In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...) the nature of the ENCODE project, the relevant notion of function and the claim that most of our genome is junk. We argue that evolutionary accounts of function presuppose functions as ‘causal roles’, and that selection is but a useful proxy for relevant functions, which might well be unsuitable to biomedical research. Taking a closer look at the discovery process in which ENCODE participates, we argue that ENCODE’s strategy of biochemical signatures successfully identified activities of DNA elements with an eye towards causal roles of interest to biomedical research. We argue that ENCODE’s controversial claim of functionality should be interpreted as saying that 80 % of the genome is engaging in relevant biochemical activities and is very likely to have a causal role in phenomena deemed relevant to biomedical research. Finally, we discuss ambiguities in the meaning of junk DNA and in one of the main arguments raised for its prevalence, and we evaluate the impact of ENCODE’s results on the claim that most of our genome is junk. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing (...) how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students. (shrink)

Presenting a fascinating analysis of the idea of what can't be said, this book ascertains whether the notion of there being a truth, or a state of affairs, or knowledge that can't be expressed linguistically is a coherent notion. The author distinguishes different senses in which it might be said that something can't be said. The first part looks at the question of whether ineffability is a coherent idea. Part two evaluates two families of arguments regarding whether ineffable states of (...) affairs actually exist: the argument from mysticism and the argument from epistemic boundedness. Part three looks more closely at the relation between mystic and non-mystic stances. In the fourth and final part the author distinguishes five qualitatively different types of ineffability. _Ineffability and Philosophy_ is a significant contribution to this area of research and will be essential reading for philosophers and those researching and studying the philosophy of language. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

In this challenging study, André Gallois proposes and defends a thesis about the character of our knowledge of our own intentional states. Taking up issues at the centre of attention in contemporary analytic philosophy of mind and epistemology, he examines accounts of self-knowledge by such philosophers as Donald Davidson, Tyler Burge and Crispin Wright, and advances his own view that, without relying on observation, we are able justifiably to attribute to ourselves propositional attitudes, such as belief, that we consciously (...) hold. His study will be of wide interest to philosophers concerned with questions about self-knowledge. (shrink)

Experiences of absence are common in everyday life, but have received little philosophical attention until recently, when two positions regarding the nature of such experiences surfaced in the literature. According to the Perceptual View, experiences of absence are perceptual in nature. This is denied by the Surprise-Based View, according to which experiences of absence belong together with cases of surprise. In this paper, I show that there is a kind of experience of absence—which I call frustrating absences—that has been overlooked (...) by the Perceptual View and by the Surprise Based-View and that cannot be adequately explained by them. I offer an alternative account to deal with frustrating absences, one according to which experiencing frustrating absences is a matter of subjects having desires for something to be present frustrated by the world. Finally, I argue that there may well be different kinds of experiences of absence. (shrink)

In the past few years, machine learning (ML) tools have been implemented with success in the medical context. However, several practitioners have raised concerns about the lack of transparency—at the algorithmic level—of many of these tools; and solutions from the field of explainable AI (XAI) have been seen as a way to open the ‘black box’ and make the tools more trustworthy. Recently, Alex London has argued that in the medical context we do not need machine learning tools to be (...) interpretable at the algorithmic level to make them trustworthy, as long as they meet some strict empirical desiderata. In this paper, we analyse and develop London’s position. In particular, we make two claims. First, we claim that London’s solution to the problem of trust can potentially address another problem, which is how to evaluate the reliability of ML tools in medicine for regulatory purposes. Second, we claim that to deal with this problem, we need to develop London’s views by shifting the focus from the opacity of algorithmic details to the opacity of the way in which ML tools are trained and built. We claim that to regulate AI tools and evaluate their reliability, agencies need an explanation of how ML tools have been built, which requires documenting and justifying the technical choices that practitioners have made in designing such tools. This is because different algorithmic designs may lead to different outcomes, and to the realization of different purposes. However, given that technical choices underlying algorithmic design are shaped by value-laden considerations, opening the black box of the design process means also making transparent and motivating (technical and ethical) values and preferences behind such choices. Using tools from philosophy of technology and philosophy of science, we elaborate a framework showing how an explanation of the training processes of ML tools in medicine should look like. (shrink)

