Preface This book is about semantics and logic. More specifically, it is about the semantics and logic of natural language; and, even more specifically than ...

This paper proposes a method for computing the temporal aspects of the interpretations of a variety of Germa sentences. The method is strictly modular in the sense that it allows each meaning-bearing sentence constituent to make its own, separate, contribution to the semantic representation of any sentence containing it. The semantic representation of a sentence is reached in several stages. First, an ‘initial semantic representation’ is constructed, using a syntactic analysis of the sentence as input. This initial representation is then (...) transformed into the definitive representation by a series of transformations which reflect the ways in which the contributions from different constituents of the sentence interact. Since the different constituents which make their respective contributions to the meaning of the sentence are in most instances ambiguous, the initial representations are typically of a high degree of underspecification. (shrink)

This paper presents a sound and complete proof system for the first order fragment of Discourse Representation Theory. Since the inferences that human language users draw from the verbal input they receive for the most transcend the capacities of such a system, it can be no more than a basis on which more powerful systems, which are capable of producing those inferences, may then be built. Nevertheless, even within the general setting of first order logic the structure of the formulas (...) of DRS-languages, i.e. of the Discourse Representation Structures suggest for the components of such a system inference rules that differ somewhat from those usually found in proof systems for the first order predicate calculus and which are, we believe, more in keeping with inference patterns that are actually employed in common sense reasoning.This is why we have decided to publish the present exercise, in spite of the fact that it is not one for which a great deal of originality could be claimed. In fact, it could be argued that the problem addressed in this paper was solved when Gödel first established the completeness of the system of Principia Mathematica for first order logic. For the DRS-languages we consider here are straightforwardly intertranslatable with standard formulations of the predicate calculus; in fact the translations are so straightforward that any sound and complete proof system for first order logic can be used as a sound and complete proof system for DRSs: simply translate the DRSs into formulas of predicate logic and then proceed as usual. As a matter of fact, this is how one has chosen to proceed in some implementations of DRT, which involve inferencing as well as semantic representation; an example is the Lex system developed jointly by IBM and the University of Tübingen ). (shrink)

This is a review of From Discourse to Logic: Introduction to Modeltheoretic Semantics of Natural Language, Formal Logic and Discourse Representation Theory, written by Hans Kamp and Uwe Reyle and published by Kluwer Academic Publishers in 1993.

abstract Can torture be morally justified? I shall criticise arguments that have been adduced against torture and demonstrate that torture can be justified more easily than most philosophers dealing with the question are prepared to admit. It can be justified not only in ticking nuclear bomb cases but also in less spectacular ticking bomb cases and even in the so‐called Dirty Harry cases. There is no morally relevant difference between self‐defensive killing of a culpable aggressor and torturing someone who is (...) culpable of a deadly threat that can be averted only by torturing him. Nevertheless, I shall argue that torture should not be institutionalised, for example by torture warrants. (shrink)

Confirmation bias is one of the most widely discussed epistemically problematic cognitions, challenging reliable belief formation and the correction of inaccurate views. Given its problematic nature, it remains unclear why the bias evolved and is still with us today. To offer an explanation, several philosophers and scientists have argued that the bias is in fact adaptive. I critically discuss three recent proposals of this kind before developing a novel alternative, what I call the ‘reality-matching account’. According to the account, confirmation (...) bias evolved because it helps us influence people and social structures so that they come to match our beliefs about them. This can result in significant developmental and epistemic benefits for us and other people, ensuring that over time we don’t become epistemically disconnected from social reality but can navigate it more easily. While that might not be the only evolved function of confirmation bias, it is an important one that has so far been neglected in the theorizing on the bias. (shrink)

When scientists or science reporters communicate research results to the public, this often involves ethical and epistemic risks. One such risk arises when scientific claims cause cognitive or behavioural changes in the audience that contribute to the self-fulfilment of these claims. I argue that the ethical and epistemic problems that such self-fulfilment effects may pose are much broader and more common than hitherto appreciated. Moreover, these problems are often due to a specific psychological phenomenon that has been neglected in the (...) research on science communication: many people tend to conform to ‘descriptive norms’, that is, norms capturing (perceptions of) what others commonly do, think, or feel. Because of this tendency, science communication may frequently produce significant social harm. I contend that scientists have a responsibility to assess the risk of this potential harm and consider adopting strategies to mitigate it. I introduce one such strategy and argue that its implementation is independently well motivated by the fact that it helps improve scientific accuracy. (shrink)

