It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare as an example, (...) attention to sociocultural conversion factors relevant to health can help in navigating technical choices that require broader considerations of the sociotechnical system, such as metric tradeoffs in model validation, resulting in better ethical and technical choices. This approach promotes awareness of the ethical dimension of technical choices by data scientists and others, and that can foster the cultivation of 'ethical skills' as integral to data science. (shrink)

In We Have Always Been Cyborgs (2021), Stefan L. Sorgner argues that, given the growing economic burden of desirable welfare programs, in order for Western democratic societies to continue to flourish it will be necessary that they establish some form of algocracy (i.e., governance by algorithm). This is argued to be necessary both in order to maintain the sustainability and efficiency of these programs, but also due to the fact that further integration of humans into technical systems provides the (...) only effective means to bridge gaps in functionality and governance. However, Sorgner’s position is entirely insensitive to the design turn in applied ethics, which argues against the neutrality of technology, instead maintaining that technology and society co-construct each other with persistent feedback loops. This, I argue, is a problem for his account inasmuch as technologies, as they become more ubiquitous, likewise become pervasive and inextricable from our sociotechnical infrastructures. As such, less-than-beneficent forces, as current trends illustrate, can appropriate these seemingly banal infrastructures to gear them towards oppressive ends, thereby ultimately threatening the social democracies that Sorgner’s position aims to buttress. (shrink)

The sociotechnical domain is the realm of scientists, the communities and institutions they form, and the tools and instruments they use to create, disseminate, and preserve knowledge. This paper reviews current scientonomic theory concerning this domain. A core scientonomic concept is that of an epistemic agent. Generally, an agent is an entity capable of intentional action—action that has content or meaning due to its purposeful direction towards a goal. An epistemic agent is one whose actions are the taking of (...) epistemic stances, such as acceptance or rejection, towards epistemic elements, like theories or questions. An epistemic agent must semantically understand the propositions in question, and their alternatives, and choose among them with reason, with the motive of acquiring knowledge. The most obvious example of an epistemic agent is an individual human being. Rejecting the network of practitioners view, current scientonomic theory argues that appropriately organized communities of scientists can also function as epistemic agents. Communal epistemic agents are of particular scientonomic importance. Whereas the methods of theory assessment of individual scientists can be idiosyncratic, scientonomic theory contends that the taking of epistemic stances by scientific communities is a lawful, rule governed process. A second concept of central importance is that of an epistemic tool. A physical object or system is an epistemic tool for some epistemic agent if there is a procedure by which the tool can provide an acceptable source of knowledge under the method employed by that agent. (shrink)

The purpose of cultural competence education for medical professionals is to ensure respectful care and reduce health disparities. Yet as Berger and Miller (2021) show, the cultural competence framework is dated, confused, and self-defeating. They argue that the framework ignores the primary driver of health disparities—systemic racism—and is apt to exacerbate rather than mitigate bias and ethnocentrism. They propose replacing cultural competence with a framework that attends to two social aspects of structural inequality: health and social policy, and institutional-system activity; (...) and two psychological aspects of structural inequality: the clinical encounter, and the epistemic. -/- We agree with the structural approach. To that end, we think it would be fruitful to include attention to physical contributors to structural inequality, namely the material artifacts used in medicine. Devices, tools, and technologies can materialize biases, perpetuate oppression, and contribute to health disparities. Granted, not everything that interests philosophers can be squeezed into medical education. Nevertheless, there are compelling reasons for including the study of material artifacts in education designed to reduce health disparities. First, devices and tools often carry forward biases from the past, and keep biases hidden from plain sight. Second, by studying these artifacts, future clinicians can begin to see themselves as part of a larger sociotechnical system. Finally, as medicine becomes increasingly tech-laden, it’s important for clinicians to see how material artifacts (including algorithms) connect individuals to structures. This will help to undermine oversimplified narratives according to which objective tools and technologies can correct for the bias and subjectivity of flawed human beings. (shrink)

The Systemic Continuum Paradigm (PCS) offers a unifying framework to understand how emergent properties—ranging from fundamental forces in physics to cognitive capacities in living systems—arise through systemic balances (BS) across multiple scales. While the Law of Structuring Systemic Emergence (LESSE) explains why one force can dominate its scale’s entire synergy in the physical domain (e.g., gravity at cosmic scales), the broader concept of Systemic Balance (BS) accounts for the emergence of non-monopolistic properties such as intelligence, consciousness, or social cooperation (...) in biological and sociotechnical contexts. This essay refines the notion of “extension of affectation” for forces that coincide with the General Systemic Balance (GSB) at a given scale, framing them as structural “monopolies,” while demonstrating that elsewhere, emergent properties operate through co-existence and catalysis rather than singular dominance. Finally, we explore how this paradigm eliminates the need for a single “Theory of Everything” in physics, while simultaneously explaining how intelligence in biological or AI systems can catalyze new configurations without invoking ex nihilo creation. We invite a transdisciplinary community—physicists, biologists, philosophers, AI researchers—to apply, critique, and expand the PCS toward a deeper understanding of cosmic, biological, and cognitive emergences. (shrink)

