Should decision-making algorithms be held to higher standards of transparency than human beings? The way we answer this question directly impacts what we demand from explainable algorithms, how we govern them via regulatory proposals, and how explainable algorithms may help resolve the social problems associated with decision making supported by artificial intelligence. Some argue that algorithms and humans should be held to the same standards of transparency and that a double standard of transparency is hardly justified. We give two arguments (...) to the contrary and specify two kinds of situations for which higher standards of transparency are required from algorithmic decisions as compared to humans. Our arguments have direct implications on the demands from explainable algorithms in decision-making contexts such as automated transportation. (shrink)

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of the (...) no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

Building on an illustrative case of a systemic environmental threat and its multi‐stakeholder response, this paper draws attention to the changing political impacts of corporations in the digital age. Political Corporate Social Responsibility (PCSR) theory suggests an expanded sense of politics and corporations, including impacts that may range from voluntary initiatives to overcome governance gaps, to avoiding state regulation via corporate political activity. Considering digitalization as a stimulus, we explore potential responsibilities of corporations toward public goods in contexts with functioning (...) governments. We show that digitalization—in the form of transparency, surveillance, and data‐sharing—offers corporations’ scope for deliberative public participation. The starry sky beetle infestation endangering public and private goods is thereby used to illustrate the possibility of expanding the political role of corporations in the digital sphere. We offer a contribution by conceptualizing data‐deliberation as a Habermasian variation of PCSR, defined as the (a) voluntary disclosure of corporate data and its transparent, open sharing with the public sector (b) along with the cooperation with governmental institutions on data analytics methods for examining large‐scale datasets (c) thereby complying with existing national and international regulations on data protection, in particular with respect to privacy and personal data. (shrink)

There are two possible realist defense strategies against the pessimistic meta-induction and Laudan’s meta-modus tollens: the selective strategy, claiming that discarded theories are partially true, and the discontinuity strategy, denying that pessimism about past theories can be extended to current ones. A radical version of discontinuity realism is proposed by Gerald Doppelt: rather than discriminating between true and false components within theories, he holds that superseded theories cannot be shown to be even partially true, while present best theories are demonstrably (...) completely true. I argue that this position, running counter both the cumulativity of science and fallibilism, is untenable; it cannot account for the success of past theories, nor for the failures of current theories, and rather than shutting the door to the pessimistic historical objections it opens it wide. The best strategy, instead, joins the selective idea there was both some truth and some falsity in discarded theories, like in current ones, with the moderate discontinuity idea that the truth rate in present best theories is much greater than in past ones. (shrink)

We propose a semantics for a connexive conditional based on the Lewis-Stalnaker conditional. It is a connexive semantics that is both classical and intuitive.

Deployment Realism resists Laudan’s and Lyons’ objections to the “No Miracle Argument” by arguing that a hypothesis is most probably true when it is deployed essentially in a novel prediction. However, Lyons criticized Psillos’ criterion of essentiality, maintaining that Deployment Realism should be committed to all the actually deployed assumptions. But since many actually deployed assumptions proved false, he concludes that the No Miracle Argument and Deployment Realism fail. I reply that the essentiality condition is required by Occam’s razor. In (...) fact, there is a simpler formulation of essentiality which escapes Lyons’ criticisms and rescues the No Miracle Argument and Deployment Realism from their purported historical counterexamples: a hypothesis is essential when it has no proper parts (in Yablo’s sense) sufficient to derive the same prediction. Although essentiality so conceived cannot be detected prospectively, this is just natural, and it is not a problem but an advantage for Deployment Realism. (shrink)

We put forth an account for when to believe causal and evidential conditionals. The basic idea is to embed a causal model in an agent’s belief state. For the evaluation of conditionals seems to be relative to beliefs about both particular facts and causal relations. Unlike other attempts using causal models, we show that ours can account rather well not only for various causal but also evidential conditionals.

