Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit (...) people’s ability to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (shrink)

A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. (...) Historical precedent speaks against it, but the main problem is that the prediction fundamentally misunderstands how capitalism works—its incentives to increase or decrease production, its principles of income allocation, and the underlying conception of merit. (shrink)

In this paper, we discuss the ethics of automated driving. More specifically, we discuss responsible human-robot coordination within mixed traffic: i.e. traffic involving both automated cars and conventional human-driven cars. We do three main things. First, we explain key differences in robotic and human agency and expectation-forming mechanisms that are likely to give rise to compatibility-problems in mixed traffic, which may lead to crashes and accidents. Second, we identify three possible solution-strategies for achieving better human-robot coordination within mixed traffic. Third, (...) we identify important ethical challenges raised by each of these three possible strategies for achieving optimized human-robot cordination in this domain. Among other things, we argue that we should not just explore ways of making robotic driving more like human driving. Rather, we ought also to take seriously potential ways of making human driving more like robotic driving. Nor should we assume that complete automation is always the ideal to aim for; in some traffic-situations, the best results may be achieved through human-robot collaboration. Ultimately, our main aim in this paper is to argue that the new field of the ethics of automated driving needs take seriously the ethics of mixed traffic and responsible human-robot coordination. (shrink)

Automating Humanity is the shocking and eye-opening new manifesto from international award-winning designer Joe Toscano that unravels and lays bare the power agendas of the world's greatest tech titans in plain language, and delivers a fair warning to policymakers, civilians, and industry professionals alike: we need a strategy for the future, and we need it now. Automating Humanity is an insider's perspective on everything Big Tech doesn't want the public to know--or think about--from the addictions installed on a global scale (...) to the profits being driven by fake news and disinformation, to the way they're manipulating the world for profit and using our data to train systems that will automate jobs at an explosive, unprecedented scale. Toscano provides a critique of modern regulation, including parts of the new European Union's General Data Proctection Regulation (GDPR) suggesting how we can create proactive, adaptable regulation that satisfies both the needs of consumer safety and commercial success in the international economy. The content touches on everything from technology, economics, and public policy to psychology, history, and ethics, and is written in a way that is accessible to everyone from the average reader to the technical expert. (shrink)

Artificial intelligence-based (AI) technologies such as machine learning (ML) systems are playing an increasingly relevant role in medicine and healthcare, bringing about novel ethical and epistemological issues that need to be timely addressed. Even though ethical questions connected to epistemic concerns have been at the center of the debate, it is going unnoticed how epistemic forms of injustice can be ML-induced, specifically in healthcare. I analyze the shortcomings of an ML system currently deployed in the USA to predict patients’ likelihood (...) of opioid addiction and misuse (PDMP algorithmic platforms). Drawing on this analysis, I aim to show that the wrong inflicted on epistemic agents involved in and affected by these systems’ decision-making processes can be captured through the lenses of Miranda Fricker’s account of hermeneutical injustice. I further argue that ML-induced hermeneutical injustice is particularly harmful due to what I define as an automated hermeneutical appropriation from the side of the ML system. The latter occurs if the ML system establishes meanings and shared hermeneutical resources without allowing for human oversight, impairing understanding and communication practices among stakeholders involved in medical decision-making. Furthermore and very much crucially, an automated hermeneutical appropriation can be recognized if physicians are strongly limited in their possibilities to safeguard patients from ML-induced hermeneutical injustice. Overall, my paper should expand the analysis of ethical issues raised by ML systems that are to be considered epistemic in nature, thus contributing to bridging the gap between these two dimensions in the ongoing debate. (shrink)