The paper explores how the framework of systemic risks can help govern the risks imposed through solar climate engineering research. The central argument is that a systemic perspective of risk is a useful tool for analysing and assessing the risks imposed through Stratospheric Aerosol Injection (SAI) research. SAI is a form of climate engineering that could cool the planet by enhancing its albedo through the injection of aerosols into the stratosphere. Researching such a technology creates systemic risks with a strong (...) sociotechnical component. This component consists of the potential societal harm that a developing or new technology might cause to existing norms, values, institutions, and politics. The systemic risk framework is a valuable heuristic for this case, given the complex interdependencies of societal systems, infrastructures, markets, etc. At the same time, the systemic risk framework can be enhanced through the inclusion of a more robust and reflected ethical considerations on technological risks. Consequently, this article seeks to supplement the systemic risk governance framework with insights from technology ethics. Specifically, the paper offers an ethically reflective conception of societal value dynamism and stakeholder engagement and participation, tying it to existing systemic risk governance approaches. (shrink)

Most engineers Fwork within social structures governing and governed by a set of values that primarily emphasise economic concerns. The majority of innovations derive from these loci. Given the effects of these innovations on various communities, it is imperative that the values they embody are aligned with those societies. Like other transformative technologies, artificial intelligence systems can be designed by a single organisation but be diffused globally, demonstrating impacts over time. This paper argues that in order to design for (...) this broad stakeholder group, engineers must adopt a systems thinking approach that allows them to understand the sociotechnicity of artificial intelligence systems across sociocultural domains. It claims that value sensitive design, and envisioning cards in particular, provides a solid first step towards helping designers harmonise human values, understood across spatiotemporal boundaries, with economic values, rather than the former coming at the opportunity cost of the latter. (shrink)

The thesis introduces and criticizes the discourse on technology, with a specific reference to the concept of AI. The discourse on AI is particularly saturated with reified metaphors which drive connotations and delimit understandings of technology in society. To better analyse the discourse on AI, the thesis proposes the concept of “Expected AI”, a composite signifier filled with historical and sociocultural connotations, and numerous referent objects. Relying on cultural semiotics, science and technology studies, and a diverse selection of heuristic concepts, (...) the thesis delves beneath the surface of AI discourse and demonstrates the hidden political, social, cultural, and ecological dangers of AI. The entanglement of the discourse(s) with (science) fiction, folklore, myth, and religion impacts how AI is perceived and received, as well as the expectations to AI-enabled technologies now and in the future. The thesis also proposes a more ethical and comprehensive ontological model for AI systems. The model describes AI systems as complex figurations, considering their socio-material organisation, global economic-material becoming, and impact on the environment, social institutions, and the semiosphere. The dissertation argues that AI should be understood not just as an object or sociotechnical system, but as its entire product chain encompassing people and cultures, as well as the used resources and impact (both material-ecological and semiotic) on a planetary scale. (shrink)

Collaborative remembering, in which two or more individuals cooperate to remember together, is an ordinary occurrence. Ordinary though it may be, it challenges traditional understandings of remembering as a cognitive process unfolding within a single subject, as well as traditional understandings of memory knowledge as a justified memory belief held within the mind of a single subject. Collaborative memory has come to be a major area of research in psychology, but it has so far not been investigated in epistemology. In (...) this chapter, we attempt an initial exploration of the epistemological implications of collaborative memory research, taking as our starting point the “extended knowledge” debate which has resulted from the recent encounter between extracranialist theories of cognition and externalist theories of knowledge (Carter et al., 2014; Carter et al., forthcoming). Various forms of socially and technologically augmented memory have played important roles in the extended knowledge debate, but the debate has so far not taken collaborative memory, in particular, into account. We will argue that collaborative memory supports a novel externalist theory of knowledge: distributed reliabilism. Distributed reliabilism departs in two important respects from both traditional reliabilism (Goldman, 2012) and updated theories such as extended (Goldberg, 2010) and social reliabilism (Goldman, 2014). First, it acknowledges that belief-forming processes may extend extracranially to include processing performed both by other subjects and by technological artifacts. Second, it acknowledges that distributed sociotechnical systems themselves may be knowing subjects. Overall, then, the main aim of the chapter is to draw out the philosophical implications of psychological research on collaborative memory. But our argument will also suggest that it may be useful to broaden the standard conception of collaborative memory to include not only the sorts of direct interactions among subjects that have been the focus of psychological research so far but also a range of more indirect, technology-supported and -mediated interactions, and it thus has implications for psychology as well. (shrink)

