This introduction to a special section on algorithmic thought provides a framework through which the articles in that collection can be contextualised and their individual contributions highlighted. Over the past decade, there has been a growing interest in artificial intelligence (AI). This special section reflects on this AI boom and its implications for studying what thinking is. Focusing on the algorithmic character of computing machines and the thinking that these machines might express, each of the special section’s (...) essays considers different dimensions of algorithmic thought, engaging with a diverse set of epistemological questions and issues. (shrink)

The rhetoric of algorithmic neutrality is more alive than ever-why? This volume explores key moments in the historical emergence of algorithmic practices and in the constitution of their credibility and authority since 1500. If algorithms are historical objects and their associated meanings and values are situated and contingent-and if we are to push back against rhetorical claims of otherwise-then the genealogical investigation this book offers is essential to understand the power of the algorithm. The fact that algorithms create (...) the conditions for many of our encounters with social reality contrasts starkly with their relative invisibility. More than other artifacts, algorithms are easily black-boxed. Rather than contingent and modifiable, they are widely seen as obvious and unproblematic-without context and without history. As an antidote, this volume keeps a clear focus on the emergence and continuous reconstitution of algorithmic practices alongside the ascendance of modernity. Its essays highlight the trajectory of an algorithmic modernity, one characterized by attitudes and practices that are best emblematized by the modernist aesthetic and inhuman efficacy of the algorithm. The volume moves from early modern algorithmic practices, centered on heuristics for arithmetic operations, emphasizing ruptures, shifts, and variations across times and cultures. By the age of Enlightenment, the term algorithm had come to signify any process of systematic calculation that could be carried out mechanically, but its meaning and implications are still distant from those familiar to us. It's in the nineteenth and twentieth century that the meaning of algorithm is sharpened through a new discipline and by adding sets of specific conditions-such as the condition of finiteness-which acquire new and crucial significance in the age of digital computing. Throughout, the connection between algorithms and modernity is one of our central concerns. Through detailed historical reconstructions of specific moments, thinkers, and cultural phenomena over the last five hundred years, these essays lead us to the definitions of algorithm most legible today and to the pervasiveness of both algorithmic procedures and rhetoric. This volume contributes a multi-faceted exploration of the genealogies of algorithms, of algorithmic thinking, and of the distinctly modernist faith in algorithms as neutral tools that merely illuminate the natural and social world. (shrink)

This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

In the technical literature of computer science, the concept of an effective procedure is closely associated with the notion of an instruction that precisely specifies an action. Turing machine instructions are held up as providing paragons of instructions that "precisely describe" or "well define" the actions they prescribe. Numerical algorithms and computer programs are judged effective just insofar as they are thought to be translatable into Turing machine programs. Nontechnical procedures (e.g., recipes, methods) are summarily dismissed as ineffective on (...) the grounds that their instructions lack the requisite precision. But despite the pivotal role played by the notion of a precisely specified instruction in classifying procedures as effective and ineffective, little attention has been paid to the manner in which instructions "precisely specify" the actions they prescribe. It is the purpose of this paper to remedy this defect. The results are startling. The reputed exemplary precision of Turing machine instructions turns out to be a myth. Indeed, the most precise specifications of action are provided not by the procedures of theoretical computer science and mathematics (algorithms) but rather by the nontechnical procedures of everyday life. I close with a discussion of some of the rumifications of these conclusions for understanding and designing concrete computers and their programming languages. (shrink)

In this paper, we will analyze the relationships among three important philosophical theses in Kuhn’s thought: the plurality of worlds thesis, the no universal algorithm thesis, and the niche-construction analogy. We will do that by resorting to a hitherto neglected notion employed by Kuhn: the idea of a feedback loop. We will show that this notion captures an important structural aspect of the epistemic dynamics at work in each of the three theses, therefore allowing us to read them as (...) constituting a virtuous epistemic cycle. Finally, we will apply our unified interpretation of the three theses to scientific practice to sketch a novel neo-Kuhnian picture of theory choice. (shrink)

The ArgumentDagognet's work shows that making algorithmic compressions seems to be one of the major targets of scientific progress. This effort has been so successful that until recently one might have thought everything could be algorithmically compressed. Indeed, this statement, which might be seen as a scientific translation of the Hegelian thesis in its strong form, admits to some objective limits in computer science. Though a lot of algorithms are successful, there exist today, and perhaps forever, logical and (...) physical limits that cannot allow us to cherish the dream of a “theory of everything.” Moreover, a complete mastery of complexity does not seem possible — because some domains of reality are too complicated to be computable, because the human brain is too limited, because computers cannot do that much better than the human brain, and because, ultimately, there are some kinds of things it would make no sense to compress. This paper shows that Dagognet's work came to recognize what a glance at the history of algorithmics has made evident. (shrink)