During the course of life, it is common to make some decisions that prove to be correct. Some of these choices are made without a specific reason, but only out of habit or intuitively, while others are based on judgments and motivations. However, when we claim that a decision is “right”, what kind of judgment are we referring to? On the one hand, the term “right” (or “wrong”) often refers to abstract norms. Usually, truth and falsehood serve as criteria in (...) these cases. In such situations, judgments about what is “right” or “wrong” depend strictly on an accurate rational evaluation, which is instrumental in guiding individuals to undertake or avoid certain actions. On the other hand, there is a sense of justice that concerns ethics and values. In these circumstances, a decision is generally considered “right” if it is based on a criterion of judgment that allows individuals to make a decision freely, without being bound by an abstract norm, but rather by elaborating the choice as the realization of what they consider good and just. In this paper will examine and redefine the concept of “right choice”, acknowledging the above mentioned dual nature of its meaning. It will be argued there is a link between what abstract norms dictate to do, in order to reach a formally correct decision, and what, instead, depends on merely reasons and attitudes. This connection is indeed ensured by wise decisions. (shrink)

Here we prove the existence of sheaf cohomology theory in arbitrary o-minimal structures.

We propose a method of learning indicative conditional information. An agent learns conditional information by Jeffrey imaging on the minimally informative proposition expressed by a Stalnaker conditional. We show that the predictions of the proposed method align with the intuitions in Douven, 239–263 2012)’s benchmark examples. Jeffrey imaging on Stalnaker conditionals can also capture the learning of uncertain conditional information, which we illustrate by generating predictions for the Judy Benjamin Problem.

This book presents a philosophical interpretation to numerical cognition based on dual process theories and heuristics. It shows how investigations in cognitive science can shed light on issues traditionally raised by philosophers of mathematics. The analysis will also help readers to better understand the relationship between current neuroscientific research and the philosophical reflection on mathematics. The author seeks to explain the acquisition of mathematical concepts. To accomplish this, he needs to answer two questions. How can the concepts of approximate numerosity (...) become an object of thought that is so accessible to our consciousness? How are these concepts refined and specified in such a way as to become numbers? Unfortunately, there is currently no model that can truly demonstrate the role of language in the development of numerical skills starting from approximate pre-verbal skills. However, the author details a solution to this problem: dual process theories. It is an approach widely used by theorists focusing on reasoning, decision making, social cognition, and consciousness. Here, he applies this approach to the studies on mathematical knowledge. He details the results brought about by psychological and neuroscientific studies conducted on numerical cognition by key neuroscientists. In the process, he develops the foundations of a new, potential philosophical explanation on mathematical knowledge. (shrink)

Criticisms à la Laudan can block the “no miracles” argument for the (approximate) truth of whole theories. Realists have thus retrenched, arguing that at least the individual claims deployed in the derivation of novel predictions should be considered (approximately) true. But for Lyons (2002) there are historical counterexamples even to this weaker “deployment” realism: he lists a number of novel predictions supposedly derived from (radically) false claims. But if so, those successes would seem unexplainable, even by Lyons’ “modest surrealism” or (...) other surrogates to realism. In fact, I argue, some of those predictions were an easy guess, or independently probable in the light of available evidence; hence, they are no counterexamples to deployment realism, for the no miracles argument wouldn’t apply to them. In other instances, pace Lyon, the prediction was actually false, and could be reinterpreted as true only by interpreting as true also the claim from which it was derived; or again, a false claim was employed in the derivation of a true prediction, but inessentially, the essential role being played by a weaker true claim. But as soon as the paradoxical air of such historical cases is explained away in any of these manners, they cease to represent counterexamples to deployment realism. If, as I suggest, all of them can be dealt with by these strategies, a theoretical claim can still be assumed to be true if it is crucial in deriving an improbable novel prediction. (shrink)

One of the open questions in Bayesian epistemology is how to rationally learn from indicative conditionals (Douven, 2016). Eva et al. (Mind 129(514):461–508, 2020) propose a strategy to resolve this question. They claim that their strategy provides a “uniquely rational response to any given learning scenario”. We show that their updating strategy is neither very general nor always rational. Even worse, we generalize their strategy and show that it still fails. Bad news for the Bayesians.