Contextual Integrity (CI) is built to assess potential privacy violations of new sociotechnical systems and practices. It does so by evaluating their respect for the context-relative informational norms at play in a given context. But can CI evaluate new sociotechnical systems that severely disrupt established social practices? In this paper, I argue that, while CI claims to be able to assess privacy violations of all sociotechnical systems and practices, it cannot assess the ones that (...) cause severe changes and disruptions in the norms and values of a given context. These types of technology are known as socially disruptive technologies (SDTs) and this paper argues that they are beyond CI’s scope. It follows that at best, a privacy assessment of those technologies by CI would be useless and, at worst, lead to potential harm, including failure to identify privacy violations and unwarranted legitimisation of privacy-threatening technology. Government actors, policymakers, and academics should refrain from relying on CI to assess this type of technology. (shrink)

Differential privacy (DP) aims to confer data processing systems with inherent privacy guarantees, offering strong protections for personal data. But DP’s approach to privacy carries with it certain assumptions about how mathematical abstractions will be translated into real-world systems, which—if left unexamined and unrealized in practice—could function to shield data collectors from liability and criticism, rather than substantively protect data subjects from privacy harms. This article investigates these assumptions and discusses their implications for using DP to govern data-driven (...) systems. In Parts 1 and 2, we introduce DP as, on one hand, a mathematical framework and, on the other hand, a kind of real-world sociotechnical system, using a hypothetical case study to illustrate how the two can diverge. In Parts 3 and 4, we discuss the way DP frames privacy loss, data processing interventions, and data subject participation, arguing it could exacerbate existing problems in privacy regulation. In part 5, we conclude with a discussion of DP’s potential interactions with the endogeneity of privacy law, and we propose principles for best governing DP systems. In making such assumptions and their consequences explicit, we hope to help DP succeed at realizing its promise for better substantive privacy protections. (shrink)

While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new (...) AI methods could be adapted for feminist purposes and what role new technologies might play in addressing concerns raised by feminist epistemologists and theorists about algorithmic systems. In particular, we highlight distributed and federated learning as providing partial solutions to the power-oriented concerns that have stymied efforts to make machine learning systems more representative and pluralist. (shrink)

Prometheus has grown four years older since its last and highly controversial special issue, published in 2017 on the Shaken Baby Debate. But, as always, Prometheus is committed to open discussion and dissemination of scientific research, regardless of the potential backlash or controversy that may ensue from such a venture, a venture that is at the core of authentic scholarship. Since the beginning of 2020, the world has changed irrevocably, making once-held norms seem obsolete in favour of new ways of (...) being in the world and new technologies emerging to face these new ways of living. Although it has been a long-held insight in the philosophy of technology that technical systems are carriers of values, the SARS-CoV-2 pandemic has made manifest how these values, and their incarnations in sociotechnical systems, can likewise change. Prometheus has, since its inception, danced in tandem with the critical interpretations, theories, and methods for understanding innovation, and how innovations fundamentally impact and are impacted by the world in which they emerge and are situated. For this reason, Steffen Steinert, Tristan de Wildt, and I chose to guest edit this special issue on designing for value change and chose Prometheus as its home. (shrink)

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and academics (...) have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented... (shrink)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, (...) standards, process, and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (shrink)

Examining AI spirituality can illuminate problematic assumptions about human spirituality and AI cognition, suggest possible directions for AI development, reduce uncertainty about future AI, and yield a methodological lens sufficient to investigate human-AI sociotechnical interaction and morality. Incompatible philosophical assumptions about human spirituality and AI limit investigations of both and suggest a vast gulf between them. An emergentist approach can replace dualist assumptions about human spirituality and identify emergent behavior in AI computation to overcome overly reductionist assumptions about computation. (...) Using general systems theory to organize models of human experience yields insight into human morality and spirituality, upon which AI modeling can also draw. In this context, the pragmatist Josiah Royce’s semiotic philosophy of spirituality identifies unanticipated overlap between symbolic AI and spirituality and suggests criteria for a human-AI community focused on modeling morality that would result in an emergent Interpreter-Spirit sufficient to influence the ongoing development of human and AI morality and spirituality. (shrink)

The expanding social role and continued development of artificial intelligence (AI) needs theological investigation of its anthropological and moral potential. A pragmatic theological anthropology adapted for AI can characterize moral AI as experiencing its natural, social, and moral world through interpretations of its external reality as well as its self-reckoning. Systems theory can further structure insights into an AI social self that conceptualizes itself within Ignacio Ellacuria’s historical reality and its moral norms through Thomistic ideogenesis. This enables a conceptualization (...) process capable of carrying moral weight and grounded in reality; structures the experience of an AI emergent self into multiple levels of interpretation; and drives a multi-level systems architecture for moral AI. Modeling AI’s interpretive experience and self-reckoning as a causal, sociotechnical, and moral actor can help moral AI identify conflicts between its normative values and develop the practical wisdom (phronesis) needed to apply its general moral models. (shrink)

