We ask how to use machine learning to expand observability, which presently depends on human learning that informs conceivability. The issue is engaged by considering the question of correspondence between conceived observability counterfactuals and observable, yet so far unobserved or unconceived, states of affairs. A possible answer lies in importing out of reference frame content which could provide means for conceiving further observability counterfactuals. They allow us to define high-fidelity observability, increasing the level of correspondence in question. To achieve high-fidelity (...) observability, we propose to use generative machine learning models as the providers of the out of reference frame content. From an applied point of view, such a role of generative machine learning models shows an emerging dimension of human-machine cooperation. (shrink)

Mặc dù 3 điểm nêu trên chưa phải đã đủ, nhưng chắc chắn không thể giải đáp. Vì vậy, khó mà tin vài lập luận đơn giản về “tính khả thi” lại có thể mang ra áp dụng cho cộng đồng trên không gian sinh thái rộng lớn.

Building on past constructive criticism, the present study provides further methodological development focused on the elimination of bias that may occur during first-person observation. First, various sources of errors that may accompany introspection are distinguished based on previous critical literature. Four main errors are classified, namely attentional, attributional, conceptual, and expressional error. Furthermore, methodological recommendations for the possible elimination of these errors have been determined based on the analysis and focused excerpting of introspective scientific literature. The following groups of methodological (...) recommendations were determined: 1) a better focusing of the subject’s attention to their mental processes, 2) providing suitable stimuli, and 3) the sharing of introspective experience between subjects. Furthermore, the potential of adjustments in introspective research designs for eliminating attentional, attributional, conceptual, and expressional error is discussed. (shrink)

As our epistemic ambitions grow, the common and scientific endeavours are becoming increasingly dependent on Machine Learning (ML). The field rests on a single experimental paradigm, which consists of splitting the available data into a training and testing set and using the latter to measure how well the trained ML model generalises to unseen samples. If the model reaches acceptable accuracy, an a posteriori contract comes into effect between humans and the model, supposedly allowing its deployment to target environments. Yet (...) the latter part of the contract depends on human inductive predictions or generalisations, which infer a uniformity between the trained ML model and the targets. The paper asks how we justify the contract between human and machine learning. It is argued that the justification becomes a pressing issue when we use ML to reach ‘elsewheres’ in space and time or deploy ML models in non-benign environments. The paper argues that the only viable version of the contract can be based on optimality (instead of on reliability which cannot be justified without circularity) and aligns this position with Schurz’s optimality justification. It is shown that when dealing with inaccessible/unstable ground-truths (‘elsewheres’ and non-benign targets), the optimality justification undergoes a slight change, which should reflect critically on our epistemic ambitions. Therefore, the study of ML robustness should involve not only heuristics that lead to acceptable accuracies on testing sets. The justification of human inductive predictions or generalisations about the uniformity between ML models and targets should be included as well. Without it, the assumptions about inductive risk minimisation in ML are not addressed in full. (shrink)

Consider a set of shuffled observations drawn from a fixed probability distribution over some instance domain. What enables learning of inductive generalizations which proceed from such a set of observations? The scenario is worthwhile because it epistemically characterizes most of machine learning. This kind of learning from observations is also inverse and ill-posed. What reduces the non-uniqueness of its result and, thus, its problematic epistemic justification, which stems from a one-to-many relation between the observations and many learnable generalizations? The paper (...) argues that this role belongs to any complexity regularization which satisfies Norton’s Material Theory of Induction (MTI) by localizing the inductive risk to facts in the given domain. A prime example of the localization is the Lottery Ticket Hypothesis (LTH) about overparameterized neural networks. The explanation of MTI’s role in complexity regularization of neural networks is provided by analyzing the stability of Empirical Risk Minimization (ERM), an inductive rule that controls the learning process and leads to an inductive generalization on the given set of observations. In cases where ERM might become asymptotically unstable, making the justification of the generalization by uniform convergence unavailable, LTH and MTI can be used to define a local stability. A priori, overparameterized neural networks are such cases and the combination of LTH and MTI can block ERM’s trivialization caused by equalizing the strengths of its inductive support for risk minimization. We bring closer the investigation of generalization in artificial neural networks and the study of inductive inference and show the division of labor between MTI and the optimality justifications (developed by Gerhard Schurz) in machine learning. (shrink)