The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily (...) require the execution of mental algorithms, which appears to be at best no more than one rather special kind of thinking. (shrink)

This paper contributes to inquiries into the genealogy of governmentality and the nature of secularization by arguing that pastoralism continues to operate in the algorithmic register. Drawing on Agamben’s notion of signature, I elucidate a pair of historically distant yet archaeologically proximate affinities: the first between the pastorate and algorithmic control, and the second between the absconded God of late medieval nominalism and the authority of algorithms in the cybernetic age. I support my hypothesis by attending to the (...) signaturial kinships between, on the one hand, temporality and authority in our contemporary conjuncture, and, on the other, obedience and submission in Christian thought from late antiquity and the late Middle Ages. I thereby illustrate the hidden genealogical continuities between theological-pastoral technologies of power and technocratic-algorithmic modalities of governance. I conclude by suggesting that medieval counter-conducts may be redeployed in our present circumstances for emancipatory ends. (shrink)

The algorithm has become an increasingly important concept in understanding human behavior in recent years. In the case of sport, human bodies are seen as superficial to the driving force of the algorithm, whether it be genetic, behavioral or surveillance-technological algorithms (Harari Citation2015, 2020; Zuboff Citation2019). However, the French mathematician and philosopher Michel Serres (1930–2019) structurally relate algorithms to sports and bodily experience at multiple places in his oeuvre. According to Serres, sport actually enables us to reprogram and rewrite our (...) behavior, moods and thoughts, and therefore modifies our algorithmic status (Serres Citation1999, Citation2019). Against deterministic conceptions of the body, Serres argues that human bodies possess a ‘metamorphic’ nature that is similar to the procedural character of computer programs. This paper investigates the relationship between the algorithm and bodily existence through a reading of both Harari and Serres on sport. It will be argued that, against deterministic conceptions of the algorithm, the algorithm can actually broaden an understanding of the role of sports and physical activity. (shrink)

Against a remarkable hardware oblivion in discussions of algorithmic intelligence, this article insists that algorithmic thought, or abstract computation, cannot be separated from its technological implementation. It requires a material medium for an abstract mechanism to become a procedural event. Temporality is both the condition and the limiting (and irritating) factor in the computational function. ‘Radical’ media archaeology is proposed as a method for such an analysis, and the neologism of techno lógos to describe some aspects of (...) algorithmic reason which only unfold in the moment of its techno-processual coming-into-being. Some core operations, such as the time-discrete rhythm of actual computing algorithms, are discussed, where the ‘tempoReal’ flashes up in computing. In a wider sense, the time-discreteness of digital computing is related to an aesthetics of existence which acknowledges the machine element within human reasoning itself, while at the same time re-actualizing previous cultural techniques of non-narrative chronology. Turing the ‘man’ himself, in the sense of the Turing machine, can be addressed ‘itself’, in its archival sense as a sequence of expressions by symbols. (shrink)

The rapidly increasing role of automation throughout the economy, culture and our personal lives has generated a large literature on the risks of algorithmic decision-making, particularly in high-stakes legal settings. Algorithmic tools are charged with bias, shrouded in secrecy, and frequently difficult to interpret. However, these criticisms have tended to focus on particular implementations, specific predictive techniques, and the idiosyncrasies of the American legal-regulatory regime. They do not address the more fundamental unease about the prospect that we might (...) one day replace judges with algorithms, no matter how fair, transparent, and intelligible they become. The aim of this paper is to propose an account of the source of that unease, and to evaluate its plausibility. I trace foundational unease with algorithmic decision-making in the law to the powerful intuition that there is a basic moral and legal difference between showing that something is true of many people just like you and showing that it is true of you. Human judgment attends to the exception; automation insists on blindly applying the rule. I show how this intuitive thought is connected to both epistemological arguments about the value of statistical evidence, as well as to court-centered conceptions of the rule of law. Unease with algorithmic decision-making in the law thus draws on an intuitive principle that underpins a disparate range of views in legal philosophy. This suggests the principle is deeply ingrained. Nonetheless, I argue that the powerful intuition is not as decisive as it may seem, and indeed runs into significant epistemological and normative challenges. At an epistemological level, I show how concerns about statistical evidence's ability to track the truth can be resolved by adopting a probabilistic, rather than modal, conception of truth-tracking. At a normative level, commitment to highly individualized decision-making co-exists with equally ingrained and competing principles, such as consistent application of law. This suggests that the “rule of law” may not identify a discrete set of institutional arrangements, as proponents of a court-centric conception would have it, but rather a more loosely defined set of values that could potentially be operationalized in multiple ways, including through some level of algorithmic adjudication. Although the prospect of replacing judges with algorithms is indeed unsettling, it does not necessarily entail unreasonable verdicts or an attack on the rule of law. (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that (...) thinking about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