Genetic engineering technologies are a subclass of the biotechnology family, and are concerned with the use of laboratory-based technologies to intervene with a given organism at the genetic level, i.e., the level of its DNA. This class of technologies could feasibly be used to treat diseases and disabilities, create disease-resistant crops, or even be used to enhance humans to make them more resistant to certain environmental conditions. However, both therapeutic and enhancement applications of genetic engineering raise serious ethical concerns. This (...) paper examines various objections to genetic engineering (as applied to humans) which have been raised in the literature, and presents a new way to frame these issues, and to look for solutions. Specifically, this paper frames genetic engineering technologies within the ‘design turn in applied ethics’ lens and thus situates these technologies as covarying with societal forces. The value sensitive design (VSD) approach to technology design is then appropriated as the conceptual framework in which genetic engineering technologies can be considered so that they can be designed for important human values. By doing so, this paper brings further nuance to the scholarship on genetic engineering technologies by discussing the sociotechnicity of genetic engineering systems rather than framing them as value-neutral tools that either support or constrain values based on how they are used. (shrink)

Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of (...) decomposition, which I call ‘atomism’, and not with decomposition writ large. Atomism posits that function ascriptions must be made to parts with minimal reference to the surrounding system. Complexity does indeed falsify atomism, but I contend that there is a weaker, ‘contextualist’ notion of decomposition that is fully compatible with the properties that holists cite. Contextualism suggests that the function of parts can shift with external context, and that interactions with other parts might help determine their context-appropriate functions. This still admits of functional decomposition within a given context. I will give examples based on the notion of oscillatory multiplexing in systems neuroscience. If contextualism is feasible, then holist inferences are faulty—one cannot infer from the presence of complexity to the failure of decomposition, mechanism, and reductionism. (shrink)

Memory evolved to supply useful, timely information to the organism’s decision-making systems. Therefore, decision rules, multiple memory systems, and the search engines that link them should have coevolved to mesh in a coadapted, functionally interlocking way. This adaptationist perspective suggested the scope hypothesis: When a generalization is retrieved from semantic memory, episodic memories that are inconsistent with it should be retrieved in tandem to place boundary conditions on the scope of the generalization. Using a priming paradigm and a (...) decision task involving person memory, the authors tested and confirmed this hypothesis. The results support the view that priming is an evolved adaptation. They further show that dissociations between memory systems are not—and should not be—absolute: Independence exists for some tasks but not others. (shrink)

It is commonly accepted that clinicians are ethically obligated to disclose their use of medical machine learning systems to patients, and that failure to do so would amount to a moral fault for which clinicians ought to be held accountable. Call this ‘the disclosure thesis.’ Four main arguments have been, or could be, given to support the disclosure thesis in the ethics literature: the risk-based argument, the rights-based argument, the materiality argument and the autonomy argument. In this article, I (...) argue that each of these four arguments are unconvincing, and therefore, that the disclosure thesis ought to be rejected. I suggest that mandating disclosure may also even risk harming patients by providing stakeholders with a way to avoid accountability for harm that results from improper applications or uses of these systems. (shrink)

There are various philosophical approaches and theories describing the intimate relation people have to artifacts. In this paper, I explore the relation between two such theories, namely distributed cognition and distributed morality theory. I point out a number of similarities and differences in these views regarding the ontological status they attribute to artifacts and the larger systems they are part of. Having evaluated and compared these views, I continue by focussing on the way cognitive artifacts are used in moral (...) practice. I specifically conceptualise how such artifacts (a) scaffold and extend moral reasoning and decision-making processes, (b) have a certain moral status which is contingent on their cognitive status, and (c) whether responsibility can be attributed to distributed systems. This paper is primarily written for those interested in the intersection of cognitive and moral theory as it relates to artifacts, but also for those independently interested in philosophical debates in extended and distributed cognition and ethics of (cognitive) technology. (shrink)

This paper examines two prominent formal trade-offs in artificial intelligence (AI)---between predictive accuracy and fairness, and between predictive accuracy and interpretability. These trade-offs have become a central focus in normative and regulatory discussions as policymakers seek to understand the value tensions that can arise in the social adoption of AI tools. The prevailing interpretation views these formal trade-offs as directly corresponding to tensions between underlying social values, implying unavoidable conflicts between those social objectives. In this paper, I challenge that prevalent (...) interpretation by introducing a sociotechnical approach to examining the value implications of trade-offs. After providing a set-theoretic understanding of these model trade-offs, I argue that their implications cannot be understood in isolation from the technical, psychological, organizational, and social factors that shape the integration of AI models into decision-making pipelines. Specifically, I identify three key considerations---validity and instrumental relevance, compositionality, and dynamics---for contextualizing and characterizing these implications. These considerations reveal that the relationship between model trade-offs and corresponding values depends on critical choices and assumptions. Crucially, judicious sacrifices in one model property for another can, in fact, promote both sets of corresponding values. The proposed sociotechnical perspective thus shows that we can and should aspire to higher epistemic and ethical possibilities than the prevalent interpretation suggests, while offering practical guidance for achieving those outcomes. Finally, I draw out the broader implications of this perspective for AI design and governance, highlighting the need to broaden normative engagement across the AI lifecycle, develop legal and auditing tools sensitive to sociotechnical considerations, and rethink the vital role and appropriate structure of interdisciplinary collaboration in fostering a responsible AI workforce. (shrink)