Some artificial intelligence systems can display algorithmic bias, i.e. they may produce outputs that unfairly discriminate against people based on their social identity. Much research on this topic focuses on algorithmic bias that disadvantages people based on their gender or racial identity. The related ethical problems are significant and well known. Algorithmic bias against other aspects of people’s social identity, for instance, their political orientation, remains largely unexplored. This paper argues that algorithmic bias against people’s political orientation can arise in (...) some of the same ways in which algorithmic gender and racial biases emerge. However, it differs importantly from them because there are strong social norms against gender and racial biases. This does not hold to the same extent for political biases. Political biases can thus more powerfully influence people, which increases the chances that these biases become embedded in algorithms and makes algorithmic political biases harder to detect and eradicate than gender and racial biases even though they all can produce similar harm. Since some algorithms can now also easily identify people’s political orientations against their will, these problems are exacerbated. Algorithmic political bias thus raises substantial and distinctive risks that the AI community should be aware of and examine. (shrink)

I argue that the often-heard claim that all serious present-day political philosophers subscribe to the principle of equal respect and concern or to the doctrine of equal moral status or are in some other fundamental sense egalitarians is wrong. Also wrong is the further claim that the usual methods currently used in political philosophy presuppose basic equality. I further argue that liberal egalitarianism itself is wrong. There is no universal duty “of equal respect and concern” towards every person, for one (...) does not owe one’s nice sister and a serial rapist equal respect and concern. There is also no duty of the state to respect all citizens equally, for a state need not be equally concerned about murderous criminals on the one hand and their innocent victims on the other. The potential maneuver of saving liberal egalitarianism by claiming that people have equal rights is unsuccessful. Human beings clearly do not have equal rights, nor are they born with equal rights; and merely having an equality of some rights, for example of “basic” or human ones, would not suffice for egalitarianism. Appeals to “recognition respect” and related concepts are also to no avail. Trying to go back still a step further and to claim that certain rights inequalities or justified discriminatory rules are themselves “grounded” in equal respect and concern at some deeper, norm-generating level (like, for example, the original position or a discourse-ethical principle of justification) is also futile. Finally, I argue that the “This is not what we mean”-strategy of escaping the above arguments reduces egalitarianism to triviality and empty rhetoric. Liberal egalitarianism should be abandoned. (shrink)

Scientists may sometimes generalize from their samples to broader populations when they have not yet sufficiently supported this generalization. Do such hasty generalizations also occur in experimental philosophy? To check, we analyzed 171 experimental philosophy studies published between 2017 and 2023. We found that most studies tested only Western populations but generalized beyond them without justification. There was also no evidence that studies with broader conclusions had larger, more diverse samples, but they nonetheless had higher citation impact. Our analyses reveal (...) important methodological limitations of many experimental philosophy studies and suggest that philosophical training may not protect against hasty generalizations. (shrink)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, overgeneralized (...) conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science. (shrink)

Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. Here, I contend that this argument (...) overlooks that human decision-making is sometimes significantly more transparent and trustworthy than algorithmic decision-making. This is because when people explain their decisions by giving reasons for them, this frequently prompts those giving the reasons to govern or regulate themselves so as to think and act in ways that confirm their reason reports. AI explanation systems lack this self-regulative feature. Overlooking it when comparing algorithmic and human decision-making can result in underestimations of the transparency of human decision-making and in the development of explainable AI that may mislead people by activating generally warranted beliefs about the regulative dimension of reason-giving. (shrink)

Members of the field of philosophy have, just as other people, political convictions or, as psychologists call them, ideologies. How are different ideologies distributed and perceived in the field? Using the familiar distinction between the political left and right, we surveyed an international sample of 794 subjects in philosophy. We found that survey participants clearly leaned left (75%), while right-leaning individuals (14%) and moderates (11%) were underrepresented. Moreover, and strikingly, across the political spectrum, from very left-leaning individuals and moderates to (...) very right-leaning individuals, participants reported experiencing ideological hostility in the field, occasionally even from those from their own side of the political spectrum. Finally, while about half of the subjects believed that discrimination against left- or right-leaning individuals in the field is not justified, a significant minority displayed an explicit willingness to discriminate against colleagues with the opposite ideology. Our findings are both surprising and important, because a commitment to tolerance and equality is widespread in philosophy, and there is reason to think that ideological similarity, hostility, and discrimination undermine reliable belief formation in many areas of the discipline. (shrink)