The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence for (...) unconceived alternatives providing modal knowledge of what is possible therein. As a result, the epistemic warrant of synthesised realist theories should emerge bolstered as the underdetermination by available evidence gets reduced. While shifting the realist commitment away from theoretical artefacts towards modalities of the possibility spaces, the synthesis comes out as a kind of perspectival modelling. (shrink)

Procedural justifications of democracy emphasize inclusiveness and respect and by doing so come into conflict with instrumental justifications that depend on voters’ competence. This conflict raises questions about jury theorems and makes their standing in democratic theory contested. We show that a type of no-regret learning called meta-induction can help to satisfy the competence assumption without excluding voters or diverse opinion leaders on an a priori basis. Meta-induction assigns weights to opinion leaders based on their past predictive performance to determine (...) the level of their inclusion in recommendations for voters. The weighting minimizes the difference between the performance of meta-induction and the best opinion leader in hindsight. The difference represents the regret of meta-induction whose minimization ensures that the recommendations are optimal in supporting voters’ competence. Meta-induction has optimal truth-tracking properties that support voters’ competence even if it is targeted by mis/disinformation and should be considered a tool for supporting democracy in hyper-plurality. (shrink)

Despite an increasing role of machine learning in science, there is a lack of results on limits of empirical exploration aided by machine learning. In this paper, we construct one such limit by proving undecidability of learnability of state spaces of physical systems. We characterize state spaces as binary hypothesis classes of the computable Probably Approximately Correct learning framework. This leads to identifying the first limit for learnability of state spaces in the agnostic setting. Further, using the fact that finiteness (...) of the combinatorial dimension of hypothesis classes is undecidable, we derive undecidability for learnability of state spaces as well. Throughout the paper, we try to connect our formal results with modern neural networks. This allows us to bring the limits close to the current practice and make a first step in connecting scientific exploration aided by machine learning with results from learning theory. (shrink)

The environmental costs and energy constraints have become emerging issues for the future development of Machine Learning (ML) and Artificial Intelligence (AI). So far, the discussion on environmental impacts of ML/AI lacks a perspective reaching beyond quantitative measurements of the energy-related research costs. Building on the foundations laid down by Schwartz et al., 2019 in the GreenAI initiative, our argument considers two interlinked phenomena, the gratuitous generalisation capability and the future where ML/AI performs the majority of quantifiable inductive inferences. The (...) gratuitous generalisation capability refers to a discrepancy between the cognitive demands of a task to be accomplished and the performance (accuracy) of a used ML/AI model. If the latter exceeds the former because the model was optimised to achieve the best possible accuracy, it becomes inefficient and its operation harmful to the environment. The future dominated by the non-anthropic induction describes a use of ML/AI so all-pervasive that most of the inductive inferences become furnished by ML/AI generalisations. The paper argues that the present debate deserves an expansion connecting the environmental costs of research and ineffective ML/AI uses (the issue of gratuitous generalisation capability) with the (near) future marked by the all-pervasive Human-Artificial Intelligence Nexus. (shrink)

Spirituality and spiritual well-being are connected with many areas of human life. Thus, especially in secular countries, there is a need for reliable validated instruments for measuring spirituality. The Spiritual Well-Being Scale is among the world’s most often used tools; therefore, the aim of this study was its psychometrical evaluation in the secular environment of the Czech Republic on a nationally representative sample (n = 1797, mean age: 45.9 ± 17.67; 48.6% men). A non-parametric comparison of different sociodemographic groups showed (...) a higher disposition for experiencing spirituality among women, older people, and divorced persons. Based on confirmatory factor analysis, negatively worded items were excluded using a polychoric correlation matrix. The new version of the scale consisting of 11 items had good internal consistency (Cronbach’s α = 0.85; McDonald’s ωt = 0.91). The two-factor model of this shortened version, with factors corresponding to the Religious and the Existential subscales of the Spiritual Well-Being Scale, shows a satisfactory fit with the data, where the loadings of all items ranged from medium to high. Thus, this study offered a new version of the tool, convenient for measuring spiritual well-being in secular conditions. (shrink)