Dynamicism has provided cognitive science with important tools to understand some aspects of “how cognitive agents work” but the issue of “what makes something cognitive” has not been sufficiently addressed yet, and, we argue, the former will never be complete without the later. Behavioristic characterizations of cognitive properties are criticized in favor of an organizational approach focused on the internal dynamic relationships that constitute cognitive systems. A definition of cognition as adaptive-autonomy in the embodied and situated neurodynamic domain is (...) provided: the compensatory regulation of a web of stability dependencies between sensorimotor structures, is created and preserved during a historical/developmental process. We highlight the functional role of emotional embodiment: internal bioregulatory processes coupled to the formation and adaptive regulation of neurodynamic autonomy. Finally, we discuss a “minimally cognitive behavior program” in evolutionary simulation modelling suggesting that much is to be learned from a complementary “minimally cognitive organization program”. (shrink)

I defend a theory of mental representation that satisfies naturalistic constraints. Briefly, we begin by distinguishing (i) what makes something a representation from (ii) given that a thing is a representation, what determines what it represents. Representations are states of biological organisms, so we should expect a unified theoretical framework for explaining both what it is to be a representation as well as what it is to be a heart or a kidney. I follow Millikan in explaining (i) in terms (...) of teleofunction, explicated in terms of natural selection. -/- To explain (ii), we begin by recognizing that representational states do not have content, that is, they are neither true nor false except insofar as they both “point to” or “refer” to something, as well as “say” something regarding whatever it is they are about. To distinguish veridical from false representations, there must be a way for these separate aspects to come apart; hence, we explain (ii) by providing independent theories of what I call f-reference and f-predication (the ‘f’ simply connotes ‘fundamental’, to distinguish these things from their natural language counterparts). -/- Causal theories of representation typically founder on error, or on what Fodor has called the disjunction problem. Resemblance or isomorphism theories typically founder on what I’ve called the non-uniqueness problem, which is that isomorphisms and resemblance are practically unconstrained and so representational content cannot be uniquely determined. These traditional problems provide the motivation for my theory, the structural preservation theory, as follows. F-reference, like reference, is a specific, asymmetric relation, as is causation. F-predication, like predication, is a non-specific relation, as predicates typically apply to many things, just as many relational systems can be isomorphic to any given relational system. Putting these observations together, a promising strategy is to explain f-reference via causal history and f-predication via something like isomorphism between relational systems. -/- This dissertation should be conceptualized as having three parts. After motivating and characterizing the problem in chapter 1, the first part is the negative project, where I review and critique Dretske’s, Fodor’s, and Millikan’s theories in chapters 2-4. Second, I construct my theory about the nature of representation in chapter 5 and defend it from objections in chapter 6. In chapters 7-8, which constitute the third and final part, I address the question of how representation is implemented in biological systems. In chapter 7 I argue that single-cell intracortical recordings taken from awake Macaque monkeys performing a cognitive task provide empirical evidence for structural preservation theory, and in chapter 8 I use the empirical results to illustrate, clarify, and refine the theory. (shrink)

The key assumption behind evolutionary epistemology is that animals are active learners or ‘knowers’. In the present study, I updated the concept of natural learning, developed by Henry Plotkin and John Odling-Smee, by expanding it from the animal-only territory to the biosphere-as-a-whole territory. In the new interpretation of natural learning the concept of biological information, guided by Peter Corning’s concept of “control information”, becomes the ‘glue’ holding the organism–environment interactions together. The control information guides biological systems, from bacteria to (...) ecosystems, in the process of natural learning executed by the universal algorithm. This algorithm, summarized by the acronym IGPT (information-gain-process-translate) incorporates natural cognitive methods including sensing/perception, memory, communication, and decision-making. Finally, the biosphere becomes the distributed network of communicative interactions between biological systems termed the interactome. The concept of interactome is based on Gregory Bateson’s natural epistemology known as the “ecology of mind”. Mimicking Bateson’s approach, the interactome may also be designated “physiology of mind”—the principle behind regulating the biosphere homeostasis. (shrink)

Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information (...) and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research. (shrink)

For some post-structuralist complexity theorists, there are no epistemic meta-perspectives from where to judge between different epistemic perspectives toward complex systems. In this paper, I argue that these theorists face a dilemma because they argue against meta-perspectives from just such a meta-perspective. In fact, when we understand two or more different perspectives, we seem to unavoidably adopt a meta-perspective to analyse, compare, and judge between those perspectives. I further argue that meta-perspectives can be evaluated and judged from meta-meta-perspectives, and (...) so on. This suggests an epistemic hierarchy. Perspectives, meta-perspectives, meta-meta-perspectives, etc. can be ranked according to the degree to which they confer understanding. I also explore what scope my thesis might have outside the philosophy of complexity by applying it to the sociology of science. (shrink)