Many of the benefits and burdens we might experience in our lives — from bank loans to bail terms — are increasingly decided by institutions relying on algorithms. In a sense, this is nothing new: algorithms — instructions whose steps can, in principle, be mechanically executed to solve a decision problem — are at least as old as allocative social institutions themselves. Algorithms, after all, help decision-makers to navigate the complexity and variation of whatever domains they are designed for. In (...) another sense, however, this development is startlingly new: not only are algorithms being deployed in ever more social contexts, they are being mechanically executed not merely in principle, but pervasively in practice. Due to recent advances in computing technology, the benefits and burdens we experience in our lives are now increasingly decided by automata, rather than each other. How are we to morally assess these technologies? In this chapter, I propose a preliminary conceptual schema for identifying and locating the various injustices of automated, algorithmic social decision systems, from a broadly liberal perspective. (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of automated (...) theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

How should automated vehicles react in emergency circumstances? Most research projects and scientific literature deal with this question from a moral perspective. In particular, it is customary to treat emergencies involving AVs as instances of moral dilemmas and to use the trolley problem as a framework to address such alleged dilemmas. Some critics have pointed out some shortcomings of this strategy and have urged to focus on mundane traffic situations instead of trolley cases involving AVs. Besides, these authors rightly point (...) out the political nature of the most interesting debates involving AVs. However, in our view, they do not offer an adequate account of the distinction between ethics and politics and still see their proposals as contributions to the ethics of AVs. We argue that many of the interesting questions about how AVs should behave, both in emergency and other situations, are of political, and not moral, nature. This view is based on a conception of politics and political normativity that we have developed elsewhere and that we call “political minimalism.” Additionally, we show that this proposed perspective has significant consequences for the design, management, and regulation of transport systems. (shrink)

Theorems in automated theorem proving are usually proved by formal logical proofs. However, there is a subset of problems which humans can prove by the use of geometric operations on diagrams, so called diagrammatic proofs. Insight is often more clearly perceived in these proofs than in the corresponding algebraic proofs; they capture an intuitive notion of truthfulness that humans find easy to see and understand. We are investigating and automating such diagrammatic reasoning about mathematical theorems. Concrete, rather than general diagrams (...) are used to prove particular concrete instances of the universally quantified theorem. The diagrammatic proof is captured by the use of geometric operations on the diagram. These operations are the inference steps of the proof. An abstracted schematic proof of the universally quantified theorem is induced from these proof instances. The constructive -rule provides the mathematical basis for this step from schematic proofs to theoremhood. In this way we avoid the difficulty of treating a general case in a diagram. One method of confirming that the abstraction of the schematic proof from the proof instances is sound is proving the correctness of schematic proofs in the meta-theory of diagrams. These ideas have been implemented in the system, called Diamond, which is presented here. (shrink)

Human obsolescence is imminent. We are living through an era in which our activity is becoming less and less relevant to our well-being and to the fate of our planet. This trend toward increased obsolescence is likely to continue in the future, and we must do our best to prepare ourselves and our societies for this reality. Far from being a cause for despair, this is in fact an opportunity for optimism. Harnessed in the right way, the technology that hastens (...) our obsolescence can open us up to new utopian possibilities and enable heightened forms of human flourishing. (shrink)

The article explores the problem of preferable technological changes in the context of work. To this end, it addresses the ‘why’ (motives and values) and the ‘how’ (organizational forms) of automation from a normative perspective. Concerning the ‘why,’ automation processes are currently mostly driven by values of economic efficiency. Yet, since automation processes are part of the basic structure of society, as is the division of labor, considerations of justice apply to them. As for the ‘how,’ the (...) article suggests ‘fair hybrid cooperation’ as an alternative ideal to guide automation priorities. It is achieved when the division of labor between humans and machines does not hinder, and preferably enables, workers’ experience of certain primary qualities in their work activity. By analogy with Rawls’ primary goods, these are qualities that it is necessary for every worker to experience in order to pursue their life plans: security, self-direction, self-development, dignity, and recognition. According to this criterion, the tasks to automate first are those hindering these contributive primary qualities. This provides us with a normative vocabulary and a standard to orient automation decisions but also to assess existing organizational forms and envisage alternative cooperative imaginaries. To illustrate how the ideal may play out in the real world, the article concludes with a ‘fair hybrid cooperation test’ and a nurse bots case for meaningful work. (shrink)

