Suhrllekah. Festgabe für Helmut Eimer. Edited by Michael Hahn, Jens-Uwe Hartmann and Roland Steiner. Indica et Tibetica Verlag, Swisttal-Odendorf 1996. xxii, 282 pp. DM48. ISBN 3-923776-28-4.

Studien zur Indologie und Buddhismuskunde: Festgabe des Seminars für Indologie und Buddhismuskunde für Professor Dr. Heinz Bechert. Herausgegeben von Reinhold Grüendahl, Jens-Uwe Hartman, Petra Kieffer-Pülz. Indica et Tibetica Verlag, Bonn 1993. 326 pp., 1 photograph, 4 tables. DM 64.00.

Vividharatnakarandaka. Festgabe für Adelheid Mette. Edited by Christine Chojnacki, Jens-Uwe Hartmann and Volker M. Tschannerl. Indica et Tibetica Verlag, Swisttal-Odendorf 2000. 540 pp. DM 128. ISBN 3-923776-37-3.

Drawing together the ideas, practices, and techniques associated with the subject, this book puts them in historical context and demonstrates their relevance to ...

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (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)

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)

The Oxford Handbook of Carl Schmitt collects thirty original chapters on the diverse oeuvre of one of the most controversial thinkers of the twentieth century. Carl Schmitt was a German theorist whose anti-liberalism continues to inspire scholars and practitioners on both the Left and the Right. Despite Schmitt's rabid anti-semitism and partisan legal practice in Nazi Germany, the appeal of his trenchant critiques of, among other things, aestheticism, representative democracy, and international law as well as of his theoretical justifications of (...) dictatorship and rule by exception is undiminished. Uniquely located at the intersection of law, the social sciences, and the humanities, this volume brings together sophisticated yet accessible interpretations of Schmitt's sprawling thought and complicated biography. The contributors hail from diverse disciplines, including art, law, literature, philosophy, political science, and history. In addition to opening up exciting new avenues of research, The Oxford Handbook of Carl Schmitt provides the intellectual foundations for an improved understanding of the political, legal, and cultural thought of this most infamous of German theorists. A substantial introduction places the trinity of Schmitt's thought in a broad context. (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)

The traditional Lewis–Stalnaker semantics treats all counterfactuals with an impossible antecedent as trivially or vacuously true. Many have regarded this as a serious defect of the semantics. For intuitively, it seems, counterfactuals with impossible antecedents—counterpossibles—can be non-trivially true and non-trivially false. Whereas the counterpossible "If Hobbes had squared the circle, then the mathematical community at the time would have been surprised" seems true, "If Hobbes had squared the circle, then sick children in the mountains of Afghanistan at the time would (...) have been thrilled" seems false. Many have proposed to extend the Lewis–Stalnaker semantics with impossible worlds to make room for a non-trivial or non-vacuous treatment of counterpossibles. Roughly, on the extended Lewis–Stalnaker semantics, we evaluate a counterfactual of the form "If A had been true, then C would have been true" by going to closest world—whether possible or impossible—in which A is true and check whether C is also true in that world. If the answer is "yes", the counterfactual is true; otherwise it is false. Since there are impossible worlds in which the mathematically impossible happens, there are impossible worlds in which Hobbes manages to square the circle. And intuitively, in the closest such impossible worlds, sick children in the mountains of Afghanistan are not thrilled—they remain sick and unmoved by the mathematical developments in Europe. If so, the counterpossible "If Hobbes had squared the circle, then sick children in the mountains of Afghanistan at the time would have been thrilled" comes out false, as desired. In this paper, I will critically investigate the extended Lewis–Stalnaker semantics for counterpossibles. I will argue that the standard version of the extended semantics, in which impossible worlds correspond to maximal, logically inconsistent entities, fails to give the correct semantic verdicts for many counterpossibles. In light of the negative arguments, I will then outline a new version of the extended Lewis–Stalnaker semantics that can avoid these problems. (shrink)

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)

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)