In this paper a possible general framework for the representation of concepts in cognitive artificial systems and cognitive architectures is proposed. The framework is inspired by the so called proxytype theory of concepts and combines it with the heterogeneity approach to concept representations, according to which concepts do not constitute a unitary phenomenon. The contribution of the paper is twofold: on one hand, it aims at providing a novel theoretical hypothesis for the debate about concepts in cognitive sciences by (...) providing unexplored connections between different theories; on the other hand it is aimed at sketching a computational characterization of the problem of concept representation in cognitively inspired artificial systems and in cognitive architectures. (shrink)

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better (...) grip on how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

Should models of consciousness be detailed _mechanistic_ models of particular types of systems, or should they be _minimal_ models that abstract away from the underlying mechanistic details and provide generalisations? Detailed mechanistic models may afford a complete and precise account of consciousness in human beings and other, physiologically similar mammals. But they do not provide a good model of consciousness in other animals, such as non-vertebrates, let alone artificial systems. Minimal models can be applicable to a wide range (...) of different conscious systems. But do they provide genuine explanations that are autonomous from explanations by detailed mechanistic models? This paper provides a taxonomy of minimal models and measures of consciousness, clarifies their relation to detailed mechanistic models, and highlights benefits of different minimalist approaches to consciousness. (shrink)

The purpose of this paper is to defend what I call the action-oriented coding theory (ACT) of spatially contentful visual experience. Integral to ACT is the view that conscious visual experience and visually guided action make use of a common subject-relative or 'egocentric' frame of reference. Proponents of the influential two visual systems hypothesis (TVSH), however, have maintained on empirical grounds that this view is false (Milner & Goodale, 1995/2006; Clark, 1999; 2001; Campbell, 2002; Jacob & Jeannerod, 2003; Goodale (...) & Milner, 2004). One main source of evidence for TVSH comes from behavioral studies of the comparative effects of size-contrast illusions on visual awareness and visuo- motor action. This paper shows that not only is the evidence from illusion studies inconclusive, there is a better, ACT-friendly interpretation of the evidence that avoids serious theoretical difficulties faced by TVSH. (shrink)

A construction principle for natural deduction systems for arbitrary, finitely-many-valued first order logics is exhibited. These systems are systematically obtained from sequent calculi, which in turn can be automatically extracted from the truth tables of the logics under consideration. Soundness and cut-free completeness of these sequent calculi translate into soundness, completeness, and normal-form theorems for natural deduction systems.

An increasing number of regulations propose the notion of ‘AI audits’ as an enforcement mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the purpose of compliance and assurance currently have little to no agreed upon practices, procedures, taxonomies, and standards. We propose the ‘criterion audit’ as an operationalizable compliance and assurance external audit framework. We model elements of this approach after financial auditing practices, and (...) argue that AI audits should similarly provide assurance to their stakeholders about AI organizations’ ability to govern their algorithms in ways that mitigate harms and uphold human values. We discuss the necessary conditions for the criterion audit, and provide a procedural blueprint for performing an audit engagement in practice. We illustrate how this framework can be adapted to current regulations by deriving the criteria on which ‘bias audits’ for hiring algorithms can be performed, as required by the recently effective New York City Local Law 144 of 2021. We conclude by offering critical discussion on the benefits, inherent limitations, and implementation challenges of applying practices of the more mature financial auditing industry to AI auditing where robust guardrails against quality assurance issues are only starting to emerge. Our discussion as informed by experiences in performing these audits in practice highlights the critical role that an audit ecosystem plays in ensuring the effectiveness of such methodology. (shrink)

Philosophers have become increasingly aware of the difficulties that plague accounts of kinds with objectively determined boundaries, and generally recognise that scientific taxonomies are shaped by human pragmatic interests and non-epistemic values. Against this trend, we propose an account of kinds conceived as dynamic entities, characterised by qualitatively distinct and robust trajectories originating from bifurcation events in the development of complex systems. We argue that the Homeorhetic Dynamic Kinds account (HDK) can be applied to systems investigated in a (...) variety of disciplinary contexts, ranging from biology, medicine, and the social sciences. Shifting the focus from a synchronic (homeostatic) to a dynamic and processual (homeorhetic) perspective, we show that HDK allows a better characterisation of discontinuities among kinds. We then outline its implications for pluralism, particularly how HDK can help us understand how scientific categories are shaped both by ontological aspects of developmental trajectories and by pragmatic, value-laden considerations. (shrink)

I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation of (...) chemotaxis in Escherichia coli—I argue that each strategy invokes a different combination of abstraction types and that each targets its abstractions to different mechanistic details. (shrink)

