Open Mind最新文献

Whereas decades of research have cataloged striking errors in physical reasoning, a resurgence of interest in intuitive physics has revealed humans' remarkable ability to successfully predict the unfolding of physical scenes. A leading interpretation intended to resolve these opposing results is that physical reasoning recruits a general-purpose mechanism that reliably models physical scenarios (explaining recent successes), but overly contrived tasks or impoverished and ecologically invalid stimuli can produce poor performance (accounting for earlier failures). But might there be tasks that persistently strain physical understanding, even in naturalistic contexts? Here, we explore this question by introducing a new intuitive physics task: evaluating the strength of knots and tangles. Knots are ubiquitous across cultures and time-periods, and evaluating them correctly often spells the difference between safety and peril. Despite this, 5 experiments show that observers fail to discern even very large differences in strength between knots. In a series of two-alternative forced-choice tasks, observers viewed a variety of simple "bends" (knots joining two pieces of thread) and decided which would require more force to undo. Though the strength of these knots is well-documented, observers' judgments completely failed to reflect these distinctions, across naturalistic photographs (E1), idealized renderings (E2), dynamic videos (E3), and even when accompanied by schematic diagrams of the knots' structures (E4). Moreover, these failures persisted despite accurate identification of the topological differences between the knots (E5); in other words, even when observers correctly perceived the underlying structure of the knot, they failed to correctly judge its strength. These results expose a blindspot in physical reasoning, placing new constraints on general-purpose theories of scene understanding.

The vocabularies of natural languages harbour many instances of iconicity, where words show a perceived resemblance between aspects of form and meaning. An open challenge in this domain is how to reconcile different operationalizations of iconicity and link them to an empirically grounded theory. Here we combine three ways of looking at iconicity using a set of 239 iconic words from 5 spoken languages (Japanese, Korean, Semai, Siwu and Ewe). Data on guessing accuracy serves as a baseline measure of probable iconicity and provides variation that we seek to explain and predict using structure-mapping theory and iconicity ratings. We systematically trace a range of cross-linguistically attested form-meaning correspondences in the dataset, yielding a word-level measure of cumulative iconicity that we find to be highly predictive of guessing accuracy. In a rating study, we collect iconicity judgments for all words from 78 participants. The ratings are well-predicted by our measure of cumulative iconicity and also correlate strongly with guessing accuracy, showing that rating tasks offer a scalable method to measure iconicity. Triangulating the measures reveals how structure-mapping can help open the black box of experimental measures of iconicity. While none of the methods is perfect, taken together they provide a well-rounded way to approach the meaning and measurement of iconicity in natural language vocabulary.

Children learn their first number words gradually over the course of many months, which is surprising given their ability to discriminate small numerosities. One potential explanation for this is that children are sensitive to the numerical features of stimuli, but don't consider exact cardinality as a primary hypothesis for novel word meanings. To test this, we trained 144 children on a number word they hadn't yet learned, and contrasted this with a condition in which they were merely required to attend to number to identify the word's referent, without encoding number as its meaning. In the first condition, children were trained to find a "giraffe with three spots." In the second condition, children were instead trained to find "Mr. Three", which also named a giraffe with three spots. In both conditions, children had to attend to number to identify the target giraffe, but, because proper nouns refer to individuals rather than their properties, the second condition did not require children to encode number as the meaning of the expression. We found that children were significantly better at identifying the giraffe when it had been labeled with the proper noun than with the number word. This finding contrasted with a second experiment involving color words, in which children (n = 56) were equally successful with a proper noun ("Mr. Purple") and an adjective ("the giraffe with purple spots"). Together, these findings suggest that, for number, but not for color, children's difficulty acquiring new words cannot be solely attributed to problems with attention or perception, but instead may be due to difficulty selecting the correct meaning from their hypothesis space for learning unknown words.

Transfer learning, the reuse of newly acquired knowledge under novel circumstances, is a critical hallmark of human intelligence that has frequently been pitted against the capacities of artificial learning agents. Yet, the computations relevant to transfer learning have been little investigated in humans. The benefit of efficient inductive biases (meta-level constraints that shape learning, often referred as priors in the Bayesian learning approach), has been both theoretically and experimentally established. Efficiency of inductive biases depends on their capacity to generalize earlier experiences. We argue that successful transfer learning upon task acquisition is ensured by updating inductive biases and transfer of knowledge hinges upon capturing the structure of the task in the inductive bias that can be reused in novel tasks. To explore this, we trained participants on a non-trivial visual stimulus sequence task (Alternating Serial Response Times, ASRT); during the Training phase, participants were exposed to one specific sequence for multiple days, then on the Transfer phase, the sequence changed, while the underlying structure of the task remained the same. Our results show that beyond the acquisition of the stimulus sequence, our participants were also able to update their inductive biases. Acquisition of the new sequence was considerably sped up by earlier exposure but this enhancement was specific to individuals showing signatures of abandoning initial inductive biases. Enhancement of learning was reflected in the development of a new internal model. Additionally, our findings highlight the ability of participants to construct an inventory of internal models and alternate between them based on environmental demands. Further, investigation of the behavior during transfer revealed that it is the subjective internal model of individuals that can predict the transfer across tasks. Our results demonstrate that even imperfect learning in a challenging environment helps learning in a new context by reusing the subjective and partial knowledge about environmental regularities.