Lorenz proposed in his (1935) articulation of a theory of behavioral instincts that the objective of ethology is to distinguish behaviors that are “innate” from behaviors that are “learned” (or “acquired”). Lorenz’s motive was to open the investigation of certain “adaptive” behaviors to evolutionary theorizing. Accordingly, since innate behaviors are “genetic”, they are open to such investigation. By Lorenz’s light an innate/acquired or learned dichotomy rested on a familiar Darwinian distinction between genes and environments. Ever since Lorenz, ascriptions of innateness (...) have become widespread in the cognitive, behavioral, and biological sciences. The trend continues despite decades of strong arguments that show, in particular, the dichotomy that Lorenz invoked in his theory of behavioral instincts is literally false: no biological trait is the product of genes alone. Some critics suggest that the failure of Lorenz’s account shows that innateness is not well-defined in biology and the practice of ascribing innateness to various biological traits should be dropped from respectable science. Elsewhere (Ariew 1996) I argued that despite the arguments of critics, there really is a biological phenomenon underlying the concept of innateness. On my view, innateness is best understood in terms of C.H. Waddington’s concept of “canalization”, i.e. the degree to which a trait is innate is the degree to which its developmental outcome is canalized. The degree to which a developmental outcome is canalized is the degree to which the developmental process is bound to produce a particular endstate despite environmental fluctuations both in the development’s initial state and during the course of development. The canalization account differs in many ways to the traditional ways that ethologists such as Konrad Lorenz originally understood the concept of innateness. Most importantly, on the canalization account the distinction between innate and acquired is not a dichotomy, as Konrad Lorenz had it, but rather a matter of degree difference that lies along a spectrum with highly canalized development outcomes on the one end and highly environmentally sensitive development outcomes on the other end. Nevertheless, I justified the canalization account on the basis of a set of desiderata or criteria that I suggested falls-out of what seemed uncontroversial about Lorenz’s account of innateness (briefly): innateness is a property of a developing individual, innateness denotes environmental stability, and innate-ascriptions are useful in certain natural selection explanations (more below). From that same set of desiderata I argued (in my 1996) that neither the concept of heritability nor of norms of reactions—two concepts from population genetics—suffice to ground innateness. In this essay, I wish to provide further support of the canalization account in two ways. First, I wish to better motivate the desiderata by revisiting a debate between Konrad Lorenz and Daniel Lehrman over the meaning and explanatory usefulness of innate ascriptions in ethology. Second, I wish to compare my canalization account of innateness with accounts proposed by contemporary philosophers, one by Stephen Stich (1975), another by Elliott Sober (forthcoming), and a third by William Wimsatt (1986). (shrink)

In the past few years, the ethical ramifications of AI technologies have been at the center of intense debates. Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars have highlighted the limitations of such a principled approach. Drawing from microethics and the virtue theory tradition, (...) in this paper, we formulate a different approach to ethics in data science which is based on a different conception of “being ethical” and, ultimately, of what it means to promote a morally responsible data science. First, we develop the idea that, rather than only compliance, ethical decision-making consists in using certain moral abilities, which are cultivated by practicing and exercising them in the data science process. An aspect of virtue development that we discuss here is moral attention, which is the ability of data scientists to identify the ethical relevance of their own technical decisions in data science activities. Next, by elaborating on the capability approach, we define a technical act as ethically relevant when it impacts one or more of the basic human capabilities of data subjects. Therefore, rather than “applying ethics”, data scientists should cultivate ethics as a form of reflection on how technical choices and ethical impacts shape one another. Finally, we show how this microethical framework concretely works, by dissecting the ethical dimension of the technical procedures involved in data understanding and preparation of electronic health records. (shrink)

In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, (...) post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methods _too, because of specific identifiable characteristics,_ can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices. (shrink)

Recently, biologists have argued that data - driven biology fosters a new scientific methodology; namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data - driven studies can be included into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...) generalizations to complement the procedure of prioritization. Overall this paper aims to shed light on the structure of contemporary research in molecular biology. (shrink)