The research aims to harness spatial interpolation techniques to produce maps with a high level of perceptual accuracy in representing the population data of the study area. This is achieved after exploring the statistical and spatial nature of the databases used, analyzing them, and determining their distribution using a variety of spatial data exploration tools available within the GIS (Geographic Information Systems) environment. These tools contribute to evaluating the characteristics, distribution, and analysis of data, including testing data distribution, identifying (...) its direction, and uncovering its spatial correlations. This highlights the importance of the study and understanding the distribution pattern of the population data in the study area, thereby facilitating the preparation of future that serve spatial organization by building spatial models for the numerical distribution of the data for age groups: young, middle-aged, and elderly, at the level of administrative units of the study area by relying on the inductive approach and the quantitative analysis approach. This is done using Geostatistical Analysis methods within the concept of spatial interpolation in GIS. The research also seeks to predict the population maps for Thi Qar Governorate by comparing spatial interpolation methods, namely Inverse Distance Weighting (IDW) and Simple Kriging (SK). The study concluded, after verifying the accuracy of the results using the Cross-Validation curve, that the Simple Kriging (SK) method is the most accurate model in spatial prediction of population data for representing the data of the young age group in the study area, as it had the lowest Root Mean Square Error (RMSE) of 10.012. It was followed by the Inverse Distance Weighting (IDW) method for representing the data of the elderly age group with an RMSE of 350.48. This indicates that the use of statistical criteria improves the accuracy of spatial interpolation and that the spatial prediction of the population data for the study area using the Simple Kriging (SK) method was more accurate than the Inverse Distance Weighting (IDW) method based on statistical indicators. (shrink)

Biologists often study particular biological systems as models of a phenomenon of interest even if they already know that the phenomenon is produced by diverse mechanisms and hence none of those systems alone can sufficiently represent it. To understand this modeling practice, the present paper provides an account of how multiple model systems can be used to study a phenomenon that is produced by diverse mechanisms. Even if generalizability of results from a single model system is significantly (...) limited, generalizations concerning specific aspects of mechanisms often hold across certain ranges of biological systems, which enables multiple model systems to jointly represent such a phenomenon. Comparing mechanisms that operate in different biological systems as examples of the same phenomenon also facilitates characterization and investigation of individual mechanisms. I also compare my account with two existing accounts of the use of multiple model systems and argue that my account is distinct from and complementary to them. (shrink)

International Studies in the Philosophy of Science, Volume 27, Issue 3, Page 273-293, September 2013.

The European project European and Latin American Systems of Ethics Regulation of Biomedical Research Project (EULABOR) has carried out the first comparative analysis of ethics regulation systems for biomedical research in seven countries in Europe and Latin America, evaluating their roles in the protection of human subjects. We developed a conceptual and methodological framework defining ‘ethics regulation system for biomedical research’ as a set of actors, institutions, codes and laws involved in overseeing the ethics of biomedical research on (...) humans. This framework allowed us to develop comprehensive national reports by conducting semi-structured interviews to key informants. These reports were summarised and analysed in a comparative analysis. The study showed that the regulatory framework for clinical research in these countries differ in scope. It showed that despite the different political contexts, actors involved and motivations for creating the regulation, in most of the studied countries it was the government who took the lead in setting up the system. The study also showed that Europe and Latin America are similar regarding national bodies and research ethics committees, but the Brazilian system has strong and noteworthy specificities. (shrink)

The Joint Battle Management Language (JBML) is an XML-based language designed to allow Command and Control (C2) systems to interface easily with Modeling and Simulation (M&S) systems. While some of the XML-tags defined in this language correspond to types of entities that exist in reality, others are mere syntactic artifacts used to structure the messages themselves. Because these two kinds of tags are not formally distinguishable, JBML messages in effect confuse data with what the data represent. In this (...) paper we show how a realism-based ontology combined with a rule language can be used to make these distinctions explicit. The approach allows storage of the contents of JBML messages in a Referent Tracking System in a format that mimics the structure of reality thereby providing an aid to message validation. (shrink)

The proliferation of Internet of Things (IoT) devices has introduced a range of opportunities for enhanced connectivity, automation, and efficiency. However, the vast array of interconnected devices has also raised concerns regarding cybersecurity, particularly due to the limited resources and diverse nature of IoT devices. Intrusion detection systems (IDS) have emerged as critical tools for identifying and mitigating security threats. This paper proposes a Multi-Layer Intrusion Detection Framework for IoT systems, leveraging Ensemble Machine Learning (EML) techniques to improve (...) the accuracy and effectiveness of detecting intrusions. The proposed framework integrates multiple layers of defense, including data preprocessing, feature extraction, classification, and post-processing, to provide a robust solution to IoT security challenges. This research explores the application of EML methods such as Random Forests, AdaBoost, and Gradient Boosting, combining them into a unified model to detect and mitigate various types of attacks in IoT environments. Experimental results demonstrate the superiority of the proposed framework in terms of detection accuracy, false positive rate, and computational efficiency. (shrink)

Autonomy is often considered a core value of Western society that is deeply entrenched in moral, legal, and political practices. The development and deployment of artificial intelligence (AI) systems to perform a wide variety of tasks has raised new questions about how AI may affect human autonomy. Numerous guidelines on the responsible development of AI now emphasise the need for human autonomy to be protected. In some cases, this need is linked to the emergence of increasingly ‘autonomous’ AI (...) class='Hi'>systems that can perform tasks without human control or supervision. Do such ‘autonomous’ systems pose a risk to our own human autonomy? In this article, I address the question of a trade-off between human autonomy and system ‘autonomy’. (shrink)