Automation can bring the risk of technological unemployment, as employees are replaced by machines that can carry out the same or similar work at a fraction of the cost. Some believe that the appropriate response is to tax automation. In this paper, I explore the justifiability of view, maintaining that we can embrace automation so long as we compensate those employees whose livelihoods are destroyed by this process by creating new opportunities for employment. My contribution in this (...) paper is important not only because I develop a theoretical framework that we can use to resolve this urgent policy dispute—a dispute that has been discussed extensively by labour economists, tax lawyers, and policymakers, but largely neglected by political philosophers—but also because my analysis sheds lights on a wider range of controversies relating to the moral and political importance of unemployment. (shrink)

Many ethicists writing about automated systems attribute agency to these systems. Not only that; they seemingly attribute an autonomous or independent form of agency to these machines. This leads some ethicists to worry about responsibility-gaps and retribution-gaps in cases where automated systems harm or kill human beings. In this paper, I consider what sorts of agency it makes sense to attribute to most current forms of automated systems, in particular automated cars and military robots. I argue that whereas it indeed (...) makes sense to attribute different forms of fairly sophisticated agency to these machines, we ought not to regard them as acting on their own, independently of any human beings. Rather, the right way to understand the agency exercised by these machines is in terms of human–robot collaborations, where the humans involved initiate, supervise, and manage the agency of their robotic collaborators. This means, I argue, that there is much less room for justified worries about responsibility-gaps and retribution-gaps than many ethicists think. (shrink)

Robots are widely expected—and pushed—to transform open-field agriculture, but these visions remain wedded to optimizing monocultural farming systems. Meanwhile there is little pull for automation from ecology-based, diversified farming realms. Noting this gap, we here explore the potential for robots to foster an agroecological approach to crop production. The research was situated in The Netherlands within the case of _pixel cropping_, a nascent farming method in which multiple food and service crops are planted together in diverse assemblages employing agroecological (...) practices such as intercropping and biological pest control. Around this case we engaged with a variety of specialists in discussion groups, workshops, and design challenges to explore the potential of field robots to meet the multifaceted demands of highly diverse agroecological cropping systems. This generated a spectrum of imaginations for how automated tools might—or might not—be appropriately used, ranging from fully automated visions, to collaborative scenarios, to fully analogue prototypes. We found that automating agroecological cropping systems requires finding ways to imbue the ethos of agroecology into designed tools, thereby seeking to overcome tensions between production aims and other forms of social and ecological care. We conclude that a rethinking of automation is necessary for agroecological contexts: not as a blueprint for replacing humans, but making room for analogue and hybrid forms of agricultural work. These findings highlight a need for design processes which include a diversity of actors, involve iterative design cycles, and incorporate feedback between designers, practitioners, tools, and cropping systems. (shrink)

Despite numerous ethical examinations of automated vehicles, philosophers have neglected to address how these technologies will affect vulnerable people. To account for this lacuna, researchers must analyze how driverless cars could hinder or help social justice. In addition to thinking through these aspects, scholars must also pay attention to the extensive moral dimensions of automated vehicles, including how they will affect the public, nonhumans, future generations, and culturally significant artifacts. If planners and engineers undertake this task, then they will have (...) to prioritize their efforts to avoid additional harm. The author shows how employing an approach called a “complex moral assessment” can help professionals implement these technologies into existing mobility systems in a just and moral fashion. (shrink)

This work provides proof-search algorithms and automated counter-model extraction for a class of STIT logics. With this, we answer an open problem concerning syntactic decision procedures and cut-free calculi for STIT logics. A new class of cut-free complete labelled sequent calculi G3LdmL^m_n, for multi-agent STIT with at most n-many choices, is introduced. We refine the calculi G3LdmL^m_n through the use of propagation rules and demonstrate the admissibility of their structural rules, resulting in auxiliary calculi Ldm^m_nL. In the single-agent case, we (...) show that the refined calculi Ldm^m_nL derive theorems within a restricted class of (forestlike) sequents, allowing us to provide proof-search algorithms that decide single-agent STIT logics. We prove that the proof-search algorithms are correct and terminate. (shrink)

In their proof-of-concept, Meier and colleagues describe the purpose and programming decisions underpinning Medical Ethics Advisor, an automated decision support system used t...