Vít Gvoždiak published a reconciliatory analysis of Searle’s social ontology with semiotics in Gvoždiak (2012). Without prior knowledge of his paper, an analysis of the same subject appeared in Msimang (2014). Even though Searle’s social ontology is a common point of reference in the formulation of semiotics in these papers, it also serves as a point of departure in their understanding of semiotics and its development. The semiotic theory expressed in Gvoždiak (2012) is an inherently linguistic (speech act centred) theory, (...) whereas the semiotic theory presented in Msimang (2014) tends more towards a general theory of communicative systems in which social ontology, which follows from speech act theory, is an interesting part. It is my purpose in this note to contrast the two positions of semiotic theory as they appear in the aforementioned papers in reference to their appropriation of Searle’s social ontology. (shrink)

Quand nous lisons un livre passionnant, quand nous passons une bonne soirée avec des amis ou quand nous dégustons des mets raffinés, nous nous trouvons parfois dans un état de plaisir. La notion de plaisir traverse de nombreux champs de recherche en philosophie. Une question centrale reste sans doute celle de sa nature : qu’est-ce donc que le plaisir ? Pour y répondre, une comparaison avec d'autres entités mentales plus familières se révèle fructueuse, et permet de mettre à jour ses (...) spécificités propres. La définition du plaisir doit rendre compte de sa diversité, puisque le plaisir semble toujours se présenter sous des formes multiples : qu'y a-t-il de commun parmi toutes les instances de plaisir ? Par ailleurs, le plaisir semble souvent avoir un objet, ce qui soulève une série de questions : Quel type de chose peut être un objet du plaisir ? Dans quelle mesure l'objet du plaisir constitue-t-il le plaisir lui-même ? Plus généralement, quelle est la nature du lien entre le plaisir et son objet ? Ces questions seront abordées dans la Section 1. Au-delà de ces questions définitionnelles, des questions plus spécifiques se posent concernant la manière dont on peut rendre compte du plaisir dans une optique naturaliste : dans quelle mesure le plaisir est-il une entité qui s’intègre dans une image unifiée du monde dans lequel on vit ? Puisqu'il est généralement entendu que la science manifeste cette ambition unificatrice, comment peut-on rendre compte du plaisir de manière scientifique ? La Section 2 est dédiée à ces questions. Une des principales difficultés rencontrées est que le plaisir ne semble pas neutre. Il paraît plutôt avoir une valeur affective positive, dans un sens qui reste bien sûr à éclaircir. Cette valeur se manifeste d'abord dans le fait que le plaisir est susceptible d'orienter nos actions et réactions : nous sommes typiquement attirés par le plaisir, de la même manière que nous cherchons à éviter la souffrance. C'est l'aspect motivationnel du plaisir. La valeur affective du plaisir semble cependant aller au-delà de son rôle motivationnel, pour donner lieu à des caractéristiques normatives. Non seulement le plaisir motive certaines actions, mais il les justifierait aussi, en fournissant des raisons d'agir qui semblent valides. Plus encore, le plaisir semble bon pour nous, ou nous faire du bien. Il semble donc avoir une valeur prudentielle, en ce qu'il contribuerait à rendre notre vie meilleure. Cela pourrait alors justifier son intégration dans le domaine de la morale. Ces considérations seront l’objet de la Section 3. (shrink)