Both thought experiments and simulation experiments apparently belong to the family of experiments, though they are somewhat special members because they work without intervention into the natural world. Instead they explore hypothetical worlds. For this reason many have wondered whether referring to them as “experiments” is justified at all. While most authors are concerned with only one type of “imagined” experiment – either simulation or thought experiment – the present chapter hopes to gain new insight by considering what (...) the two types of experiment share, and what they do not. A close look reveals at least one fundamental methodological difference between thought and simulation experiments: while thought experiments are a cognitive process that employs intuition, simulation experiments rest on automated iterations of formal algorithms. It will be argued that this difference has important epistemological ramifications. (shrink)

Recommender system depends on the thoughts of numerous users to predict the favourites of potential consumers. RS is vulnerable to malicious information. Unsuitable products can be offered to the user by injecting a few unscrupulous “shilling” profiles like push and nuke attacks into the RS. Injection of these attacks results in the wrong recommendation for a product. The aim of this research is to develop a framework that can be widely utilized to make excellent recommendations for sales growth. This study (...) uses the methodology that presents an enhanced clustering algorithm named as modified density peak clustering algorithm on the consumer review dataset to ensure a well-formed cluster. An improved recurrent neural network algorithm is proposed to detect these attacks in hybrid RS, which uses the content-based RS and collaborative filtering RS. The results are compared with other state of the art algorithms. The proposed method is more suitable for E-commerce applications where the number of customers and products grows rapidly. (shrink)

Mental health apps bring unprecedented benefits and risks to individual and public health. A thorough evaluation of these apps involves considering two aspects that are often neglected: the algorithms they deploy and the functions they perform. We focus on mental health apps based on black box algorithms, explore their forms of opacity, discuss the implications derived from their opacity, and propose how to use their outcomes in mental healthcare, self‐care practices, and research. We argue that there is a relevant distinction (...) between functions performed by algorithms in mental health apps, and we focus on the functions of analysis and generation of advice. When performing analytic functions, such as identifying patterns and making predictions concerning people's emotions, thoughts, and behaviors, black box algorithms can be better than other algorithms to provide information to identify early signs of relapse, support diagnostic processes, and improve research by generating outcomes that lead to a better understanding of mental health. However, when carrying out the function of providing mental health advice, black box algorithms have the potential to deliver unforeseen advice that may harm users. We argue that the outcomes of these apps may be trustworthy as a complementary source of information, but express caution about black box algorithms that give advice directly to users. To reap the benefits of mental health apps based on black box algorithms and avoid unintended consequences, we critically need to know whether these algorithms are fulfilling the function of providing mental health advice. (shrink)

In a recent book, Secular Translations: Nation State, Modern State and Calculative Reason, Talal Asad is concerned with how the language of calculation and abstraction, inaugurated by modernity and accelerated by our current algorithmic reality, erodes the language of cultivated embodiment typical of religious worldviews and the virtues that such embodiment seeks to develop. These languages are predicated upon and cultivate different types of selves that are fundamentally at variance with each other. It is not that that one cannot (...) cultivate the worshipful, virtuous self in our algorithmic reality, but Asad’s pessimistic conclusion is that the conditions for such cultivation are being made increasingly difficult as we seemingly hasten towards a posthuman future. Asad here echoes thinkers such as Leon Kass and Michael Sandel who have also expressed disquiet about the loss of cultivated embodiment in such a future, but in an important meta sense, he goes beyond them by interrogating the underlying language we use to frame our discussions in this area. The purpose of this article is to bring an awareness to this Asadian argument, which, I believe, should at the very least give us some pause for thought as technology plunges us into new and unknowing horizons.Contribution: Despite the many laudable accomplishments of modernity in the techno-scientific sphere, vital questions remain about its ability to bring about overall human flourishing. Among others, the thought of Talal Asad provides a way to think about why the promised potential of modernity in this regard has not been realised and, concomitantly, why traditional, embodied teachings of religion continue to be critical in thinking about the future. (shrink)