Morality is central to social well-being and cognition, and moral lexicon is a key device for human communication of moral concepts and experiences. How was the moral lexicon formed? We explore this open question and hypothesize that words evolved to take on abstract moral meanings from concrete and grounded experiences. We test this hypothesis by analyzing semantic change and formation of over 800 words from the English Moral Foundations Dictionary and the Historical Thesaurus of English over the past hundreds of years. Across historical text corpora and dictionaries, we discover concrete-to-abstract shifts as words acquire moral meaning, in contrast with the broad observation that words become more concrete over time. Furthermore, we find that compound moral words tend to be derived from a concrete-to-abstract shift from their constituents, and this derivational property is more prominent in moral words compared to alternative compound words when word frequency is controlled for. We suggest that evolution of the moral lexicon depends on systematic metaphorical mappings from concrete domains to the moral domain. Our results provide large-scale evidence for the role of metaphor in shaping the historical development of the English moral lexicon.

A large program of research has aimed to ground large-scale cultural phenomena in processes taking place within individual minds. For example, investigating whether individual agents equipped with the right social learning strategies can enable cumulative cultural evolution given long enough time horizons. However, this approach often omits the critical group-level processes that mediate between individual agents and multi-generational societies. Here, we argue that interacting groups are a necessary and explanatory level of analysis, linking individual and collective intelligence through two characteristic feedback loops. In the first loop, more sophisticated individual-level social learning mechanisms based on Theory of Mind facilitate group-level complementarity, allowing distributed knowledge to be compositionally recombined in groups; these group-level innovations, in turn, ease the cognitive load on individuals. In the second loop, societal-level processes of cumulative culture provide groups with new cognitive technologies, including shared language and conceptual abstractions, which set in motion new group-level processes to further coordinate, recombine, and innovate. Taken together, these cycles establish group-level interaction as a dual engine of intelligence, catalyzing both individual cognition and cumulative culture.

Researchers have recently argued that the capabilities of Large Language Models (LLMs) can provide new insights into longstanding debates about the role of learning and/or innateness in the development and evolution of human language. Here, we argue on two grounds that LLMs alone tell us very little about human language and cognition in terms of acquisition and evolution. First, any similarities between human language and the output of LLMs are purely functional. Borrowing the "four questions" framework from ethology, we argue that what LLMs do is superficially similar, but how they do it is not. In contrast to the rich multimodal data humans leverage in interactive language learning, LLMs rely on immersive exposure to vastly greater quantities of unimodal text data, with recent multimodal efforts built upon mappings between images and text. Second, turning to functional similarities between human language and LLM output, we show that human linguistic behavior is much broader. LLMs were designed to imitate the very specific behavior of human writing; while they do this impressively, the underlying mechanisms of these models limit their capacities for meaning and naturalistic interaction, and their potential for dealing with the diversity in human language. We conclude by emphasising that LLMs are not theories of language, but tools that may be used to study language, and that can only be effectively applied with specific hypotheses to motivate research.

All talkers show some flexibility in their speech, and the ability to imitate an unfamiliar accent is a skill that shows vast individual differences. Yet the source of these individual differences, in particular whether they originate from perceptual, motor, or social/personality factors, is not yet clear. In the current study, we ask how individual differences in these factors predict individual differences in deliberate accent imitation. Participants imitated three accents, and attempts were rated for accuracy. A set of measures tracking individual differences in perceptual, motor, cognitive, personality, and demographic factors were also acquired. Imitation ability was related to differences in musical perception, vocal articulation, and the personality characteristic of "openness to experience," and was affected by attitudes towards the imitated talkers. Taken together, results suggest that deliberate accent imitation skill is modulated not only by core perceptual and motor skills, but also by personality and affinity to the talker, suggesting that some aspects of deliberate imitation are a function of domain-general constraints on perceptual-motor systems, while others may be modulated by social context.

Mate choice requires navigating an exploration-exploitation trade-off. Successful mate choice requires choosing partners who have preferred qualities; but time spent determining one partner's qualities could have been spent exploring for potentially superior alternatives. Here I argue that this dilemma can be modeled in a reinforcement learning framework as a multi-armed bandit problem. Moreover, using agent-based models and a sample of k = 522 real-world romantic dyads, I show that a reciprocity-weighted Thompson sampling algorithm performs well both in guiding mate search in noisy search environments and in reproducing the mate choices of real-world participants. These results provide a formal model of the understudied psychology of human mate search. They additionally offer implications for our understanding of person perception and mate choice.

Eye movements in the visual world paradigm are known to depend not only on linguistic input but on such factors as task, pragmatic context, affordances, etc. However, the degree to which eye movements may depend on task rather than on linguistic input is unclear. The present study for the first time tests how task constraints modulate eye movement behavior in the visual world paradigm by probing whether participants could refrain from looking at the referred image. Across two experiments with and without comprehension questions (total N = 159), we found that when participants were instructed to avoid looking at the referred images, the probability of fixating these reduced from 58% to 18% while comprehension scores remained high. Although language-mediated eye movements could not be suppressed fully, the degree of possible decoupling of eye movements from language processing suggests that participants can withdraw at least some looks from the referred images when needed. If they do so to different degrees in different experimental conditions, comparisons between conditions might be compromised. We discuss some cases where participants could adopt different viewing behaviors depending on the experimental condition, and provide some tentative ways to test for such differences.