In jurisprudential literature, the adjective ‘defeasible’ appears as a predicate of many terms: concepts, laws, rules, reasoning, justification, proof, and so on. In this paper, we analyze the effects of some versions of the thesis of the defeasibility of legal norms on the reconstruction of the notion of legal validity. We analyze some possible justifications of this thesis considered as a claim concerning validity, and enquire into two possible sets of problems related to the defeasibility of the criteria of identification (...) of a legal system. We also provide a formalization of some options regarding defeasible criteria of identification, which can be used as a tool for meta-jurisprudential analysis. Finally, the thesis according to which defeasibility is better conceived of as a feature of legal application is examined and questioned. (shrink)

In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...) the context they are embedded within—and hence by the web of relations they are part of. (shrink)

Machine learning (ML) has been praised as a tool that can advance science and knowledge in radical ways. However, it is not clear exactly how radical are the novelties that ML generates. In this article, I argue that this question can only be answered contextually, because outputs generated by ML have to be evaluated on the basis of the theory of the science to which ML is applied. In particular, I analyze the problem of novelty of ML outputs in the (...) context of molecular biology. In order to do this, I first clarify the nature of the models generated by ML. Next, I distinguish three ways in which a model can be novel (from the weakest to the strongest). Third, I dissect the way ML algorithms work and generate models in molecular biology and genomics. On these bases, I argue that ML is either a tool to identify instances of knowledge already present and codified, or to generate models that are novel in a weak sense. The notable contribution of ML to scientific discovery in the context of biology is that it can aid humans in overcoming potential bias by exploring more systematically the space of possible hypotheses implied by a theory. (shrink)

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)

This book presents a comprehensive and detailed exploration of the relationship between the thought of G.W.F. Hegel and that of John McDowell, the latter of whom is widely considered to be one of the most influential living analytic philosophers. It serves as a point of entry in McDowell’s and Hegel’s philosophy, and a substantial contribution to ongoing debates on perceptual experience and perceptual justification, naturalism, human freedom and action. The chapters gathered in this volume, as well as McDowell’s responses, make (...) it clear that McDowell’s work paves the way for an original reading of Hegel’s texts. His conceptual framework allows for new interpretive possibilities in Hegel’s philosophy which, until now, have remained largely unexplored. Moreover, these interpretations shed light on various aspects of continuity and discontinuity between the philosophies of these two authors, thus defining more clearly their positions on specific issues. In addition, they allow us to see Hegel’s thought as containing a number of conceptual tools that might be useful for advancing McDowell’s own philosophy and contemporary philosophy in general. (shrink)

The notion of biological function is fraught with difficulties—intrinsically and irremediably so, we argue. The physiological practice of functional ascription originates from a time when organisms were thought to be designed and remained largely unchanged since. In a secularized worldview, this creates a paradox which accounts of functions as selected effect attempt to resolve. This attempt, we argue, misses its target in physiology and it brings problems of its own. Instead, we propose that a better solution to the conundrum of (...) biological functions is to abandon the notion altogether, a prospect not only less daunting than it appears, but arguably the natural continuation of the naturalisation of biology. (shrink)

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find LMs to (...) be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

In the last few years, the lack of a unitary notion of gene across biological sciences has troubled the philosophy of biology community. However, the debate on this concept has remained largely historical or focused on particular cases presented by the scientific empirical advancements. Moreover, in the literature there are no explicit and reasonable arguments about why a philosophical clarification of the concept of gene is needed. In our paper, we claim that a philosophical clarification of the concept of gene (...) does not contribute to biology. Unlike the question, for example, “What is a biological function?”, we argue that the question “What is a gene?” could be answered by means of empirical research, in the sense that biologists' labour is enough to shed light on it. (shrink)