L’humanité est devenue facteur d’évolution au niveau planétaire. En complexifiant toujours plus les modalités de ses relations avec l’environnement, elle pense trouver dans la science l’outil principal de son développement et en définitive de sa survie. La science, en effet, est un système d’acquisition de connaissances qui génère une interprétation systématique et rationnelle du monde naturel ethumain, jamais définitive et en renouvellement continu. En tant qu’explication rationnelle des phénomènes naturels et sociaux, elle nous permet de raffiner sans cesse la compréhension (...) de notre place et notre rôle dans le monde. Au vu des enjeux inhérents à l’exploitation des acquis scientifiques et de leurs conséquences sur la vie des populations humaines et sur les équilibres biosphériques, continuer à imaginer que les scientifiques vivent isolés dans une sorte de tour d’ivoire de la connaissance, éloignée de l’agitationde la πόλις, signifie ignorer que la responsabilité sociale est consubstantielle à l’activité de la science. Un scientifique ne vit pas dans un vacuum social, il est porteur de valeurs sociales dans la sphère scientifique. En même temps, il véhicule dans la sphère sociale des valeurs qui découlent de son activité. Si, d’une part, son rôle est celui de développer des connaissances qui soient à la fin du processus d’enquête scientifique exemptes de la marque de la subjectivité, d’autre part, pendant ce processus les valeurs s’affrontent en laissant le dernier mot aux tests expérimentaux et observationnels propres à la méthode scientifique. En dernière analyse, ce sera la réalité phénoménologique qui tranchera vis-à-vis des multiples modèles et constructions épistémiques, plus ou moins imprégnés de valeurs, soumis par l’ensemble de la communauté scientifique. La Conférence générale de l’Organisation des Nations-Unies pour l’éducation, la science et la culture (UNESCO), réunie à Paris en 1974, a adopté la Recommandation concernant la condition des chercheurs scientifiques, où ont été définis normes et principes pouvant servir de guide pour optimiser l’activité de recherche et les conditions de sa mise en place. Au vu de la complexité toujours croissante des relations entre la science et la société, la Commission nationale française pour l’UNESCO (CNFU) a été consultée sur la mise à jour de la Recommandation en focalisant son attention sur la question de la responsabilité morale des scientifiques dans l’exercice de leur profession. (shrink)

Caste : Groupe qui se distingue par ses privilèges et son esprit d’exclusive à l’égard de toute personne qui n’appartient pas au groupe. Larousse -/- La hausse des prix des carburants proposée pour lutter contre le changement climatique et mettre en œuvre les principes de la « transition écologique » adoptés par la France lors de la COP21, a fait naître le mouvement des gilets jaunes. Plus globalement c’est une bonne partie des français qui se trouve concernée, celle qui vit (...) dans des zones excentrées et qui ne bénéficie pas d'un réseau de transports très efficient tel celui qui émaille par exemple le territoire parisien. Ainsi, augmenter les prix des carburants, en particulier le diesel, a été perçu comme un contresens économique anti-populaire. Pendant des en, les producteurs d’automobiles, avec le support des politiques publiques, ont présenté le diesel comme le carburant le moins polluant. Mais aujourd’hui devenu le carburant « satanique », les consommateurs qui l’ont choisi, en toute bonne conscience, se sentent manipulés. La reconversion vers l’achat d’une voiture électrique est hors de la portée de la plupart de ceux qui aujourd’hui manifestent. Les aides du gouvernement ne changent pas cette réalité socioéconomique. Sous quel angle, les média ont-ils restitué le mouvement des gilets jaunes ? Alors qu’on voit émerger au sein de ce mouvement des revendications pour plus de justice sociale, qu’en est-il de la justice environnementale ? Peut-on dire qu’il s’agit d’une révolte sociale anti-écologique ? Ou autrement dit, les gilets jaunes sont-ils un mouvement anti-écologique ? (shrink)

La précarité fait référence à l'existence de la rareté. Judith Butler montre l'impossibilité d'être un à travers le concept hégélien du sujet heureux. Le sujet ainsi défini est projeté sur l'Autre – langage, normes sociales, regard extérieur –, ce qui conduit à un état de vulnérabilité : je dépends de ce que je ne serai pas. Cependant, l'impuissance, loin d'être parfaite, peut se transformer en puissance sans s'affranchir des frontières qui la définissent, si elle défie les illusions modernes de la (...) sensualité et permet la présence et l'origine de la coexistence. De même, loin d'être la fin de l'éthique, celle-ci est différente pour chaque acteur du monde dans lequel il vit. (shrink)