Andrés Páez

Cada día es más evidente que existen muchas formas sutiles de exclusión y parcialidad que afectan el correcto funcionamiento de los sistemas jurídicos. El concepto de injusticia epistémica, introducido por la filósofa Miranda Fricker, ofrece una herramienta conceptual útil para comprender estas formas de exclusión y parcialidad judicial que a menudo pasan desapercibidas. En este artículo presentamos la teoría original de Fricker y algunas de las aplicaciones del concepto de injusticia epistémica en los procesos jurídicos. En particular, queremos demostrar que la semilla sembrada por Fricker ha generado un floreciente campo de estudio en el cual el concepto se utiliza para analizar muchos fenómenos diferentes en el ámbito jurídico, no siempre siguiendo la caracterización original proporcionada por ella. Esto ha llevado a una distinción entre lo que llamaremos la versión estrecha del concepto, que se acerca a la descripción original de Fricker, y la versión más amplia de injusticia epistémica, que es una noción más controvertida porque existe el riesgo de que se confunda con otros conceptos más conocidos como el sexismo, la discriminación racial, la opresión, el silenciamiento y el gaslighting. Mostraremos que el valor de la versión estrecha es principalmente teórico y que para utilizar el concepto de injusticia epistémica se debe adoptar una comprensión más liberal del mismo.

In this paper I critically examine the notion of explanation used in Artificial Intelligence in general, and in the theory of belief revision in particular. I focus on two of the best known accounts in the literature: Pagnucco’s abductive expansion functions and Gärdenfors’ counterfactual analysis. I argue that both accounts are at odds with the way in which this notion has historically been understood in philosophy. They are also at odds with the explanatory strategies used in actual scientific practice. At the end of the paper I outline the desiderata for an epistemologically motivated, scientifically informed belief revision model for explanation.

In a recent paper, Erasmus et al. (2021) defend the idea that the ambiguity of the term “explanation” in explainable AI (XAI) can be solved by adopting any of four different extant accounts of explanation in the philosophy of science: the Deductive Nomological, Inductive Statistical, Causal Mechanical, and New Mechanist models. In this chapter, I show that the authors’ claim that these accounts can be applied to deep neural networks as they would to any natural phenomenon is mistaken. I also provide a more general argument as to why the notion of explainability as it is currently used in the XAI literature bears little resemblance to the traditional concept of scientific explanation. It would be more fruitful to use the label “understandable AI” to avoid the confusion that surrounds the goal and purposes of XAI. In the second half of the chapter, I argue for a pragmatic conception of understanding that is better suited to play the central role attributed to explanation in XAI. Following De Regt (2017) and Kuorikoski and Ylikoski (2015), the conditions of satisfaction for understanding an ML system are fleshed out in terms of an agent’s success in using the system.

Introducción a la lógica moderna es un libro de texto dedicado al estudio de la lógica simbólica elemental. No presupone familiaridad alguna con la lógica, las matemáticas o la filosofía, y se ha hecho un esfuerzo deliberado por adaptarlo a los intereses de estudiantes provenientes de las más diversas disciplinas. Al mismo tiempo, los conceptos centrales son expuestos de una manera precisa y rigurosa, sin ocultar los detalles y problemas técnicos y filosóficos que hacen de la lógica un área de estudio interesante en sí misma. El libro está dividido en tres partes. La primera se ocupa de la lógica proposicional, la segunda de la lógica de primer orden y la tercera de la lógica modal proposicional. Los tres temas se estudian semánticamente utilizando árboles de verdad, y sintácticamente a través de sistemas de deducción natural. Al final de cada sección hay numerosos ejercicios de práctica, la mitad de los cuales son resueltos en el apéndice. El texto está diseñado para un curso de un año de duración y permite gran flexibilidad en el diseño del mismo.

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature.

In many contexts, such as business, science and law, it is essential to determine whether a company, a product or a person in fact has the reputation attributed to it, regardless of whether that reputation has been rightly earned. In this paper I offer two necessary and jointly sufficient conditions for the attribution of a reputation to a subject within a social group. The first one concerns the way in which reputational information is spread among the members of the relevant social group; the second is the existence, in most members of the group, of a disposition to interpret and evaluate a reputational object in a manner molded by reputational information. Reputational claims generate expectations that are tested every time a member of the group comes in contact with the reputational object. In many cases, the preferential search for behavioral evidence consistent with those expectations will result in a distorted evaluation of the reputational object.

Explanation and understanding are intimately connected notions, but the nature of that connection has generally not been considered a topic worthy of serious philosophical investigation. Most authors have avoided making reference to the notion of understanding in their accounts of explanation because they fear that any mention of the epistemic states of the individuals involved compromises the objectivity of explanation. Understanding is a pragmatic notion, they argue, and pragmatics should be kept at a safe distance from the universal features of explanation. My main contention in this dissertation is that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize this notion it is necessary to formulate an account of objective explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. ;My account of explanation is based on the belief-doubt model of inquiry first proposed by Peirce. Using the tools provided by decision theory, and the models of belief revision developed by Isaac Levi and by Alchourron, Gardenfors, and Makinson, I analyze the objective and pragmatic conditions that a piece of information must fulfill to be both explanatory and epistemically useful to an inquiring agent. The objective basis for an explanation is provided by the relation of probabilistic relevance that the fact described by the explanans bares to the fact described by the explanandum. But an explanation is much more than its foundation. As an epistemological notion, a potential explanation can only be a bona fide explanation if it becomes part of inquiry, that is, if an agent or a group of agents can see any value in it for their cognitive purposes. I provide a way to evaluate an explanation in terms of its credibility, its content, and its explanatory value. I argue that although an objective measure of the credibility and content of an explanation can be established, in many cases a complete determination of its explanatory value will ultimately depend on the interests and goals of the individual inquirers

There are several approaches to the way in which standards of proof in law should be understood. In the central article in this issue, Rodrigo Coloma suggests that they should be conceived either as thresholds either as prototypes. He also offers a taxonomy of the different uses of standards of proof, which transcends their function as error distributors. In their comments on the paper, Raymundo Gama and Claudio Agüero clarify and challenge this way of understanding standards of proof. Some of their criticisms are right on target, but many others are directed more at Coloma’s theoretical presuppositions than at his substantial contributions. In this paper I offer a wider context to evaluate their disagreements.

El concepto de reputación ocupa un lugar central en muchas esferas de la vida humana, incluyendo el derecho, pero no existen muchos análisis filosóficos del mismo. En este ensayo presento un análisis de la reputación desde la perspectiva de la epistemología social, en particular, haciendo uso de las teorías contemporáneas sobre actitudes epistémicas grupales. El ensayo comienza examinando las interpretaciones del concepto de reputación que se encuentran en la literatura jurídica. En particular, examino el bien conocido análisis del concepto que hace Post (1986) en el contexto de la ley de difamación. A partir de la tercera sección presento el análisis epistemológico y establezco una distinción entre reputación objetiva y subjetiva, una distinción que es fácilmente identificable en la práctica. Mi interés principal reside en el concepto de reputación subjetiva, que es el que presenta el mayor desafío conceptual desde el punto de vista epistemológico. En la sección 4 emprendo la tarea de determinar si podemos entender la reputación subjetiva como un tipo de creencia grupal. Tras rechazar esta posibilidad, en la sección final ofrezco una manera diferente de entender este concepto y examino sus implicaciones para el derecho.