There is a growing awareness that there are many subtle forms of exclusion and partiality that affect the correct workings of a judicial system. The concept of epistemic injustice, introduced by the philosopher Miranda Fricker, is a useful conceptual tool to understand forms of judicial partiality that often go undetected. In this paper, we present Fricker’s original theory and some of the applications of the concept of epistemic injustice in legal processes. In particular, we want to show that the seed (...) planted by Fricker has flourished into a rich field of study in which the concept is used to analyze many different phenomena in law, not always following the original characterization provided by her. This has led to a distinction between what we will call the narrow version of the concept, which is closer to Fricker’s original account, and the wider version of epistemic injustice, which is a more controversial notion because it is always on the verge of morphing into other well-known concepts like sexism, racial discrimination, oppression, silencing, and gaslighting. We will show that the value of the narrow version is mostly theoretical, and that in order to use the concept of epistemic injustice one must adopt a more liberal understanding of it. (shrink)

We argue that mechanistic models elaborated by machine learning cannot be explanatory by discussing the relation between mechanistic models, explanation and the notion of intelligibility of models. We show that the ability of biologists to understand the model that they work with severely constrains their capacity of turning the model into an explanatory model. The more a mechanistic model is complex, the less explanatory it will be. Since machine learning increases its performances when more components are added, then it generates (...) models which are not intelligible, and hence not explanatory. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

This paper offers a new interpretation for Wittgenstein`s treatment of mathematical identities. As it is widely known, Wittgenstein`s mature philosophy of mathematics includes a general rejection of abstract objects. On the other hand, the traditional interpretation of mathematical identities involves precisely the idea of a single abstract object – usually a number –named by both sides of an equation.

In biology—as in other scientific fields—there is a lively opposition between big and small science projects. In this commentary, I try to contextualize this opposition in the field of biomedicine, and I argue that, at least in this context, big science projects should come first.

REM sleep behaviour disorder is a REM sleep-related parasomnia which may be considered a “dissociated state of wakefulness and sleep”, given that conflicting elements of REM sleep and of wakefulness coexist during the episodes, leading to motor and behavioural manifestations reminiscent of an enacted dream. RBD has been reported in association with α-synucleinopathies: around a third of patients with Parkinson’s disease have full-blown RBD.Recent data indicate that PD patients with RBD are more prone to hallucinations than PD patients without this (...) parasomnia. However it is still not clear why RBD in PD is associated with an increased prevalence of VHs.Data exist which suggest that visual hallucinations in PD may be the result of untimely intrusions of REM visual imagery into wakefulness. RBD, which is characterised by a REM sleep dissociation pattern, might be a condition that particularly favours such intrusions. However, other hypotheses may be advanced. In fact, deficits in attentional, executive, visuoperceptual and visuospatial abilities have been documented in RBD and found to occur far more frequently in PD with RBD than in PD without RBD. Neuropsychological deficits involving visual perception and attentional processes are thought to play an important role in the pathophysiology of VHs. On this basis, RBD in PD could be viewed as a contributory risk factor for VHs. (shrink)

A recent article by Herzog provides a much-needed integration of ethical and epistemological arguments in favor of explicable AI in medicine. In this short piece, I suggest a way in which its epistemological intuition of XAI as “explanatory interface” can be further developed to delineate the relation between AI tools and scientific research.

In this chapter, we propose a non-traditional RCR training in data science that is grounded in a virtue theory framework. First, we delineate the approach in more theoretical detail by discussing how the goal of RCR training is to foster the cultivation of certain moral abilities. We specify the nature of these ‘abilities’: while the ideal is the cultivation of virtues, the limited space allowed by RCR modules can only facilitate the cultivation of superficial abilities or proto-virtues, which help students (...) to familiarize themselves with moral and political issues in the data science environment. Third, we operationalize our approach by stressing that (proto-)virtue acquisition (like skill acquisition) occurs through the technical and social tasks of daily data science activities, where these repetitive tasks provide the opportunities to develop (proto-)virtue capacity and to support the development of ethically robust data systems. Finally, we discuss a concrete example of implementing this approach. In particular, we describe how this method is applied to teach data ethics to students participating in the CODATA-RDA Data Science Summer Schools. (shrink)

