Advances in research on human cerebral organoids (HCOs) call for a critical review of current research policies. A challenge for the evaluation of necessary research regulations lies in the severe uncertainty about future trajectories the currently very rudimentary stages of neural cell cultures might take as the technology progresses. To gain insights into organotypic cultures, ethicists, legal scholars, and neuroscientists rely on resemblances to the human brain. They refer to similarities in structural or functional terms that have been established in (...) scientific practice to validate organotypic cultures as models for brain research. In ethical discourse, however, such similarities are also used to justify assumptions about the potential risk to cause harm to HCOs. Ethicists assume that as the technology advances, organotypic cultures will increasingly resemble the human brain, raising more complex ethical issues. I argue that such reasoning is not justified given the heterogeneity of HCOs that have been modified to enable scientists to pursue their research goals. I then discuss the implications this line of thought has for advocates of the precautionary principle, focussing on those suggestions which propose adopting research regulations to the presence of bodily warning signs deemed worthy of protection. In doing so, I illustrate that the prevalent assumptions on similarity in ethical discourse ultimately risk disproportionately restricting research. I conclude that given the severe uncertainty about the technology’s future development, ethical discourse might benefit from narrowing the time frame for anticipation. (shrink)

If we speak of degrees of similarity, what kinds of judgment are we assuming to make sense? It will be argued that the necessary and sufficient condition for there to be degrees of similarity is that there should be a four-termed relation of comparative similarity — w resembles x at least as much as y resembles z—obeying certain constraints. Of course, nothing turns on how we use the words 'degree of similarity'. Rather, the point is to (...) distinguish the different levels of ideologicalcommitment which different kinds of judgment of similarity involve. (shrink)

The feature-matching approach pioneered by Amos Tversky remains a groundwork for psychological models of similarity and categorization but is rarely explicitly justified considering recent advances in thinking about cognition. While psychologists often view similarity as an unproblematic foundational concept that explains generalization and conceptual thought, long-standing philosophical problems challenging this assumption suggest that similarity derives from processes of higher-level cognition, including inference and conceptual thought. This paper addresses three specific challenges to Tversky’s approach: (i) the feature-selection problem, (...) (ii) the problem of cognitive implausibility, and (iii) the problem of unprincipled tweaking. It subsequently supports key insights from Tversky’s account based on recent developments in Bayesian modeling of cognition. A novel computational view of similarity as inference is proposed that addresses each challenge by considering the contrast class as constitutive of similarity and selecting for highly informative features. In so doing, this view illustrates the ongoing promise of the feature-matching approach in explaining perception, generalization and conceptual thought by grounding them in principles of probabilistic inference. (shrink)

In section I the notions of logical and inductive probability will be discussed as well as two explicanda, viz. degree of confirmation, the base for inductive probability, and degree of evidential support, Popper's favourite explicandum. In section II it will be argued that Popper's paradox of ideal evidence is no paradox at all; however, it will also be shown that Popper's way out has its own merits.

Being imitated has a wide range of pro-social effects, but it is not clear how these effects are mediated. Naturalistic studies of the effects of being imitated have not established whether pro-social outcomes are due to the similarity and/or the contingency between the movements performed by the actor and those of the imitator. Similarity is often assumed to be the active ingredient, but we hypothesized that contingency might also be important, as it produces positive affect in infants and (...) can be detected by phylogenetically ancient mechanisms of associative learning. We manipulated similarity and contingency between performed and observed actions in a computerized task. Similarity had no positive effects; however, contingency resulted in greater enjoyment of the task, reported closeness to others, and helping behavior. These results suggest that the pro-social effects of being imitated may rely on associative mechanisms. (shrink)

We propose and investigate an Analogy Principle in the context of Unary Inductive Logic based on a notion of support by structural similarity which is often employed to motivate scientific conjectures.

We investigate the role of perceptual similarity in visual metaphor comprehension process. In visual metaphors, perceptual features of the source and the target are objectively present as images. Moreover, to determine perceptual similarity, we use an image-based search system that computes similarity based on low-level perceptual features. We hypothesize that perceptual similarity at the level of color, shape, texture, orientation, and the like, between the source and the target image facilitates metaphorical comprehension and aids creative interpretation. (...) We present three experiments, two of which are eye-movement studies, to demonstrate that in the interpretation and generation of visual metaphors, perceptual similarity between the two images is recognized at a subconscious level, and facilitates the search for creative conceptual associations in terms of emergent features. We argue that the capacity to recognize perceptual similarity—considered to be a hallmark of creativity—plays a major role in the creative understanding of metaphors. (shrink)

abstract Applied ethics engages with concrete moral issues. This engagement involves the application of philosophical tools. When the philosophical tools used in applied ethics are problematic, conclusions about applied problems can become skewed. In this paper, I focus on problems with the idea that comparison cases must be exactly alike, except for the moral issue at hand. I argue that this idea has skewed the debate regarding the moral distinction between killing and letting die. I begin with problems that can (...) arise from attempts to produce comparison cases that are exactly alike, except for the moral issue at hand. I then argue that attempts to produce such examples are doomed to failure. Finally, I argue that abandoning concerns about similarity advances the debate regarding the moral distinction between killing and letting die. (shrink)

We compare methods of aggregating repeated decisions from a single decision maker to improve medical image decision making using metacognitive processes (confidence judgments) and representational similarity from artificial neural networks for both novice and expert participants.