In this article we introduce a logical structure for normative reasoning, called Normative Detachment Structure with Ideal Conditions, that can be used to represent the content of certain legal texts in a normalized way. The structure exploits the deductive properties of a system of bimodal logic able to distinguish between ideal and actual normative statements, as well as a novel formalization of conditional normative statements able to capture interesting cases of contrary-to-duty reasoning and to avoid deontic paradoxes. Furthermore, we illustrate (...) how the theoretical framework proposed can be mechanized to get an automated procedure of query-answering on an example of legal text. (shrink)

Automated influence, delivered by digital targeting technologies such as targeted advertising, digital nudges, and recommender systems, has attracted significant interest from both empirical researchers, on one hand, and critical scholars and policymakers on the other. In this paper, we argue for closer integration of these efforts. Critical scholars and policymakers, who focus primarily on the social, ethical, and political effects of these technologies, need empirical evidence to substantiate and motivate their concerns. However, existing empirical research investigating the effectiveness of these (...) technologies (or lack thereof), neglects other morally relevant effects—which can be felt regardless of whether or not the technologies "work" in the sense of fulfilling the promises of their designers. Drawing from the ethics and policy literature, we enumerate a range of questions begging for empirical analysis—the outline of a research agenda bridging these fields—and issue a call to action for more empirical research that takes these urgent ethics and policy questions as their starting point. (shrink)

Artificial intelligence is poised to eliminate millions of jobs, from finance to truck driving. But artisanal products are valued precisely because of their human origins, and thus have some inherent “immunity” from AI job loss. At the same time, artisanal labor, combined with technology, could potentially help to democratize the economy, allowing independent, small-scale businesses to flourish. Could AI, robotics and related automation technologies enhance the economic viability and environmental sustainability of these beloved crafting professions, perhaps even expanding their (...) niche to replace some job loss in other sectors? In this paper, we compare the problems created by the current mass production economy and potential solutions from an artisanal economy. In doing so, the paper details the possibilities of utilizing AI to support hybrid forms of human–machine production at the microscale; localized and sustainable value chains at the mesoscale; and networks of these localized and sustainable producers at the macroscale. In short, a wide range of automation technologies are potentially available for facilitating and empowering an artisanal economy. Ultimately, it is our hope that this paper will facilitate a discussion on a future vision for more “generative” economic forms in which labor value, ecological value and social value can circulate without extraction or alienation. (shrink)

Patent landscaping is the process of finding patents related to a particular topic. It is important for companies, investors, governments, and academics seeking to gauge innovation and assess risk. However, there is no broadly recognized best approach to landscaping. Frequently, patent landscaping is a bespoke human-driven process that relies heavily on complex queries over bibliographic patent databases. In this paper, we present Automated Patent Landscaping, an approach that jointly leverages human domain expertise, heuristics based on patent metadata, and machine learning (...) to generate high-quality patent landscapes with minimal effort. In particular, this paper describes a flexible automated methodology to construct a patent landscape for a topic based on an initial seed set of patents. This approach takes human-selected seed patents that are representative of a topic, such as operating systems, and uses structure inherent in patent data such as references and class codes to “expand” the seed set to a set of “probably-related” patents and anti-seed “probably-unrelated” patents. The expanded set of patents is then pruned with a semi-supervised machine learning model trained on seed and anti-seed patents. This removes patents from the expanded set that are unrelated to the topic and ensures a comprehensive and accurate landscape. (shrink)