The monograph presents the ideas about the main changes that occurred in the development of technologies from the emergence of Homo sapiens till present time and outlines the prospects of their development in the next 30–60 years and in some respect until the end of the twenty-first century. What determines the transition of a society from one level of development to another? One of the most fundamental causes is the global technological transformations. Among all major technological breakthroughs in history the (...) most important are three production revolutions: 1) the Agrarian Revolution; 2) the Industrial Revolution; and 3) the Cybernetic one. The book introduces the theory of production revolutions which is a new valuable explanatory paradigm that analyzes causes and trends of dramatic shifts in historical process. The authors describe the course of technological transformations in history and demonstrate a possible application of the theory to explain the present and forthcoming technological changes. They analyze the technological shifts which took place in the second half of the twentieth and early twenty-first centuries and forecast the main shifts in the next half a century. On this basis the authors present a detailed analysis of the latest production revolution which is denoted as ‘Сybernetic’. They make some predictions about its development in the nearest five decades and up to the end of the twenty-first century and show that the development of various self-regulating systems will be the main trend of this revolution. The authors argue that the transition to the starting final phase of the Cybernetic Revolution (in the 2030–2040s) will first occur in the field of medicine (in some its innovative branches). In future we will deal with the started convergence of innovative technologies which will form the system of MANBRIC-technologies (i.e. the technological paradigm based on medicine, additive, nano- and bio- technologies, robotics, IT and cognitive technologies). The monograph gives an outline of the future breakthroughs in medicine and some other technologies (between the 2010s and 2070s). (shrink)

Memory Detection Tests (MDTs) are a general class of psychophysiological tests that can be used to determine whether someone remembers a particular fact or datum. The P300 MDT is a type of MDT that relies on a presumed correlation between the presence of a detectable neural signal (the P300 “brainwave”) in a test subject, and the recognition of those facts in the subject’s mind. As such, the P300 MDT belongs to a class of brain-based forensic technologies which have proved popular (...) and controversial in recent years. With such tests increasingly being proffered for use in the courtroom — to either support or call into question testimony — it would behoove the legal system to have some systematic framework for ensuring that they are used responsibly. In this paper, I defend one such framework for ensuring that this is the case: the legitimacy enhancing test. According to this test, it is appropriate to make use of technologies such as the P300 MDT whenever doing so would (probably) enhance the legitimacy of the trial. I argue that this test addresses tensions between scientific and legal norms of evidence, and exhibits a number of additional virtues including unification, simplicity and flexibility. Although the test is defended by considering the example of the P300 MDT, its significance is much broader than that. If it has the virtues I claim for it, it should provide a general framework for the responsible use of technologies, and the responsible innovation of social epistemic systems. (shrink)

This paper is concerned with the construction of theories of software systems yielding adequate predictions of their target systems’ computations. It is first argued that mathematical theories of programs are not able to provide predictions that are consistent with observed executions. Empirical theories of software systems are here introduced semantically, in terms of a hierarchy of computational models that are supplied by formal methods and testing techniques in computer science. Both deductive top-down and inductive bottom-up approaches in (...) the discovery of semantic software theories are refused to argue in favour of the abductive process of hypothesising and refining models at each level in the hierarchy, until they become satisfactorily predictive. Empirical theories of computational systems are required to be modular, as modular are most software verification and testing activities. We argue that logic relations must be thereby defined among models representing different modules in a semantic theory of a modular software system. We exclude that scientific structuralism is able to define module relations needed in software modular theories. The algebraic Theory of Institutions is finally introduced to specify the logic structure of modular semantic theories of computational systems. (shrink)

The purpose of this study is to compile a selection of the various formalisms found in conversation theory to introduce readers to Pask's discursive algebra. In this way, the text demonstrates how concept sharing and concept formation by means of the interaction of two participants may be formalized. The approach taken in this study is to examine the formal notation system used by Pask and demonstrate how such formalisms may be used to represent concept sharing and concept formation through conversation. (...) The compilation of the discursive algebra using the framework provided by conversation theory could potentially be used as an auxiliary framework to study conversational interactions in multi-agent systems theory. (shrink)

The nature and structure of time and time-intervals in physical, chemical and biological systems will be elucidated. The relation and dependence among time, energy and taking place of natural processes will be critically analyzed. The bio-processes taking place in nano-time intervals will be identified. Their relevance to nano-bio-science and nano-bio-technology will be developed and nano-time interval-aspect of nano-sciences and nano-technology will be advanced. -/- .

In “What Does Environmental Protection Protect?” Mark Sagoff argues that there is no ecological way to test the claim that natural ecosystems are complex adaptive systems. In this critical commentary, I recreate that argument, object to it, and attempt to clarify its normative upshot. I show that Sagoff relies on substantive assumptions about (1) the tools and methods of ecological science, (2) what can be done with those tools and methods, and (3) ecology’s being separable from other disciplines, all (...) of which are controversial and in need of defense. I also identify five different ways that one might interpret the action-guiding recommendation that Sagoff wants to make on the basis of that argument, and I explain why all five are somewhat problematic. (shrink)