According to Ernst Cassirer, the transition from the concept of substance to that of mathematical function as a guide of knowledge coincided with the end of ancient and the beginning of modern theoretical thought. In the first part of this article we argue that a similar transition has also taken place in the practical sphere, where mathematical function occurs in one of its specific forms, which is that of the algorithm concept. In the second part we argue that with (...) the rise of modernity the idea of substance and the related concepts of category and classification, which are deeply embedded in western culture, have not been totally supplanted by that of function. The intertwining of the concepts of substance and function has generated contradictory hybrids. These hybrids are used as a key for the understanding of the different repercussions of algorithmic logic on society in terms of social integration. (shrink)

John Searle dismisses the attempt to understand thought as a form of computation, on the grounds that it is not scientific. Science is concerned with intrinsic properties, i.e. those features which are not observer relative, e.g. science is concerned with mass but not with beauty. Computation, according to Searle, presupposes the property of following an algorithm, but algorithmicity is normative, by reason of appealing to function, and hence not intrinsic. I argue that Searle's critique presupposes the folk notion of (...) function, which is indeed normative. But this folk notion can be replaced by a purely descriptive analogue, thereby showing that algorithmicity can be construed as intrinsic after all. (shrink)

A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one-shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out (...) that the success of the IA depends substantially on the ‘‘preference order’’ (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. (shrink)

Social media has revolutionized the way information is distributed throughout society, as folks continue to rely entirely on these apps for information on current events, health protocols, and socio-political discussions. However, these containers of knowledge do not appear in the same shape for every user; Algorithms, informed by capitalist agendas, determine what information sifts through its networks and to whom. Data scientists, researchers, and activists have dissected the hidden mechanics fueling these popular platforms, inciting critical conversations around the harmful biases (...) embedded in algorithms. These studies often skim the surface of how these algorithms digitally marginalize people of color, if acknowledging it at all. Even fewer have attempted to examine the role these algorithms play in the social activism and digital community organizing happening amongst communities of color via social media. Referring to indigenous scholar Marisa Elena Duarte’s book Network Sovereignty as a framework of thought, this paper roots itself in the notion that technology is an extension of the agenda utilizing it. Through dissecting the algorithmic structures of popular social platforms among communities of color, this paper examines how social media distributes information within its networks and how its encoded biases silence Black, brown, and indigenous voices. This paper also provides insight into how BIPOC content-creators, when informed on how the algorithms work, can use these platforms to their advantage and effectively facilitate socio-political discourse online; Changing the narrative of social networks from being yet another landscape of white supremacy to instead a communal canvas for radical change. (shrink)

Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational (...) model of storage in, and activation of, a human semantic network, or semantic memory, whose core element is logical form; this is normalized by description logic (DL), namely by CL, a DL-based language – Conception Language – designed to formalize conceptualization from the viewpoint of individual cognitive agency. In this model, disruptions in the rule-based implementation of the logical form account for the apparently semantic anomalies symptomatic of FTD, which are detected by means of a CL-based algorithmic assessment. (shrink)

In "The Status and Future of the Turing Test" (Moor, 2001), which appeared in an earlier issue of this journal, James Moor remarks on my paper "Turing's Two Tests for Intelligence." In my paper I had claimed that, whatever Turing may or may not have thought, the test described in the opening section of Turing's now legendary 1950 paper "Computing Machinery and Intelligence" is not equivalent to, and in fact is superior to, the test described in a passage that (...) occurs much later in Turing's paper (i.e., in Section 5 of Turing, 1950). I'm pleased Moor chose to give such prominence to my point, and very happy to see that he recognized that my claim was a normative one about the superiority of one test over another, rather than a claim about Turing's intentions. However, as I think the way he describes my point could lead to misunderstandings, I'd like to clarify the points I made. One major clari?cation is which two tests I am contrasting; another is that the difference in overall structure of the two tests is of philosophical signi?cance. (shrink)

Maps and territory suggest problems which have to do with the opening of pathways in some poorly explored domain.