The existence of causal explanations in science has been an issue of interest in Western philosophy from its very beginnings. That is the reason this work, following an idea of Mario Bunge, makes a historical review of this matter. The modern treatment of this subject takes place since the postulation by Popper and Hempel of the D-N model of scientific explanation, whose viability is scrutinized here from different points of view in the current philosophy of science. The main object of (...) this paper is to present two arguments against the possibility of causal explanations in theoretical physics. The first one concerns the existence, in certain cases, of inter-theoretical incompatibilities, and the second refers to the need to resort, in other cases, to concatenations of laws of different theories and disciplines. The final conclusion will be the defence of a form of theoretical explanation, which follows the Popper-Hempel model, but devoid of any ontological and metaphysical connotations. (shrink)

In this paper, I present a position that I call erotetic amelioration, according to which we must evaluate and, eventually, improve our answers to questions of the form “What is x?”. My focus will be on cases where x stands for a strongly social kind, such as marriage. Such a position is offered as an alternative to the idea-sometimes called conceptual engineering-according to which we should evaluate and, eventually, seek to improve our concepts. After introducing the idea of erotetic amelioration, (...) I will show how it can be put into work to deal with what I call the topic preservation challenge, and what advantages it has in relation to a similar position available in the literature, namely, Cappelen’s (2018) Austerity Framework. (shrink)

It is widely believed by philosophers that we human beings are capable of stepping back from inclinations to act in a certain way and consider whether we should do so. If we judge that there are enough reasons in favour of following our initial inclination, we are definitely motivated, and, if all goes well, we act. This view of human agency naturally leads to the idea that our actions are self-determined, or controlled by ourselves. Some go one step further to (...) the point of saying that we should extend the fundamental aspects of this view of human agency to the epistemic realm. This we call ‘the control-view”. Here we will make a strong case against the control-view. While we have a substantial control over our practical lives, it is very unlikely that this extends to our epistemic lives. Our discussion will proceed in three stages. We will present two asymmetries between our practical and epistemic lives which are followed by a general argument against the control-view. (shrink)

El uso de sistemas de machine learning en los procesos de selección laboral ha sido de gran utilidad para agilizarlos y volverlos más eficientes, pero al mismo tiempo ha generado problemas en términos de equidad, confiabilidad y transparencia. En este artículo comenzamos explicando los diferentes usos de la Inteligencia Artificial en los procesos de selección laboral en Estados Unidos. Presentamos los sesgos sexuales y raciales que han sido detectados en algunos de ellos y explicamos los obstáculos jurídicos y prácticos para (...) su detección y análisis. Un posible remedio jurídico a la discriminación algorítmica es el régimen de impacto diferencial sistémico utilizado en Estados Unidos. Usamos algunas características de este régimen para señalar los vacíos jurídicos frente a la discriminación en el acceso al empleo en el ámbito del derecho laboral colombiano, y ofrecemos algunas características generales que podría tener un régimen de esa naturaleza. (shrink)

This article argues that Robert Alexy's influential theory of balancing is affected by a contradiction that makes it unfeasible as an instrument by which to explain some aspects of law and legal reasoning it aims to clarify. In particular, I will show that one of the premises of Alexy's theory of balancing is incompatible with its conclusion. Alexy's theory is based upon a sharp distinction between rules and principles. However, as my analysis will demonstrate, its conclusion implies that it is (...) impossible to distinguish between rules and principles. This is because the so‐called weight formula and the law of colliding principles (i.e., the two main notions used by Alexy to explain balancing) cancel out any difference between these two types of norms. (shrink)

In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towards addressing ethics at the societal level. In this article, we propose a tripartite framework to overcome these (...) difficulties. Our framework analytically decomposes an ethics module into three dimensions. First, there is the ethical dimension, which pertains to the learning goals. Second, there is the moral dimension, which addresses the moral relevance of engineers’ conduct. Finally, there is the political dimension, which scales up issues of moral relevance at the civic level. All in all, our framework has two advantages. First, it provides analytic clarity, i.e. it enables course instructors to locate ethical dilemmas in either the moral or political realm and to make use of the tools and resources from moral and/or political philosophy. Second, it depicts a comprehensive ethical training, which enables students to both reason about moral issues in the abstract, and to socially contextualize potential solutions. (shrink)