This book reports on theoretical and practical analyses of the ethical challenges connected to driving automation. It also aims at discussing issues that have arisen from the European Commission 2020 report “Ethics of Connected and Automated Vehicles. Recommendations on Road Safety, Privacy, Fairness, Explainability and Responsibility”. Gathering contributions by philosophers, social scientists, mechanical engineers, and UI designers, the book discusses key ethical concerns relating to responsibility and personal autonomy, privacy, safety, and cybersecurity, as well as explainability and human-machine interaction. (...) On the one hand, it examines these issues from a theoretical, normative point of view. On the other hand, it proposes practical strategies to face the most urgent ethical problems, showing how the integration of ethics and technology can be achieved through design practices. All in all, this book fosters a multidisciplinary approach where philosophy, ethics, and engineering are integrated, rather than just juxtaposed. It is meant to inform and inspire an audience of philosophers of technology, ethicists, engineers, developers, manufacturers, and regulators, among other interested readers. (shrink)

This chapter contains sections titled: The Cutting Edge Automated Reasoning, Principles and Elements Significant Successes Myths, Mechanization, and Mystique.

Automation, artificial intelligence, and biotechnology have become topics of increasing interest in both academia as well as in popular media. The goal of this article is to establish which issues are the most pressing, and what are the underlying causes of the rise of robots. I demonstrate that fears of automation are well supported by current trends of automation as well as the inherent tendency within a capitalist system to automate at the expense of workers and working (...) wages. Additionally, I point to what appears to be a potential evolutionary divide between what Yuval Noah Harari calls the “god” class and the “useless” class. Finally, I discuss how the new role of information as the world’s most valued commodity can either exacerbate this coming divide or liberate society. I present the case that in order to diminish the negative effects we must move beyond the present capitalist economic system, towards one in which economic democracy and the free flow of information thrives. (shrink)

Algorithmic decision making is used in an increasing number of fields. Letting automated processes take decisions raises the question of their accountability. In the field of computational journalism, the algorithmic accountability framework proposed by Diakopoulos formalizes this challenge by considering algorithms as objects of human creation, with the goal of revealing the intent embedded into their implementation. A consequence of this definition is that ensuring accountability essentially boils down to a transparency question: given the appropriate reverse-engineering tools, it should be (...) feasible to extract design criteria and to identify intentional biases. General limitations of this transparency ideal have been discussed by Ananny and Crawford :973–989, 2018). We further focus on its technical limitations. We show that even if reverse-engineering concludes that the criteria embedded into an algorithm correspond to its publicized intent, it may be that adversarial behaviors make the algorithm deviate from its expected operation. We illustrate this issue with an automated news recommendation system, and show how the classification algorithms used in such systems can be fooled with hard-to-notice modifications of the articles to classify. We therefore suggest that robustness against adversarial behaviors should be taken into account in the definition of algorithmic accountability, to better capture the risks inherent to algorithmic decision making. We finally discuss the various challenges that this new technical limitation raises for journalism practice. (shrink)

How should policymakers respond to the risk of technological unemployment that automation brings? First, I develop a procedure for answering this question that consults, rather than usurps, individuals’ own attitudes and ambitions towards that risk. I call this the insurance argument. A distinctive virtue of this view is that it dispenses with the need to appeal to a class of controversial reasons about the value of employment, and so is consistent with the demands of liberal political morality. Second, I (...) appeal to the insurance argument to show that governments ought not simply to provide those who are displaced by machines with unemployment benefits. Instead, it must offer re-training programmes, as well as enact more general macroeconomic policies that create new opportunities for employment. My contribution is important not only because it helps us to resolve a series of urgent policy disputes—disputes that have been discussed extensively by labour market economists and policymakers, but less so by political philosophers—but also because my analysis sheds light on more general philosophical controversies relating to risk. (shrink)