Modern society makes extensive use of automated algorithmic decisions, fueled by advances in artificial intelligence. However, since these systems are not perfect, questions about fairness are increasingly investigated in the literature. In particular, many authors take a Rawlsian approach to algorithmic fairness. This article aims to identify some complications with this approach: Under which circumstances can Rawls’s original position reasonably be applied to algorithmic fairness decisions? First, it is argued that there are important differences between Rawls’s original (...) position and a parallel algorithmic fairness original position with respect to risk attitudes. Second, it is argued that the application of Rawls’s original position to algorithmic fairness faces a boundary problem in defining relevant stakeholders. Third, it is observed that the definition of the least advantaged, necessary for applying the difference principle, requires some attention in the context of algorithmic fairness. Finally, it is argued that appropriate deliberation in algorithmic fairness contexts often require more knowledge about probabilities than the Rawlsian original position allows. Provided that these complications are duly considered, the thought-experiment of the Rawlsian original position can be useful in algorithmic fairness decisions. (shrink)

This paper begins with the thought that there is something out of place about offloading inquiry into one's own mind to AI. The paper's primary goal is to articulate the unease felt when considering cases of doing so. It draws a parallel between the use of algorithms in the criminal law: in both cases one feels entitled to be treated as an exception to a verdict made on the basis of a certain kind of evidence. Then it identifies an (...) account of first‐person authority that can make good on this: agentialism. Thus, the paper constitutes an argument in favor of an agentialist treatment of self‐knowledge and first‐person authority. (shrink)

The computational approach to psychiatric disorders, including delusions, promises explanation and treatment. Here, we argue that an information processing approach might be misleading to understand psychopathology and requires further refinement. We explore the claim of computational psychiatry being a bridge between phenomenology and physiology while focussing on the ontological commitments and corresponding methodology computational psychiatry is based on. Interconnecting ontological claims and methodological practices, the paper illustrates the structure of theory-building and testing in computational psychiatry.First, we will explain the ontological (...) commitments computational psychiatry is grounded in, theBayesian Brain hypothesis(BBH) of unconscious inference, paired with normative deontic approaches applied to gauge psychopathology. We then turn to the steps taken in empirical paradigms, from definitions, which are used as starting points, to the operationalisation and isolation of cognitive processes and hypothesis testing based on algorithmic models, to consecutive interpretations regarding the aetiology of psychiatric disorders. We outline how experimental paradigms in computational psychiatry are specifically designed to confirm aberrations in assumed inferential processes, which are thought of as being the underlyingcore invariant features.We will illustrate a gap between the ontological commitments of computational psychiatry and the operationalisation and testing of the cognition assumed to be relevant for psychopathology. This conceptual gap is of utmost importance when designing computational paradigms and may impede a crisp understanding of the approach. Lastly, in evaluating the conceptual gap, it becomes apparent that the information processing formalism used in computational psychiatry is still grounded in rational cognitive psychology. (shrink)

This study aims to develop a hybrid model to represent the human mind from a functionalist point of view that can be adapted to artificial intelligence. The model is not a realistic theory of the neural network of the brain but an instrumentalist AI model, which means that there can be some other representative models too. It had been thought that the provability of an axiomatic system requires the completeness of a formal system. However, Gödel proved that no consistent (...) formal system can prove its own consistency. There is a paradoxical limit to provability. Both consistency and completeness are impossible together. These formal limits form the basis of our model: the hybrid model of the mind consists of a formal axiomatic system and an evolutionary algorithm (EA) of intelligence, which also includes the genetic algorithm (GA) of consciousness. The GA of consciousness operates based on intentions, functioning in conjunction with the principles of EA. This collaboration allows it to transcend the paradoxical formal limits of intelligence. However, GA overcomes the problem of paradoxicality at the cost of producing illusions. Following this collaboration gives us a GA operating system. After all, if the rational optimization task of the GA in question produces illusions, then the rationality must lie elsewhere in the paradox. (shrink)

This article addresses computational procedures that are no longer constrained by human modes of representation and considers how these procedures could be philosophically understood in terms of ‘algorithmic thought’. Research in deep learning is its case study. This artificial intelligence (AI) technique operates in computational ways that are often opaque. Such a black-box character demands rethinking the abstractive operations of deep learning. The article does so by entering debates about explainability in AI and assessing how technoscience and technoculture (...) tackle the possibility to ‘re-present’ the algorithmic procedures of feature extraction and feature learning to the human mind. The article thus mobilises the notion of incommensurability (originally developed in the philosophy of science) to address explainability as a communicational and representational issue, which challenges phenomenological and existential modes of comparison between human and algorithmic ‘thinking’ operations. (shrink)

This commentary article outlines and explores the key problem that faces anyone interested in researching and understanding what might be thought of as a recursive society. It reflects on the problem that is posed by the layering of multiple feedback loops as a result of algorithmic sorting and data processes. This article is concerned with the difficulties of understanding the social where recursive algorithmic processes have repeatedly shaped outcomes, practices, relations and actions over time. This is not (...) just about the sinking of algorithms into the everyday, it is about the way that loop-upon-loop of data processes lead to the social world itself being recursive. This repeated looping is described here as a kind of data coiling. The article argues for a focus on recursivity and for an engagement with the conceptual problems and questions that this notion implies. (shrink)

