Eleonora Cresto

We take up the challenge of developing an international network with capacity to survey the world’s scientists on an ongoing basis, providing rich datasets regarding the opinions of scientists and scientific sub-communities, both at a time and also over time. The novel methodology employed sees local coordinators, at each institution in the network, sending survey invitation emails internally to scientists at their home institution. The emails link to a ‘10 second survey’, where the participant is presented with a single statement to consider, and a standard five-point Likert scale. In June 2023, a group of 30 philosophers and social scientists invited 20,085 scientists across 30 institutions in 12 countries to participate, gathering 6,807 responses to the statement Science has put it beyond reasonable doubt that COVID-19 is caused by a virus. The study demonstrates that it is possible to establish a global network to quickly ascertain scientific opinion on a large international scale, with high response rate, low opt-out rate, and in a way that allows for significant (perhaps indefinite) repeatability. Measuring scientific opinion in this new way would be a valuable complement to currently available approaches, potentially informing policy decisions and public understanding across diverse fields.

Higher-order likes and desires sometimes lead agents to have ungrounded or paradoxical preferences. This situation is particularly problematic in the context of games. If payoffs are interdependent, the overall assessment of particular courses of action becomes ungrounded; in such cases, the game’s matrix is radically underdetermined. Paradigmatic examples of this phenomenon occur when players are ‘perfect lovers’ or ‘perfect haters’, in a sense to be explained. In this paper, I use a dynamic doxastic logic to mimic the search for a suitable matrix. Upgrades are triggered by conjectures about other players’ utilities, which can, in turn, be based on behavioural or verbal cues. We can prove that, under certain conditions, pairs of agents with paradoxical preferences eventually come to believe they cannot interact in a game. As a result, I hope to provide a better understanding of game-theoretic ungroundedness and, more generally, of the structure of higher-order preferences and desires.

Este trabajo examina el concepto de conocimiento grupal. Por un lado, se observa que a menudo nos vemos compelidos a atribuir a los agentes grupales actitudes epistémicas que difieren de las de sus miembros individuales; por otro lado, también notamos que los agentes idealmente responsables están sometidos a una “presión deflacionaria” para anclar tales actitudes en individuos concretos. En vistas de ello, argumento que los grupos epistémicamente esponsables deben concebirse como entidades dinámicas; de anera correlativa, el conocimiento grupal puede definirse en érminos de una familia de posibles rutas entre el onocimiento distribuido y el conocimiento común del grupo. Muestro ntonces que las Lógicas de Anuncios Públicos pueden usarse en este contexto como herramientas adecuadas para monitorear la satisfacción de requerimientos normativos por parte de individuos epistémicamente responsables.

In this paper I present a model of rational belief change, and I show how to use it to obtain a better insight into the debate about the nature of pneumococcal transformation, genes and DNA that took place in the forties, as a result of Oswald T. Avery’s work. The model offers a particular elaboration of the concept of inference to the best explanation, along decision theoretic lines. Within this framework, I distinguish different senses in which Avery’s team can be said to have proceeded with caution, thus throwing some light upon a persistent source of disagreement among researchers in the history of genetics. In addition, I explain why we are entitled to say that rival parties such as physicist Maclyn McCarty and biochemist Alfred Mirsky were epistemically rational, in spite of the fact that they reached different conclusions on the basis of the same evidence.

En este trabajo argumento a favor de la idea de que una explicación científica es una respuesta a una pregunta, aunque no necesariamente a una pregunta-por-qué. Esto no quiere decir que las preguntas-por-qué no sean elementos fundamentales de toda investigación científica: su importancia radica en que son capaces de organizar y sistematizar un conjunto dado de creencias. Para justificar esta afirmación, comienzo por identificar tres estadios básicos en los cuales pueden surgir preguntas-por-qué, y luego procedo a caracterizar su estructura. Muestro finalmente cómo usar este análisis para elucidar la noción de poder de unificación de hipótesis rivales. Entiendo que esta última noción, a su vez, constituye uno de los criterios que debemos considerar a la hora de evaluar cuál de dichas hipótesis rivales es la mejor explicación disponible, comparativamente hablando. In this paper I take scientific explanations to be answers to questions, though not necessarily to why-questions. This, however, is not meant to imply that why-questions are not fundamental in their own peculiar way. As I understand it, why-questions are crucial elements in any research process because they are able to organize and systematize an agent's belief set. In order to justify my claim I start by identifying three basic stages in which whyquestions can arise, and then I proceed to characterize their structure. I also show how to use this analysis to elucidate the notion of comparative unification power of rival hypotheses. The notion of comparative unification power, in turn, can be thought of as one of the criteria that we should take into account at the time of assessing which of such rival hypotheses is the best explanation available, comparatively speaking.

I discuss the epistemic status of algorithmic predictions in the legal realm. My main claim is that algorithmic predictions do not give us knowledge, not even probabilistic knowledge. The situation, however, is relevantly different from the one in which we find ourselves at the time of assessing statistical evidence in general, and it is rather related to the fact that algorithmic fairness in legal contexts is essentially undetermined. In the light of this, we have to settle for justified beliefs and justified credences. I end by drawing some morals for the Knowledge Norm of action.

I explore a game-theoretic analysis of social interactions in which each agent’s well-being depends crucially on the well-being of another agent. As a result of this, payoffs are interdependent and cannot be fixed, and hence the overall assessment of strategies becomes ungrounded. A paradigmatic example of this general phenomenon occurs when both players are ‘reflective altruists’, in a sense to be explained. I argue that ungroundedness cannot be captured by standard games with incomplete information, but that it requires the concept of an underspecified game; underspecified games have radically underdetermined matrices. Players locked in ungroundedness will be assumed to engage simultaneously in an implicit second-order game in which they try to coordinate their first-order matrices. If they fail to coordinate, their first-order interaction cannot be recast as a game in the first place.

In a recent paper Samir Okasha has suggested an application of Arrow’s impossibility theorem to theory choice. When epistemic virtues are interpreted as ‘voters’ in charge of ranking competing theories, and there are more than two theories at stake, the final ordering is bound to coincide with the one proposed by one of the voters, provided a number of seemingly reasonable conditions are in place. In a similar spirit, Jacob Stegenga has shown that Arrow’s theorem applies to the amalgamation of evidence; the ‘voters’ here are the different sources of evidence. As with Okasha’s proposal, it is not clear how to avoid Arrow’s pessimistic conclusion.In this paper we develop a novel argument that purports to show that, in typical examples, Arrow’s result does not obtain when dealing with evidence amalgamation. The reason is that we cannot escape the well-known Duhem problem: the evidence actually confirms complex conjunctions that include various auxiliary hypotheses. We argue that confirmational holism induces us to restrict the domain of a reasonable amalgamation function, thus violating one of Arrow’s conditions. The upshot is that we are now able to see the Duhem problem under a different, positive light – namely, as a phenomenon that makes the aggregation of the evidence possible in the first place, when there are at least three options on the table.

The paper suggests a way of modeling belief changes within the tradition of formal belief revision theories. The present model extends the scope of traditional proposals, such as AGM, so as to take care of “structural belief changes” – a type of radical shifts that is best illustrated with, but not limited to, instances of scientific discovery; we obtain AGM expansions and contractions as limiting cases. The representation strategy relies on a non-standard use of a semantic machinery. More precisely, the model seeks to correlate knowledge states with interpretations of a given formal language L, in such a way that the epistemic state of an agent at a given time gives rise to a picture of how things could be, if there weren’t anything else to know. Interpretations of L proceed along supervaluational ideas; hence, the model as a whole can be seen as a particular application of supervaluational semantics to epistemic matters.