Possible-worlds accounts of mental or linguistic content are often criticized for being too coarse-grained. To make room for more fine-grained distinctions among contents, several authors have recently proposed extending the space of possible worlds by "impossible worlds". We argue that this strategy comes with serious costs: we would effectively have to abandon most of the features that make the possible-worlds framework attractive. More generally, we argue that while there are intuitive and theoretical considerations against overly coarse-grained notions of content, the (...) same kinds of considerations also prohibit an overly fine-grained individuation of content. An adequate notion of content, it seems, should have intermediate granularity. However, it is hard to construe a notion of content that meets these demands. Any notion of content, we suggest, must be either implausibly coarse-grained or implausibly fine-grained (or both). (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)

This section is a discussion of Joseph Raz's Conception of Normativity introduced by Georgios Pavlakos.

The phenomenological approach to the philosophy of mind, as worked out by Husserl, has been severely criticized by philosophers within the Wittgensteinian tradition and, implicitly, by Wittgenstein himself. This book examines this criticism in detail, looking at the writings of Wittgenstein, Ryle, Hacker, Dennett, and others. In defending Husserl against his critics, it offers a comprehensive fresh view of phenomenology as a philosophy of mind.

Why, then, has Anglo-American jurisprudence remained staunchly indifferent to history? How has it been able to maintain its confident assumption that the analytical and the historical can be neatly...

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)

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)

In an article entitled "Is BAD a semantic primitive?", John Myhill suggested that the concept 'bad' should be removed from the list of semantic primitives put forward by Anna Wierzbicka and Cliff Goddard. Myhill argued that 'bad' is semantically decomposable, that there is no word in Biblical Hebrew that corresponds to the English word bad and, thus, no linguistic form that represents the primitive BAD in this language, and that 'bad' is dispensable in the semantic analysis and can be replaced (...) with other components without any loss or change of meaning. Discussing and illustrating some fundamental questions in the search for universal semantic primitives, the present author reconsiders these findings and finds a different answer to John Myhill's question. (shrink)

The labor market is an area with diverse data structures and multiple applications, such as matching job seekers with the right training or job. For this reason, the multilingual classification of European Skills, Competences, Qualifications and Occupations (ESCO) is a good example of the central role of ontologies in this area. However, ESCO cannot provide all the details of local labor market needs and does not provide links to other hierarchies of competences. For example, other taxonomies of occupations and skills (...) are widely used in German-speaking countries, but they are not in a state where they are easily accessible for interoperability and reasoning. In this paper, we present a first version of a German Labor Market Ontology (GLMO) that uses ESCO as a top-level ontology for the target domain. This makes it highly interoperable and comparable to existing ontologies by providing details for the regional structures in German-speaking countries. In addition, we present a detailed evaluation of the provided data and applications, as well as an extensive discussion of future work. (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)

In this paper, I investigate whether we can use a world-involving framework to model the epistemic states of non-ideal agents. The standard possible-world framework falters in this respect because of a commitment to logical omniscience. A familiar attempt to overcome this problem centers around the use of impossible worlds where the truths of logic can be false. As we shall see, if we admit impossible worlds where “anything goes” in modal space, it is easy to model extremely non-ideal agents that (...) are incapable of performing even the most elementary logical deductions. A much harder, and considerably less investigated challenge is to ensure that the resulting modal space can also be used to model moderately ideal agents that are not logically omniscient but nevertheless logically competent. Intuitively, while such agents may fail to rule out subtly impossible worlds that verify complex logical falsehoods, they are nevertheless able to rule out blatantly impossible worlds that verify obvious logical falsehoods. To model moderately ideal agents, I argue, the job is to construct a modal space that contains only possible and non-trivially impossible worlds where it is not the case that “anything goes”. But I prove that it is impossible to develop an impossible-world framework that can do this job and that satisfies certain standard conditions. Effectively, I show that attempts to model moderately ideal agents in a world-involving framework collapse to modeling either logical omniscient agents, or extremely non-ideal agents. (shrink)