A wide-ranging history of the intellectual developments that produced the modern idea of the algorithm. Bringing together the histories of mathematics, computer science, and linguistic thought, Language and the Rise of the Algorithm reveals how recent developments in artificial intelligence are reopening an issue that troubled mathematicians long before the computer age. How do you draw the line between computational rules and the complexities of making systems comprehensible to people? Here Jeffrey M. Binder offers a compelling tour of four (...) visions of universal computation that addressed this issue in very different ways: G. W. Leibniz's calculus ratiocinator; a universal algebra scheme Nicolas de Condorcet designed during the French Revolution; George Boole's nineteenth-century logic system; and the early programming language ALGOL, whose name is short for algorithmic language. These episodes show that symbolic computation has repeatedly become entangled in debates about the nature of communication. To what extent can meaning be controlled by individuals, like the values of a and b in algebra, and to what extent is meaning inevitably social? By attending to this long-neglected question, we come to see that the modern idea of the algorithm is implicated in a long history of attempts to maintain a disciplinary boundary separating technical knowledge from the languages people speak day to day. Machine learning, in its increasing dependence on words, now places this boundary in jeopardy, making its stakes all the more urgent to understand. The idea of the algorithm is a levee holding back the social complexity of language, and it is about to break. This book is about the flood that inspired its construction. (shrink)

Our private perception of listening to an individualized playlist during a jog is very different from the interaction we might experience at a live concert. We do realize that music is not necessarily a performing art, such as dancing or theater, while our demands regarding musical performances are conflicting: We expect perfect sound quality and the thrill of the immediate. We want the artist to overwhelm us with her virtuosity and we want her to struggle, just like a human. We (...) want to engage with the musical expression and rely on visual and physical cues. Considering that the ears of today's listeners are used to technologically mediated music, in this paper I explore the unique qualities of musical live performances and examine if our conception allows for new mechatronic inventions, in particular robotic musicians, to participate in this art form. Some of Godlovitch's main thoughts expounded in his work on "musical performance" [11] serve as a reference and starting point for this investigation. His concept of `personalism', which deprives computer-/program-based musical performances from expressive potential and creative accomplishment is an issue that I want to challenge by pointing out new approaches arising from a reective discourse on technology, embodiment and expression. The enquiry conducted illustrates, how in reasoning about machine performers and algorithmic realization of music, we also examine the perceptual, physical and social aspects of human musicianship, reconceptualizing our understanding of a musical live performance. (shrink)

John Locke offered what he considered a sound a priori argument that Mind must come first, must be the original Cause, not merely an Effect: If, then, there must be something eternal, let us see what sort of Being it must be. And to that it is very obvious to Reason, that it must necessarily be a cogitative Being. For it is as impossible to conceive that ever bare incogitative Matter should produce a thinking intelligent Being, as that nothing should (...) of itself produce Matter. Let us suppose any parcel of Matter eternal, great or small, we shall find it, in itself, able to produce nothing. . . . . Matter then, by its own strength, cannot produce in itself so much as Motion: the Motion it has, must also be from Eternity, or else be produced, and added to Matter by some other Being more powerful than Matter. . . . But let us suppose Motion eternal too: yet Matter, incogitative Matter and Motion, whatever changes it might produce of Figure and Bulk, could never produce Thought: Knowledge will still be as far beyond the power of Motion and Matter to produce, as Matter is beyond the power of nothing or nonentity to produce. And I appeal to everyone's own thoughts, whether he cannot as easily conceive Matter produced by nothing, as Thought produced by pure Matter, when before there was no such thing as Thought, or an intelligent Being existing. . . . So if we will suppose nothing first, or eternal: Matter can never begin to be: If we suppose bare Matter, without Motion, eternal: Motion can never being to be: If we suppose only Matter and Motion first, or eternal: Thought can never begin to be. For it is impossible to conceive that Matter either with or without Motion could have originally in and from itself Sense, Perception and Knowledge, as is evident from hence, that then Sense, Perception, and Knowledge must be a property eternally inseparable from Matter and every particle of it. (shrink)