Moore’s Paradox is a test case for any formal theory of belief. In Knowledge and Belief, Hintikka developed a multimodal logic for statements that express sentences containing the epistemic notions of knowledge and belief. His account purports to offer an explanation of the paradox. In this paper I argue that Hintikka’s interpretation of one of the doxastic operators is philosophically problematic and leads to an unnecessarily strong logical system. I offer a weaker alternative that captures in a more accurate way (...) our logical intuitions about the notion of belief without sacrificing the possibility of providing an explanation for problematic cases such as Moore’s Paradox. (shrink)

We claim that in contemporary studies in molecular biology and biomedicine, the nature of ‘manipulation’ and ‘intervention’ has changed. Traditionally, molecular biology and molecular studies in medicine are considered experimental sciences, whereas experiments take the form of material manipulation and intervention. On the contrary “big science” projects in biology focus on the practice of data mining of biological databases. We argue that the practice of data mining is a form of intervention although it does not require material manipulation. We also (...) suggest that material manipulation, although still present in in the practice of data mining, fulfill a different epistemic role. (shrink)

This paper raises three questions regarding the attribution of beliefs, desires, and intentions to robots. The first one is whether humans in fact engage in robot mindreading. If they do, this raises a second question: does robot mindreading foster trust towards robots? Both of these questions are empirical, and I show that the available evidence is insufficient to answer them. Now, if we assume that the answer to both questions is affirmative, a third and more important question arises: should developers (...) and engineers promote robot mindreading in view of their stated goal of enhancing transparency? My worry here is that by attempting to make robots more mind-readable, they are abandoning the project of understanding automatic decision processes. Features that enhance mind-readability are prone to make the factors that determine automatic decisions even more opaque than they already are. And current strategies to eliminate opacity do not enhance mind-readability. The last part of the paper discusses different ways to analyze this apparent trade-off and suggests that a possible solution must adopt tolerable degrees of opacity that depend on pragmatic factors connected to the level of trust required for the intended uses of the robot. (shrink)

Le génie de Blaise Pascal séduit toujours de nombreux chercheurs. Des âmes avides d'absolu font de ses écrits leur livre de chevet. Sans doute cette notoriété a-t-elle estompé les autres membres de cette famille somme toute remarquable. Etienne, le père, est un esprit universel. Juriste, délégué de la cité, il est aussi grand mathématicien, compositeur et organiste, religieux et père admirable. Gilberte, la sœur aînée, a un talent littéraire qui s'exprimera dans La vie de M. Pascal. Les dons poétiques de (...) Jacqueline, la cadette, étonnent dès l'enfance. Etienne, le neveu, écrira un précieux témoignage sur la méthode de son oncle. Marguerite, la nièce miraculée, vivra jusqu'à quatre-vingt-sept ans et rapportera ses souvenirs dans un livre sur Blaise. Leurs lettres, peu nombreuses et trop souvent ignorées, méritent une attention d'autant plus minutieuse qu'elles nous introduisent dans l'intimité de cette famille. Ce qui domine, c'est une union exceptionnelle qui survit au-delà de la mort après avoir traversé les heurts inévitables entre ces fortes personnalités. On s'émerveille de la diversité des vocations : chaste veuvage pour Etienne, maternité et vie de famille pour Gilberte, vie religieuse pour Jacqueline, consécration à Dieu dans le monde pour Blaise, ministère presbytéral pour Louis. André Bord nous raconte cette vie de famille étonnante en nous faisant découvrir plusieurs faits inédits. (shrink)

Assurément, la lecture d'Origène par Erasme est d'abord un plaisir du texte. L'étude d'André Goin en éclaire les prolongements historico- théologiques. Erasme s'est d'abord employé à délivrer Origène de la "caverne des ombres" d'où de nombreux humanistes, dont Pic de la Mirandole, n'avaient pu le tirer. Avec son génie propre, et alliant l'audace calculée et l'enthousiasme sincère pour la spiritualité origienne, Erasme fait une exégèse subtile fondée sur un réemploi, massif et sélectif, de l'énorme matériau emprunté à Origène, une (...) tentative de dépassement des problèmes posés par l'orthodoxie d'Origène, et enfin, s'impose comme traducteur et éditeur d'Origène. (shrink)