historians of philosophy.Des Chene explains that the use of a machine model in physiology was neither new nor entirely unacceptable to the Aristotelians. What is new is Descartes's use of it. His mechanistic understanding of the body as a machine is incompatible with accepting the soul as the source of life and the principle of all our physiological and psychological capacities, while Aristotelians had no problem in accepting both the soul and certain machine models of the body. (Aristotle himself uses the lever to explain animal motion.) Des Chene sketches Descartes's attempt to explain all physiological processes by means of the physical properties of material parts that obey the general laws of motion, excluding all talk of ends. In this context, the use of illustrations is of considerable importance: though they cannot per se convey a denial of a "soul-model" of physiology, they strongly suggest that the (mechanistically understood) machine is all there is to say about the functions of human and animal bodies. Des Chene offers an interesting, albeit sometimes somewhat speculative and ahistoric, discussion of the aesthetic aspects of the machine model.As Des Chene showed in his Physiologia, the rejection of teleology is one of the main goals of Descartes's physics. However, although Descartes may be successful in rejecting the view that stones fall down from some kind of desire to reach their final destiny, he is less successful in denying that the eye is meant for seeing (and hence for our self-preservation). Des Chene gives a truly fascinating account of the limits of Descartes's denial of teleology in physiology. This includes questions about the physical unity of the human body: how can I explain why I have this body and how can I even identify this body as a unit without invoking ends? Similarly, Descartes takes the healthy, "normally" functioning body as the norm of his investigations. But, again, can he do so without acknowledging some form of teleology? Descartes's answer in most of these cases is that the final goals... (shrink)

Machines have always been a tool or technical instrument for human beings to facilitate and to accelerate processes through mechanical power. The same applies to robots nowadays – the next step in the evolution of machines. Over the course of the last few years, robot usage in society has expanded enormously, and they now carry out a remarkable number of tasks for us. It seems we are on the eve of a historic revolution that will change everything we know right (...) now. But not only robots have an impact on our life. It is digitization in its entirety, including smart applications and games, that confronts us with new spaces. This special volume of Ethics in Progress tries to broaden our understanding of a philosophical field – robots and digitization – that is still in its infancy in terms of it research and literature. (shrink)

I recall an old man selling Paul Lafargue’s Right to be Lazy on a busy street in the Latin Quarter in the 1980s. At the time, I was writing then my first book on the history of work time and leisure and felt by seeing this strange and grumpy man so energetically promoting the nearly forgotten work of Marx’s son-in-law somehow vindicated in my efforts. Paul Lafargue’s pamphlet makes an interesting assumption: The “natural” state of human being was relaxation and (...) that only a century or so of propaganda convinced the naïve worker and labor movement to embrace the doctrine of the “right” to work. The industrial revolution had produced the craziness of workers’ overproduction and legions of savants and servants for the small utterly unbusy rich. Once freed from the illusion of the right to work, machines, Lafargue insisted, would liberate us all from the drudgery of labor and let us live as the ancient Greek philosophers had dreamed—but without the dependence upon slaves. Lafargue’s view was hardly unique for its day. Many in the late nineteenth century believed that overwork caused production gluts and the irrational excesses of the rich. Busyness was a false doctrine of modern capitalism that was devoted to endlessly extending and intensifying work. Before and after him, many fought to win freedom from busyness with the reduction of worktime. But Lafargue’s dream that mechanical progress would liberate humanity from labor hardly happened. Instead, the “overproduction” that ceaseless toil created was “absorbed” by mass consumption. Even the “wastefulness” of the rich and their minions came to be seen merely as indifferent contributions to the Gross Domestic Product. So what happened? (shrink)

In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. -/- As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? (...) What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? -/- The essays in this collection by researchers from both humanities and science describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility, and accurately modeling essential physician-machine-patient relationships. -/- This collection is the first book to address these 21st-century concerns. (shrink)