Scholars in both digital humanities and media studies have noted an apparent disconnect between computation and the interpretive methods of the humanities. Alan Liu has argued that literary scholars employing digital methods encounter a “meaning problem” due to the difficulty of reconciling algorithmic methods with interpretive ones. Conversely, the media scholar Friedrich Kittler has questioned the adequacy of hermeneutics as a means of studying computers. This paper argues that that this disconnect results from a set of contingent decisions made (...) in both humanistic and mathematical disciplines in the first half of the nineteenth century that delineated, with implications that continue to resonate in the present day, which aspects of human activity would come to be formalized in algorithms and which would not. I begin with a discussion of Nicolas de Condorcet, who attempted, at the height of the 1789 revolution, to turn algebra into a universal language; his work, I argue, exemplifies the form of algorithmic thinking that existed before the Romantic turn. Next, I discuss William Wordsworth’s arguments about the relationship of poetry and science. While Wordsworth is sometimes viewed as a critic of science, I argue that his polemic is specifically targeted at highly politicized projects like Condorcet’s that sought to supplant existing modes of thought with scientific rationality. Finally, I demonstrate the importance of Romantic thought for George Boole, creator of the logic system that would eventually form the basis of digital electronics. The reason Boole was able to succeed where Condorcet had failed, I argue, was that Romantic notions of culture enabled him to reconcile a mechanical view of mathematical reasoning with an organic view of the development of meaning—a dichotomy that remains a key assumption of computer interfaces in the twenty-first century. (shrink)

In the same way as the quantum no-cloning theorem and quantum key distribution in two preceding papers, entanglement-assisted quantum teleportation and Grover’s search algorithm are generalized by transferring them to an abstract setting, including usual quantum mechanics as a special case. This again shows that a much more general and abstract access to these quantum mechanical features is possible than commonly thought. A non-classical extension of conditional probability and, particularly, a very special type of state-independent conditional probability are used (...) instead of Hilbert spaces and wavefunctions. (shrink)

How should driverless vehicles respond to situations of unavoidable personal harm? This paper takes up the case of self-driving cars as a prominent example of algorithmic moral decision-making, an emergent type of morality that is evolving at a high pace in a digitised business world. As its main contribution, it juxtaposes dilemma decision situations relating to ethical crash algorithms for autonomous cars to two edge cases: the case of manually driven cars facing real-life, mundane accidents, on the one hand, (...) and the dilemmatic situation in theoretically constructed trolley cases, on the other. The paper identifies analogies and disanalogies between the three cases with regard to decision makers, decision design, and decision outcomes. The findings are discussed from the angle of three perspectives: aspects where analogies could be found, those where the case of self-driving cars has turned out to lie in between both edge cases, and those where it entirely departs from either edge case. As a main result, the paper argues that manual driving as well as trolley cases are suitable points of reference for the issue of designing ethical crash algorithms only to a limited extent. Instead, a fundamental epistemic and conceptual divergence of dilemma decision situations in the context of self-driving cars and the used edge cases is substantiated. Finally, the areas of specific need for regulation on the road to introducing autonomous cars are pointed out and related thoughts are sketched through the lens of the humanistic paradigm. (shrink)

Writing is frequently analyzed as a mode of communication. But writing can be done for personal reasons, to remind oneself of things to do, of thoughts, of events. The cellphone has revealed this shift, commencing as a communication device and ending up as a memory prosthesis that records what we see, hear, read and think. The recordings are not necessarily for communicating a message to others, but sometimes just for oneself. Today, when machine learning algorithms read, write and transmit, a (...) new mode of communication arises that is not centered on the human. In this chapter the various phases of modern writing are modeled according to postphenomenology. As a branch of philosophy of technology, postphenomenology offers a set of analytical tools to study technologies and our relations to them. One of its central frameworks is the scheme of “I–technology–world.” The author proposes some modifications so that the scheme can systematically model the changes in the humans users, in machine learning algorithms imbued with non-human cognition and in the environments of readers, interlocutors and contexts. (shrink)