In this paper, we analyze the legal situation regarding physician-assisted suicide in the world. Our hypothesis is that the prohibitive stance on physician-assisted suicide in most societies in the world today seems to be related to our moral attitudes toward suicide. This brings us to a discussion about life itself. We claim that the total lack of legal protection for physician-assisted suicide from international organizations and most countries in the world lies in a philosophical assumption that supports much of our (...) common beliefs about what life really is. This assumption states that life must be thought of as not belonging exclusively to the individual. We argue that this assumption is a misconception that can be heard in the debate on suicide. Consequently we endorse a different conception of life which tends to favor a pro-choice stance towards suicide and assisted death in general. This position takes the patient’s decision about when to die more seriously. We conclude that there is no reason why physician-assisted suicide does not deserve legal protection as an individual right to die under international law. (shrink)

Gerald Doppelt claims that Deployment Realism cannot withstand the antirealist objections based on the “pessimistic meta-induction” and Laudan’s historical counterexamples. Moreover it is incomplete, as it purports to explain the predictive success of theories, but overlooks the necessity to explain also their explanatory success. Accordingly, he proposes a new version of realism, presented as the best explanation of both predictive and explanatory success, and committed only to the truth of best current theories, not of the discarded ones. Elsewhere I criticized (...) his new brand of realism. Here instead I argue that Doppelt has not shown that Deployment Realism cannot solve the problems raised by the history of science, explaining explanatory success does not add much to explaining novel predictive success, and Doppelt is right that truth is not a sufficient explanans, but for different reasons, and this does not refute Deployment Realism, but helps to detail it better. In a more explicit formulation, the realist IBE concludes not only to the truth of theories, but also to the reliability of scientists and scientific method, the order and simplicity of nature, and the approximate truth of background theories. (shrink)

In this paper, we put forth an analysis of sensitivity which aims to discern individual from merely statistical evidence. We argue that sensitivity is not to be understood as a factive concept, but as a purely epistemic one. Our resulting analysis of epistemic sensitivity gives rise to an account of legal proof on which a defendant is only found liable based on epistemically sensitive evidence.

Many formulations of scientific realism (SR) include some commitment to metaphysical realism (MR). On the other hand, authors like Schlick, Carnap and Putnam held forms of scientific realism coupled with metaphysical antirealism (and this has analogies in Kant). So we might ask: do scientific realists really need MR? or is MR already implied by SR, so that SR is actually incompatible with metaphysical antirealism? And if MR must really be added to SR, why is that so? And which additional arguments (...) scientific realists need to support it? After reviewing and classifying a number of different kinds of realisms, metaphysical and not, I answer that SR and MR are logically independent of each other, so that there is no logical inconsistency in holding SR while rejecting MR. However, I argue that the “no miracle” argument (NMA) not only is the “ultimate” argument for SR, but by the same token it also supports MR. Therefore one cannot effectively defend SR without also subscribing to MR, but this can be done at no additional argumentative cost. I show this by discussing not only the standard version of the NMA, but also three more versions which are not usually considered as such in the literature. (shrink)

O objectivo deste artigo é apresentar um conjunto de reflexões sobre o imaginário literário de Hidácio, bispo de Chaves, na conjuntura política da província hispânica da Galécia, durante o século V.

An epistemological analysis of the decision, this book includes a critical analysis through the continuous reference to an interdisciplinary approach including a synthesis of philosophical approaches, biology and neuroscience.