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group level even when they (...) negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

Answer-set programming (ASP) has emerged as a declarative programming paradigm where problems are encoded as logic programs, such that the so-called answer sets of theses programs represent the solutions of the encoded problem. The efficiency of the latest ASP solvers reached a state that makes them applicable for problems of practical importance. Consequently, problems from many different areas, including diagnosis, data integration, and graph theory, have been successfully tackled via ASP. In this work, we present such ASP-encodings for problems associated (...) to abstract argumentation frameworks (AFs) and generalisations thereof. Our encodings are formulated as fixed queries, such that the input is the only part depending on the actual AF to process. We illustrate the functioning of this approach, which is underlying a new argumentation system called ASPARTIX in detail and show its adequacy in terms of computational complexity. (shrink)

Many ethical frameworks require artificial intelligence (AI) systems to be explainable. Explainable AI (XAI) models are frequently tested for their adequacy in user studies. Since different people may have different explanatory needs, it is important that participant samples in user studies are large enough to represent the target population to enable generalizations. However, it is unclear to what extent XAI researchers reflect on and justify their sample sizes or avoid broad generalizations across people. We analyzed XAI user studies (N = (...) 220) published between 2012 and 2022. Most studies did not offer rationales for their sample sizes. Moreover, most papers generalized their conclusions beyond their target population, and there was no evidence that broader conclusions in quantitative studies were correlated with larger samples. These methodological problems can impede evaluations of whether XAI systems implement the explainability called for in ethical frameworks. We outline principles for more inclusive XAI user studies. (shrink)

It has been argued that implicit biases are operative in philosophy and lead to significant epistemic costs in the field. Philosophers working on this issue have focussed mainly on implicit gender and race biases. They have overlooked ideological bias, which targets political orientations. Psychologists have found ideological bias in their field and have argued that it has negative epistemic effects on scientific research. I relate this debate to the field of philosophy and argue that if, as some studies suggest, the (...) same bias also exists in philosophy then it will lead to hitherto unrecognised epistemic hazards in the field. Furthermore, the bias is epistemically different from the more familiar biases in respects that are important for epistemology, ethics, and metaphilosophy. (shrink)

Throughout the post-World War II decades, the United States has wrestled in its own unique style with a problem that is shared by all modern societies: how to achieve a reasonably equitable distribution of health care, without losing control of total spending on health care, and without suffocating the delivery system with controls and regulations that inhibit technical progress.Because an equitable distribution of health care inevitably requires at least some government regulation, and because government regulations tend to impose rigidity on (...) any system, it is widely believed in the United States that a trade-off actually exists between fairness in the distribution of care and the health system’s ability to innovate. This troublesome trade-off bedevils American policy makers to this day. (shrink)

Throughout the post-World War II decades, the United States has wrestled in its own unique style with a problem that is shared by all modern societies: how to achieve a reasonably equitable distribution of health care, without losing control of total spending on health care, and without suffocating the delivery system with controls and regulations that inhibit technical progress.Because an equitable distribution of health care inevitably requires at least some government regulation, and because government regulations tend to impose rigidity on (...) any system, it is widely believed in the United States that a trade-off actually exists between fairness in the distribution of care and the health system’s ability to innovate. This troublesome trade-off bedevils American policy makers to this day. (shrink)

Why do we engage in folk psychology, that is, why do we think about and ascribe propositional attitudes such as beliefs, desires, intentions etc. to people? On the standard view, folk psychology is primarily for mindreading, for detecting mental states and explaining and/or predicting people’s behaviour in terms of them. In contrast, McGeer (1996, 2007, 2015), and Zawidzki (2008, 2013) maintain that folk psychology is not primarily for mindreading but for mindshaping, that is, for moulding people’s behavior and minds (e.g., (...) via the imposition of social norms) so that coordination becomes easier. Mindreading is derived from and only as effective as it is because of mindshaping, not vice versa. I critically assess McGeer’s, and Zawidzki’s proposal and contend that three common motivations for the mindshaping view do not provide sufficient support for their particular version of it. I argue furthermore that their proposal underestimates the role that epistemic processing plays for mindshaping. And I provide reasons for favouring an alternative according to which, in social cognition involving ascriptions of propositional attitudes, neither mindshaping nor mindreading is primary but both are complementary in that effective mindshaping depends as much on mindreading as effective mindreading depends on mindshaping. (shrink)