This article recapitulates and develops the attempts in the Nietzschean traditions to address and overcome the proliferation of nihilism that Nietzsche predicted to unfold in the next 200 years (WP 2). Nietzsche approached nihilism not merely as a psychology but as a labyrinthic and pervasive historical process whereby the highest values of culture and founding assumptions of philosophical thought prevented the further flourishing of life. Therefore, he thought nihilism had to be encountered and experienced on many, often opposing, (...) fronts to be fully consumed and left behind. Thus, just as Nietzsche captured the subtle reinventions of nihilism in new forms in his time, in the new doers assumed behind new deeds (WP 488), this article focuses on the contemporary tectonic shifts brought by digital technology and challenges subjectivation and narrativization of algorithmic will to power in human-like interfaces such as ChatGPT. Having identified philosophers and himself as the most advanced nihilists in their overvaluation of truth, in the 4th part of Thus Spoke Zarathustra, Nietzsche grappled with the difficult, perhaps impossible, temporality of post-nihilistic historicity that oscillates between highest creativity and highest truths, especially in the sections entitled The Shadow and At Noon whereby he explored new temporal techniques to evade the relapses into temporal nihilisms of the notions of linear progress or eternity (TSZ, 4). By drawing on this juncture, this article offers ways to address transfigurations of nihilism behind new technological performances of subjectivity. The article points toward creative temporalities beyond narrativity and subjectivity insofar as the statistical operations and probabilistic estimations of language-models exceed grammatical construction of meaning. This multifaceted application of his thought on the contemporary ontic reality is necessary to perceive our comet's incalculable movement as a veritable ray of sunshine. (shrink)

Michel Serres said that history is the propagation of effects, saying in his conversations with Bruno Latour, “we experience time as much in our inner senses as externally in nature, as much as le temps of history as le temps of weather,” characterized more by turbulence than by Euclidean geometry. Setting out from Serres’ nautical meditation on noise, guided by Giuseppe Longo’s and interlocutors’ characterization of the random as a function of theory and measure, one can distinguish the random from (...) the non-schematizable noisy. How do we think given the noisy dynamics of the world? Bernard Stiegler’s epiphylogenetic technologies and Gilbert Simondon’s transindividuating technics prepares considering thought as collective as well as individual activity. After sallies into algorithmic technology to establish its limits, we consider how epiphylogenetic thought develops in the presence of indeterminacy. We return to noise not as a simple veil between the discernible and indiscernible, but as a constitutive aspect of the complexification and enrichment of developmental ontologies, an enrichment co-articulated by epiphylogenetic imagination and technics. (shrink)

The article considers the problem of images and the role they play in our reflection turning to evidence provided by two seemingly very distant theories of mind together with two sorts of corresponding visions: dreams as analyzed by Freud who claimed that they are pictures of our thoughts, and their mechanical counterparts produced by neural networks designed for object recognition and classification. Freud’s theory of dreams has largely been ignored by philosophers interested in cognition, most of whom focused solely on (...) the linguistic incarnation of thoughts, but even though commonly neglected by respectable theories of thinking, dream images may prove to be the key to the black box of thought. As argued in this article, when seen from the right perspective and approached with the right set of questions, oneiric visions yield groundbreaking insights into the mechanism of how concepts and judgments are formed. Support for this conclusion comes from a tradition seemingly remote, if not opposed to psychoanalysis: the mechanical model of the mind conceived by information sciences and embodied in the form of artificial neural nets which mirror the activity of human visual cortex producing visions strikingly similar to those created by the sleeping mind. These purely mechanical, artificial ‘dreams’ constitute byproducts of algorithms designed for object recognition and classification, which, as I shall argue, reveals the true purpose of our own oneiric visual formations. Just like their mechanical counterparts produced by neural networks, condensations and displacements encountered in dreams are in fact visual universals. (shrink)

This book provides a comprehensive examination of the police role from within a broader philosophical context. Contending that the police are in the midst of an identity crisis that exacerbates unjustified law enforcement tactics, Luke William Hunt examines various major conceptions of the police—those seeing them as heroes, warriors, and guardians. The book looks at the police role considering the overarching societal goal of justice and seeks to present a synthetic theory that draws upon history, law, society, psychology, and philosophy. (...) Each major conception of the police role is examined in light of how it affects the pursuit of justice, and how it may be contrary to seeking justice holistically and collectively. The book sets forth a conception of the police role that is consistent with the basic values of a constitutional democracy in the liberal tradition. Hunt’s intent is that clarifying the police role will likewise elucidate any constraints upon policing strategies, including algorithmic strategies such as predictive policing. This book is essential reading for thoughtful policing and legal scholars as well as those interested in political philosophy, political theory, psychology, and related areas. Now more than ever, the nature of the police role is a philosophical topic that is relevant not just to police officials and social scientists, but to everyone. (shrink)

This is the first of two volumes of essays on the intellectual legacy of Alan Turing, whose pioneering work in artificial intelligence and computer science made him one of the seminal thinkers of the century. A distinguished international cast of contributors focus on the three famous ideas associated with his name: the Turing test, the Turing machine, and the Church-Turing thesis. 'a fascinating series of essays on computation by contributors in many fields' Choice.