A great deal of theorizing has emerged about the economic ramifications of increased automation. However, significantly less attention has been paid to the potential effects of AI-driven occupational replacement on less measurable metrics—in particular, what it feels like to be replaced. In politics, we see examples of nation-states and extremist groups invoking the concept of replacement as a motivator for political action, unrest, and, at times, violence. In the realm of workplace automation, and in particular, in the case (...) of AI-driven workplace automation, the replacement of human labor with artificial labor is an explicit goal. In this paper, we suggest that, given the effects that the experience of a sense of replacement has in political contexts and the potential for that sense of replacement to motivate unrest and violence, we should be concerned about the widely predicted replacement of workers over the coming decades beyond the potential economic challenges which may arise. (shrink)

The automated parsing of 130,213 news articles about the 2012 US presidential elections produces a network formed by the key political actors and issues, which were linked by relations of support and opposition. The nodes are formed by noun phrases and links by verbs, directly expressing the action of one node upon the other. This network is studied by applying insights from several theories and techniques, and by combining existing tools in an innovative way, including: graph partitioning, centrality, assortativity, hierarchy (...) and structural balance. The analysis yields various patterns. First, we observe that the fundamental split between the Republican and Democrat camps can be easily detected by network partitioning, which provides a strong validation check of the approach adopted, as well as a sound way to assign actors and topics to one of the two camps. Second, we identify the most central nodes of the political camps. We also learnt that Clinton played a more central role than Biden in the Democrat camp; the overall campaign was much focused on economy and rights; the Republican Party is the most divisive subject in the campaign, and is portrayed more negatively than the Democrats; and, overall, the media reported positive statements more frequently for the Democrats than the Republicans. This is the first study in which political positions are automatically extracted and derived from a very large corpus of online news, generating a network that goes well beyond traditional word-association networks by means of richer linguistic analysis of texts. (shrink)

This article discusses Fin de Copenhague, a Situationist book experiment from 1957 by Asger Jorn and Guy Debord. By way of a contextualizing archival study with special attention to Jorn’s contemporaneous book project Pour la forme, the article demonstrates that the Russian avant-garde book was a key influence if also a point of critical departure. On this reading, Fin de Copenhague marks a turn away from the unbridled technological optimism of the historical avant-garde. In its material implications and aesthetic choices, (...) Fin de Copenhague draws attention to crucial changes in the capitalist mode of production and challenges the then nascent discourse about “full automation.”. (shrink)

The use of advanced AI and data-driven automation in the public sector poses several organisational, practical, and ethical challenges. One that is easy to underestimate is automation bias, which, in turn, has underappreciated legal consequences. Automation bias is an attitude in which the operator of an autonomous system will defer to its outputs to the point where the operator overlooks or ignores evidence that the system is failing. The legal problem arises when statutory office-holders (or their employees) (...) either fetter their discretion to in-house algorithms or improperly delegate their discretion to third-party software developers—something automation bias may facilitate. A synthesis of previous research suggests an easy way to mitigate the risks of automation bias and its potential legal ramifications is for those responsible for procurement decisions to adhere to a simple checklist that ensures that the pitfalls of automation are avoided as much as possible. (shrink)

Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based on Prolog, and in (...) bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model vague concepts following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) a representative use case, the criteria for the admission of students in the “Comunidad de Madrid”. (shrink)

Reflectance spectroscopy is a standard tool for studying the mineral composition of rock and soil samples and for remote sensing of terrestrial and extraterrestrial surfaces. We describe research on automated methods of mineral identification from reflectance spectra and give evidence that a simple algorithm, adapted from a well-known search procedure for Bayes nets, identifies the most frequently occurring classes of carbonates with reliability equal to or greater than that of human experts. We compare the reliability of the procedure to the (...) reliability of several other automated methods adapted to the same purpose. Evidence is given that the procedure can be applied to some other mineral classes as well. Since the procedure is fast with low memory requirements, it is suitable for on- board scientific analysis by orbiters or surface rovers. (shrink)

