Probabilistic causation

In this paper we will proceed in the following way: firstly we will give In this paper we will proceed in the following way: firstly we will give a brief reminder of the main tenets of the philosophical program connected to strong probabilistic causation; then we will recall some of the principal problems that the mathematization of probability-based causal theories have tried to solve in the last two decades (with a certain degree of success, which explains the two different incipit quoted above). Eventually we will discuss the connection between kinds of probabilities and kinds of probabilistic causations, an issue that has a strong impact on the problem of determinism

Metaphors we lie by: our ‘war’against COVID-19

In this paper, we discuss the influence of war as a metaphor in the context of the COVID-19 pandemic. After an introduction to the traditional analysis of the war metaphor, we address the social consequences of using this metaphor, a topic that has been widely debated with regard to public communication in the context of COVID-19. We pay particular attention to a theory that many intellectuals have raised: the possibility that the use of the metaphor in this context is harmful to a democratic society because it may lead citizens to accept limited civil liberties and authoritarian policies. After presenting the extensive literature on the use of the war metaphor before and during the COVID-19 pandemic, in the final section of the paper, we analyse experimental evidence of the effects of this metaphor. In the conclusion, we hint at open questions and suggest that the current evidence does not support claims of direct liberticidal influence

Cause, scienza e senso comune

I metodi di inferenza causale utilizzati in ambito scientifico \u2013 in particolare nell\u2019ambito delle scienze mediche e sociali, utilizzano nozioni di causazione generica, vale a dire relative a popolazioni. Nel campo della causazione generica, dunque, gran parte del lavoro teorico svolto dai filosofi della scienza e dai filosofici analitici negli ultimi trent\u2019anni, ha trovato stimoli, applicazioni, banchi di prova in ambito scientifico, fino a consolidare un\u2019area di ricerca interdisciplinare. Sul fronte della causazione singolare, tuttavia, le cose stanno diversamente: il \u2018controllo\u2019 delle teorie di volta in volta proposte \ue8 affidato all\u2019intuizione, e al verdetto del senso comune. Tuattavia anche la nozione di causazione singolare ha rilevanza scientifica, in particolare in quei casi nei quali \ue8 richiesto un tipo di ragionamento diagnostico. Questo lavoro si propone di analizzare il ricorso al senso comune nella valutazione critica delle teorie della causazione singolare e di indagare l\u2019effettiva portata delle apparenti differenze metodologiche tra riflessione sulla causazione singolare e riflessione sulla causazione generale

defining metabolic syndrome which kind of causality if any is required

Abstract The definition of metabolic syndrome (MetS) has been, and still is, extremely controversial. My purpose is not to give a solution to the associated debate but to argue that the controversy is at least partially due to the different 'causal content' of the various definitions: their theoretical validity and practical utility can be evaluated by reconstructing or making explicit the underlying causal structure. I will therefore propose to distinguish the alternative definitions according to the kinds of causal content they carry: (1) definitions grounded on associations, (2) definitions presupposing a causal model built upon statistical associations, and (3) definitions grounded on underlying mechanisms. I suggest that analysing definitions according to their causal content can be helpful in evaluating alternative definitions of some diseases. I want to show how the controversy over MetS suggests a distinction among three kinds of definitions based on how explicitly they characterise the syndrome in causal terms, and on the type of causality involved. I will call 'type 1 definitions' those definitions that are purely associative; 'type 2 definitions' the definitions based on statistical associations, plus generic medical and causal knowledge; and 'type 3 definitions' the definitions based on (hypotheses about) mechanisms. These kinds of definitions, although different, can be related to each other. A definition with more specific causal content may be useful in the evaluation of definitions characterised by a lower degree of causal specificity. Moreover, the identification of the type of causality involved is of help to constitute a good criterion for choosing among different definitions of a pathological entity. In section (1) I introduce the controversy about MetS, in section (2) I propose some remarks about medical definitions and their 'causal import', and in section (3) I suggest that the different attitudes towards the definition of MetS are relevant to evaluate their explicative power

Introduction: COVID-19 Models and the Difficult Balance between Methods and Values

The COVID-19 pandemic had an unprecedented impact not only on the socio-economic and political conditions worldwide but also on the practices of the scientific community and on the public image of science itself. The scientific community suddenly found itself in the spotlight and was pressured to rapidly produce evidence applicable to the management of the present health crisis. This in turn had some unexpected consequences, among which an increase of the publication speed and sometimes a decrease of the quality of peer review (see e.g., Chan 2020). At the same time, the public discussion of scientific issues related to COVID-19 among an audience often lacking the appropriate knowledge of the characteristics of modern science (e.g., critical reasoning, hypothetical nature of research, the role of uncertainty, \u2026 ), was associated with the emergence of extreme stances in the population

Un probabilista neoclassico: F. P. Cantelli

For some decades F. P. Cantelli (1875\u20131966) was one of the most prominent Italian contributors to the mathematical theory of probability. Although his name is frequently connected with the name of E. Borel, Cantelli's approach to probability is very different from that of Borel. This paper looks at F. P. Cantelli's contributions to the development of the calculus of probability during the years of the earlier axiomatic formulations, with particular emphasis on Cantelli's point of view on the foundations of probability. After a brief biographical sketch, I emphasize the relation between Cantelli's papers of the years 1916\u20131917 and the debate among some Italian mathematicians about the possibility of defining probability in terms of relative frequencies. Some of the most important mathematical results are recalled and related to other researches on the calculus of probability during the period 1920\u20131930. Cantelli's conception of the foundations of probability is analyzed and compared with that of R. von Mises, as presented in 1936 during a debate published in the Giornale dell'Istituto Italiano degli Attuari

Il ragionamento in condizioni di incertezza

Il termine \u2018incertezza\u2019 assume diversi significati a seconda del contesto scientifico in cui ricorre. Questo saggio si concentra sui diversi modi di concepire e formalizzare il ragionamento con premesse incomplete, vaghe approssimative o tali per cui il legame tra premesse e conclusioni \ue8 pi\uf9 debole che nella logica classica. La maggior parte dei metodi qui trattati trova origine, o ha raggiunto piena valorizzazione, a partire dalla ricerca degli anni \u201980 in intelligenza artificiale (IA). Il dibattito sul ragionamento incerto ha coinvolto sin dagli inizi contributi provenienti non solo dalla logica e dall\u2019informatica, ma anche dalla filosofia, dalla matematica e dalla psicologia, e si \ue8 esteso ad altri settori, quali quello dell\u2019argomentazione giuridica o della diagnosi medica, provvedendo una adeguata cassetta degli attrezzi per i diversi contesti di applicazione. Negli ultimi decenni l\u2019espressione \u2018intelligenza artificiale\u2019 ha aumentato il proprio carico di ambiguit\ue0, dato che viene utilizzata, specialmente dai media, come sinonimo di machine learning, e/o di Big Data. Esplorare le conseguenze della \u2018nuova\u2019 IA sulla nozione generale di incertezza richiederebbe un contributo a parte. Se qui ci concentriamo sugli approcci \u2018classici\u2019 \ue8 perch\ue9: a) non pensiamo che siano obsoleti: di fatto sono tuttora in uso e si rivelano utili anche per capire che cosa sia realmente la \u2018nuova\u2019 IA; b) hanno contribuito a chiarire, o a vedere da nuove prospettive, concetti che in precedenza erano spesso assimilati tra loro - come vaghezza, incertezza, probabilit\ue0, imprecisione, approssimazione, default,\u2026, prestandosi a un proficuo scambio di idee tra informatici, logici e filosofi