Standard economic theory usually analyzes the decisions made by individuals as a rational process in which each individual has sound and consistent preferences and makes decisions according to the principle of subjective expected utility maximization. Starting from the pioneering work of Herbert Simon and the research of cognitive psychologists Kahneman and Tversky, the contributions provided by cognitive-behavioral theory have repeatedly shown that real agents make choices in a way that differs systematically from standard theory, hence highlighting its limits. Rather than (...) considering standard normative theory as false or unable to explain the data obtained by behavioral economists, several economists decided to develop new formal models that could include the results of different experiments and empirical observations that captured all dimensions of the choice made by an individual. In this sense, they proposed new models that were not intended to challenge standard theory but rather designed to provide a kind of psychological expansion to it. This article has the aim of describing and analyzing the advantages and limitations of these new models, which unfortunately are not always suited to describe the individual behavior, the individuals’ actions, or the equilibria due to the combination of the actions of several players. To overcome the limits of these models, we decided to take into consideration the unfortunately unfinished work of Michael Bacharach, who strived to understand the individual and collective forms of rationality without applying only analytical devices or a theoretical vision of the world but bringing rationality back to the perception level of the agents. (shrink)

THE TWEET OF THE UNIVERSE. GRAVITATIONAL WAVES BETWEEN THEORY, EFFORTS AND MISTAKES The recent discovery of gravitational waves fills a substantial gap in the theory of general relativity, since these waves were the only phenomenon predicted by Einstein’s theory that had not yet been directly observed. This was mainly due to the fact that the passage of waves is an elusive phenomenon, almost imperceptible, up to the point that even Einstein thought that it was almost impossible to detect it using (...) “traditional” tools. This paper will explore the efforts made over the years to detect the passage of these waves, the mistakes made, and the recent results obtained through the use of the twin optical interferometers LIGO and VIRGO. This extraordinary discovery shows one more time that the history of science is full of trials, errors and sudden steps forward maybe due to the use of new technology. (shrink)

Neuroeconomics is a science pledged to tracing the neurobiological correlates involved in decision-making, especially in the case of economic decisions. Despite representing a recent research field that is still identifying its research objects, tools and methods, its epistemological scope and scientific relevance have already been openly questioned by several authors. Among these critics, the most influential names in the debate have been those of Faruk Gul and Wolfgang Pesendorfer, who claim that the data on neural activity cannot find place in (...) economic models, which should on the contrary be solely based on the data produced by choices. This paper aims at countering the gloomy and unsubstantiated claims of these two authors and those who believe that neuroscience cannot provide new and useful insights to the established knowledge of standard economics. The main point stressed here is that this perception is the product of a general misunderstanding of the advances made by neuroscience, which are incidentally of crucial importance. (shrink)

The article describes several representations of Alexander the Great which were current in medieval Arabic learned circles and proposes some ideas on the genesis of these representations in the Greek and Syriac civilizations: 1) Alexander as moralist; 2) Alexander as a mystical philosopher who knew the mysterious links governing the cosmos; 3) Alexander as a monotheist philosopher who was charged with responsibility for the d; 4) Alexander as a cunning politician.

The currently most plausible version of scientific realism is probably “deployment” realism, based on various contributions in the recent literature, and worked out as a unitary account in Psillos. According to it we can believe in the at least partial truth of theories, because that is the best explanation of their predictive success, and discarded theories which had novel predictive success had nonetheless some true parts, those necessary to derive their novel predictions. According to Doppelt this account cannot withstand the (...) antirealist objections based on the “pessimistic meta-induction” and Laudan’s historical counterexamples. Moreover it is incomplete, as it purports to explain the predictive success of theories, but overlooks the necessity to explain also their explanatory success. Accordingly, he proposes a new version of realism, presented as the best explanation of both predictive and explanatory success, and committed only to the truth of best current theories, not of the discarded ones. Here I argue that Doppelt has not shown that deployment realism as it stands cannot solve the problems raised by the history of science, explaining explanatory success does not add much to explaining novel predictive success, and a realism confined to current theories is implausible, and actually the easiest prey to the pessimistic meta-induction argument. (shrink)

I argue that the understanding's spontaneity is only manifest in its purely logical use.