Demographic diversity might often be present in a group without group members noticing it. What are the epistemic effects if they do? Several philosophers and social scientists have recently argued that when individuals detect demographic diversity in their group, this can result in epistemic benefits even if that diversity doesn’t involve cognitive differences. Here I critically discuss research advocating this proposal, introduce a distinction between two types of detection of demographic diversity, and apply this distinction to the theorizing on diversity (...) in science. Focusing on ‘invisible’ diversity, I argue that in one common kind of group in science, if group members have full insight into their group’s diversity, this is likely to create epistemic costs. These costs can be avoided and epistemic benefits gained if group members only partly detect their group’s diversity. There is thus an epistemic reason for context-dependent limitations on scientists’ insight into the diversity of their group. (shrink)

For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations and that (...) many popular XAI designs implicitly and problematically assume that Western explanatory needs are shared cross-culturally. Additionally, we systematically reviewed over 200 XAI user studies and found that most studies did not consider relevant cultural variations, sampled only Western populations, but drew conclusions about human-XAI interactions more generally. We also analyzed over 30 literature reviews of XAI studies. Most reviews did not mention cultural differences in explanatory needs or flag overly broad cross-cultural extrapolations of XAI user study results. Combined, our analyses provide evidence of a cultural bias toward Western populations in XAI research, highlighting an important knowledge gap regarding how culturally diverse users may respond to widely used XAI systems that future work can and should address. (shrink)

Arguing against the doctrine of double effect, Bennett claims that the terror bomber only intends to make his victims appear dead. An obvious reply is that he intends to make them appear dead by killing them. I argue that the alleged refutations of this reply rest on a mistaken test question to determine what an agent intends, as Bennett's own test question confirms, and that Bennett is misled by confusing metaphorical death and literal death. Moreover, Bennett's argument is half-hearted anyway, (...) and going the whole way would not only undermine the DDE but also Quinn's revision of it. (shrink)

It is well known that on the Internet, computer algorithms track our website browsing, clicks, and search history to infer our preferences, interests, and goals. The nature of this algorithmic tracking remains unclear, however. Does it involve what many cognitive scientists and philosophers call ‘mindreading’, i.e., an epistemic capacity to attribute mental states to people to predict, explain, or influence their actions? Here I argue that it does. This is because humans are in a particular way embedded in the process (...) of algorithmic tracking. Specifically, if we endorse common conditions for extended cognition, then human mindreading (by website operators and users) is often literally extended into, that is, partly realized by, not merely causally coupled to, computer systems performing algorithmic tracking. The view that human mindreading extends outside the body into computers in this way has significant ethical advantages. It points to new conceptual ways to reclaim our autonomy and privacy in the face of increasing risks of computational control and online manipulation. These benefits speak in favor of endorsing the notion of extended mindreading. (shrink)

The paper presents a new version of the "Cosmological Argument" – considered to be an ontological argument, since it exclusively uses ontological concepts and principles. It employs famous results of modern physics, and distinguishes between event-causation and agent-causation. Due to these features, the argument manages to avoid the objection of infinite regress. It remains true, however, that the conclusion of the argument is too unspecific to be unambiguously considered an argument for the existence of God.

In this paper, we compare several cut-free sequent systems for propositional intuitionistic logic Intwith respect to polynomial simulations. Such calculi can be divided into two classes, namely single-succedent calculi (like Gentzen's LJ) and multi-succedent calculi. We show that the latter allow for more compact proofs than the former. Moreover, for some classes of formulae, the same is true if proofs in single-succedent calculi are directed acyclic graphs (dags) instead of trees. Additionally, we investigate the effect of weakening rules on the (...) structure and length of dag proofs.The second topic of this paper is the effect of different embeddings from Int to S4. We select two different embeddings from the literature and show that translated (propositional) intuitionistic formulae have sometimes exponentially shorter minimal proofs in a cut-free Gentzen system for S4than the original formula in a cut-free single-succedent Gentzen system for Int. Moreover, the length and the structure of proofs of translated formulae crucially depend on the chosen embedding. (shrink)

In this paper, we consider three different search strategies for a cut-free sequent system formalizing orthologic, and estimate the respective search spaces. Applying backward search, there are classes of formulae for which both the minimal proof length and the search space are exponential. In a combined forward and backward approach, all proofs are polynomial, but the potential search space remains exponential. Using a forward strategy, the potential search space becomes polynomial yielding a polynomial decision procedure for orthologic and the word (...) problem for free ortholattices. (shrink)

The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range (...) of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors. (shrink)