The literature contains a disconnect between accounts of how humans learn lexical semantic representations for words. Theories generally propose that lexical semantics are learned either through perceptual experience or through exposure to regularities in language. We propose here a model to integrate these two information sources. Specifically, the model uses the global structure of memory to exploit the redundancy between language and perception in order to generate inferred perceptual representations for words with which the model has no perceptual experience. We (...) test the model on a variety of different datasets from grounded cognition experiments and demonstrate that this diverse set of results can be explained as perceptual simulation (cf. Barsalou, Simmons, Barbey, & Wilson, 2003) within a global memory model. (shrink)

Decades of research have pushed us closer to understanding what babies know. However, a powerful approach – representational similarity analysis (RSA) – is underused in developmental research. I discuss the strengths of this approach and what it can tell us about infant conceptual knowledge. As a case study, I focus on numerosity as a domain where RSA can make unique progress.

The common law system is a legal system that values precedent, or previous court decisions, in the resolution of current cases. As the availability of legal documents in digital form has increased, it has become more difficult for legal professionals to manually identify relevant past cases due to the vast amount of data. Researchers have developed automated systems for determining the similarity between legal documents to address this issue. Our research explores various representations of a legal document and discusses (...) a novel paragraph filtering process to identify key paragraphs using legal citation information to remove unnecessary text paragraphs without disturbing the concept of the legal document. State-of-the-art techniques like TF-IDF, BERT, Legal Bert, Doc2Vec, and Legal-longformer are used for the performance analysis of the proposed approach with document comparison. It has been shown that a model trained on the proposed filtered paragraphs can achieve better results than a model trained on the complete text and can also shorten the document by over 40%. The proposed filtering strategy could be helpful for models like BERT, where the maximum token length is fixed. (shrink)

In the original publication of the article, the y axis labels present in Figs. 1a and 2a are incorrect. The correct Figs. 1a and 2a are provided here.

Michael Weisberg has given us a lovely book on models. It has very broad coverage of issues intersecting the nature of models and their use, an extensive consideration of long ignored “concrete” models with a rich case study, a discussion and classification of the many diverse kinds of models, and a particularly groundbreaking and innovative discussion of similarity concerning how models relate to the world. Included are insightful discussions of increasingly used “agent based” models, and the conjoint use of (...) multiple models in looking for robust results. Weisberg fills in some discussions with modeling and simulation results of his own.In addition, he considers and critiques other recent competing views on models, including the increasingly popular “models as fictions” account. His discussion is clear and technically precise without being needlessly so, and his distinctions are useful. The scientist is more likely to recognize his objects than the semantic theorist, and that is how it .. (shrink)

Previous work has shown that the Complex Conceptual Spaces − Single Observation Mathematical framework is a useful tool for event characterization. This mathematical framework is developed on the basis of Conceptual Spaces and uses integer linear programming to find the needed similarity values. The work of this paper is focused primarily on space event characterization. In particular, the focus is on the ranking of threats for malicious space events such as a kinetic kill. To make the Conceptual Spaces framework (...) work, the similarity values between the contents of observations on the one hand and the properties of the entities observed on the other needs to be found. This paper shows how to exploit Dempster-Shafer theory to implement a statistical approach for finding these similarities values. This approach will allow a user to identify the uncertainty involved in similarity value data, which can later be propagated through the developed mathematical model in order for the user to know the overall uncertainty in the observation-to-concept mappings needed for space event characterization. (shrink)

In this paper we ask whether approximation for abstract argumentation is useful in practice, and in particular whether reasoning with grounded semantics – which has polynomial runtime – is already an approximation approach sufficient for several practical purposes. While it is clear from theoretical results that reasoning with grounded semantics is different from, for example, skeptical reasoning with preferred semantics, we investigate how significant this difference is in actual argumentation frameworks. As it turns out, in many graphs models, reasoning with (...) grounded semantics actually approximates reasoning with other semantics almost perfectly. An algorithm for grounded reasoning is thus a conceptually simple approximation algorithm that not only does not need a learning phase – like recent approaches – but also approximates well – in practice – several decision problems associated to other semantics. (shrink)

The target article postulates that rule-based and similarity-based categorization are best described by a unitary process. A number of recent empirical dissociations between rule-based and similarity-based categorization severely challenge this view. Collectively, these new results provide strong evidence that these two types of category learning are mediated by separate systems.

A promising approach to more refined models consistent with the Caplan & Waters hypothesis is based on similarity-based interference, a general principle that applies across working memory domains. This may explain both the fine details of syntactic working memory phenomena and the gross fractionation for which Caplan & Waters have found evidence. Detailed models of syntactic processing that embody similarity-based interference fare well cross-linguistically.

Criteria that aim to dichotomize cognition into rules and similarity are destined to fail because rules and similarity are not in genuine conflict. It is possible for a given cognitive domain to exploit rules without similarity, similarity without rules, or both (rules and similarity) at the same time.

ABSTRACTMoran and Bar-Anan. The effect of object-valence relations on automatic evaluation. Cognition and Emotion, 27, 743–752) demonstrated that evaluations on...