This article contributes to the debate on automation and justice by discussing two under-represented concerns: labour justice and equality. Since automation involves both winners and losers, and given that there is no ‘end of work’ on the horizon, it is argued that most normative views on the subject – i.e. the ‘allocative’ view of basic income, and the ‘desirability’ views of post-work and workist ethics – do not provide many resources with which to address unjustly unequal divisions of (...) labour involved in technological innovation. This article problematises these common responses reframing the problem from the perspective of labour justice. While the allocative view assumes that labour justice follows ‘spontaneously’ from income redistribution, the desirability views are chiefly interested in either defining or contesting the meanings of work for individuals, overlooking the interdependent nature of work and concerns of equality other than autonomy. Two conceptions of labour justice are thus applied to the problem: Paul Gomberg’s contributive justice, and Iris Young’s democratic division of labour. Instead of deciding between them, the normative core of ‘contributive parity’ is suggested as a critical standard for assessing unequal labour structures, and for envisaging a future in which technology can be an ally in making social cooperation fair. (shrink)

The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation. We have confirmed Adam's conclusions through manual experiments. To describe Adam's research, we have developed an ontology and logical language. The resulting formalization involves over (...) 10,000 different research units in a nested treelike structure, 10 levels deep, that relates the 6.6 million biomass measurements to their logical description. This formalization describes how a machine contributed to scientific knowledge. (shrink)

The intention of this paper is to point to the dilemma humanity may face in light of AI advancements. The dilemma is whether to create a world with less evil or maintain the human status of moral agents. This dilemma may arise as a consequence of using automated decision-making systems for high-stakes decisions. The use of automated decision-making bears the risk of eliminating human moral agency and autonomy and reducing humans to mere moral patients. On the other hand, it also (...) has the potential to bring tremendous benefits to humanity by decreasing human-induced harm in the world. After presenting how this dilemma may arise, I explore general avenues for addressing it. I will argue that we do not have to solve this dilemma in an all-or-nothing fashion and that a more nuanced approach may be suitable. However, the main point I want to highlight is that we need to have a principled way of addressing this dilemma, which is currently missing. (shrink)

POLITICS is a system of computer programs which simulates humans in comprehending and responding to world events from a given political or ideological perspective. The primary theoretical motivations were: (1) the implemention of a functional system which applies the knowledge structures of Schank and Abelson (1977) to the domain of simulating political belief systems; (2) the development of a tentative theory of intentional goal conflicts and counterplanning. Secondary goals of the POLITICS project include developing a representation for belief systems, investigating (...) cognitive processes such as goal‐directed inferencing, and the integration of several types of knowledge representations into a functional system. (shrink)

This chapter examines the role of shopfloor knowledge in the operation of advanced manufacturing systems. Design trends towards full automation are contrasted with those toward hybrid, human-centred systems with particular emphasis on job design and the development and reproduction of knowledge. The chapter concludes with a short discussion of the problems inherent in hybrid design.

Automated decision making for sentencing is the use of a software algorithm to analyse a convicted offender’s case and deliver a sentence. This chapter reviews the moral arguments for and against employing automated decision making for sentencing and finds that its use is in principle morally permissible. Specifically, it argues that well-designed automated decision making for sentencing will better approximate the just sentence than human sentencers. Moreover, it dismisses common concerns about transparency, privacy and bias as unpersuasive or inapplicable. The (...) chapter also notes that moral disagreement about theories of just sentencing are plausibly resolved by applying the principle of maximising expected moral choiceworthiness, and that automated decision making is better suited to the resulting ensemble model. Finally, the chapter considers the challenge posed by penal populism. The dispiriting conclusion is that although it is in theory morally desirable to use automated decision-making for criminal sentencing, it may well be the case that we ought not to try. (shrink)

Are automated vehicles really safer than manually driven vehicles? If so, how would we know? Answering this question has spurred a contentious debate. Unfortunately, several issues make answering this question difficult for the foreseeable future. First, how do we measure safety? Second, how can we keep track of automated vehicle safety? Finally, how do we determine what is or what is not an AV? Until these questions are addressed, it will continue to be difficult to determine whether or when AVs (...) might really be safer than manually driven vehicles. (shrink)

Automated classification of legal documents has been the subject of extensive research in recent years. However, this is still a challenging task for long documents, since it is difficult for a model to identify the most relevant information for classification. In this paper, we propose a two-stage supervised learning approach for the classification of petitions, a type of legal document that requests a court order. The proposed approach is based on a word-level encoder–decoder Seq2Seq deep neural network, such as a (...) Bidirectional Long Short-Term Memory (BiLSTM) or a Bidirectional Encoder Representations from Transformers (BERT) model, and a document-level Support Vector Machine classifier. To address the challenges posed by the lengthy legal documents, the approach introduces a human-in-the-loop approach, whose task is to localize and tag relevant segments of text in the word-level training part, which dramatically reduces the dimension of the document classifier input vector. We performed experiments to validate our approach using a real-world dataset comprised of 270 intermediate petitions, which were carefully annotated by specialists from the 15th civil unit of the State of Alagoas, Brazil. Our results revealed that both BiLSTM and BERT-Convolutional Neural Networks variants achieved an accuracy of up to 95.49%, and also outperformed baseline classifiers based on the Term Frequency–Inverse Document Frequency test vectorizer. The proposed approach is currently being utilized to automate the aforementioned justice unit, thereby increasing its efficiency in handling repetitive tasks. (shrink)

In order to think of philosophy after automation, we have to ask if there is more in philosophy than the process of learning what philosophy is by inducing, from actual inferential practices, the future possible moves that are believed to produce philosophical truths. In the same way as the production of scientific hypothesis has been automated like a self-updating process which entails schemas of decisions and actions, philosophy itself, once conceived as a game where the truth of the statements (...) is measured with respect to the social reproduction of inferential moves, could be automated as well. (shrink)

In this paper we focus on how automated vehicles can reduce the number of deaths and injuries in accident situations in order to protect public health. This is actually a problem not only of public health and ethics, but also of big data—not only in terms of all the different data that could be used to inform such decisions, but also in the sense of deciding how wide the scope of data should be. We identify three key different types of (...) data, including basic data, advanced data and preference data, provide an ethical analysis of the use of these different types of data and of different ways of prioritizing between pedestrians and passengers, and propose four rules that can help set ethical priorities for ethical data use and decision making by automated vehicles. (shrink)

This paper described a formal theory of type judgments for propositional logic notations of PM; I felt the need of my own automated type checker to check their examples. The type checker I wrote did indeed serve to help me referee the paper, but also took a rather different approach to notation and typing for propositional functions of PM, which proved worth writing up independently in our own paper: Holmes, M. Randall, “Polymorphic type– checking for the ramified theory of types (...) of Principia Mathematica”, in Fairouz Kamareddine, ed., Thirty–five Years of Automating Mathematics, Kluwer, 2003, pp. 173-215. (shrink)

Reflectance spectroscopy is a standard tool for studying the mineral composition of rock and soil samples and for remote sensing of terrestrial and extraterrestrial surfaces. We describe research on automated methods of mineral identification from reflectance spectra and give evidence that a simple algorithm, adapted from a well-known search procedure for Bayes nets, identifies the most frequently occurring classes of carbonates with reliability equal to or greater than that of human experts. We compare the reliability of the procedure to the (...) reliability of several other automated methods adapted to the same purpose. Evidence is given that the procedure can be applied to some other mineral classes as well. Since the procedure is fast with low memory requirements, it is suitable for on-board scientific analysis by orbiters or surface rovers. (shrink)

Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate what (...) it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)