Language agents are AI systems capable of understanding and responding to natural language, potentially facilitating the process of encoding human goals into AI systems. However, this paper argues that if language agents can achieve easy alignment, they also increase the risk of malevolent agents building harmful AI systems aligned with destructive intentions. The paper contends that if training AI becomes sufficiently easy or is perceived as such, it enables malicious actors, including rogue states, terrorists, (...) and criminal organizations, to create powerful AI systems devoted to their nefarious aims. Given the strong incentives for such groups and the rapid progress in AI capabilities, this risk demands serious attention. In addition, the paper highlights considerations suggesting that the negative impacts of language agents may outweigh the positive ones, including the potential irreversibility of certain negative AI impacts. The overarching lesson is that various AI-related issues are intimately connected with each other, and we must recognize this interconnected nature when addressing those issues. (shrink)

Recent advances in natural language processing have given rise to a new kind of AI architecture: the language agent. By repeatedly calling an LLM to perform a variety of cognitive tasks, language agents are able to function autonomously to pursue goals specified in natural language and stored in a human-readable format. Because of their architecture, language agents exhibit behavior that is predictable according to the laws of folk psychology: they function as though they (...) have desires and beliefs, and then make and update plans to pursue their desires given their beliefs. We argue that the rise of language agents significantly reduces the probability of an existential catastrophe due to loss of control over an AGI. This is because the probability of such an existential catastrophe is proportional to the difficulty of aligning AGI systems, and language agents significantly reduce that difficulty. In particular, language agents help to resolve three important issues related to aligning AIs: reward misspecification, goal misgeneralization, and uninterpretability. (shrink)

Language agents are AI systems that combine large language models with other elements to facilitate interaction with an environment. They include LLM-based chatbots but can have a wide range of additional features to support learning, reasoning and decision-making. Goldstein and Kirk-Giannini. Citationm.s. [AI wellbeing] argue that some language agents have beliefs and desires, but it is not obvious that they are agents at all, since they select outputs by querying language models. This paper (...) investigates agency and desires in language agents. (shrink)

It is generally assumed that existing artificial systems are not phenomenally conscious, and that the construction of phenomenally conscious artificial systems would require significant technological progress if it is possible at all. We challenge this assumption by arguing that if Global Workspace Theory (GWT) — a leading scientific theory of phenomenal consciousness — is correct, then instances of one widely implemented AI architecture, the artificial language agent, might easily be made phenomenally conscious if they are not already. Along the (...) way, we articulate an explicit methodology for thinking about how to apply scientific theories of consciousness to artificial systems and employ this methodology to arrive at a set of necessary and sufficient conditions for phenomenal consciousness according to GWT. (shrink)

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample languages from (...) this posterior distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior. Under these conditions, iterated learning is a form of Gibbs sampling, a widely-used Markov chain Monte Carlo algorithm. The consequences of iterated learning are more complicated when learners choose the language with maximum posterior probability, being affected by both the prior of the learners and the amount of information transmitted between generations. We show that in this case, iterated learning corresponds to another statistical inference algorithm, a variant of the expectation-maximization (EM) algorithm. These results clarify the role of iterated learning in explanations of linguistic universals and provide a formal connection between constraints on language acquisition and the languages that come to be spoken, suggesting that information transmitted via iterated learning will ultimately come to mirror the minds of the learners. (shrink)

Languages show substantial variability between their speakers, but it is currently unclear how the structure of the communicative network contributes to the patterning of this variability. While previous studies have highlighted the role of network structure in language change, the specific aspects of network structure that shape language variability remain largely unknown. To address this gap, we developed a Bayesian agent‐based model of language evolution, contrasting between two distinct scenarios: language change and language emergence. By (...) isolating the relative effects of specific global network metrics across thousands of simulations, we show that global characteristics of network structure play a critical role in shaping interindividual variation in language, while intraindividual variation is relatively unaffected. We effectively challenge the long‐held belief that size and density are the main network structural factors influencing language variation, and show that path length and clustering coefficient are the main factors driving interindividual variation. In particular, we show that variation is more likely to occur in populations where individuals are not well‐connected to each other. Additionally, variation is more likely to emerge in populations that are structured in small communities. Our study provides potentially important insights into the theoretical mechanisms underlying language variation. (shrink)

While agent-based modelling languages naturally implement concurrency, the currently available languages for argumentation do not allow to explicitly model this type of interaction. In this paper we introduce a concurrent language for handling agents arguing and communicating using a shared argumentation space. We also show how to perform high-level operations like persuasion and negotiation through basic belief revision constructs, and present a working implementation of the language and the associated web interface.

While understanding and expressing causal relations are universal aspects of human cognition, language users may differ in their capacity to perceive, interpret, and express events. One source of variation in descriptions of caused motion events is agentivity, which refers to the attribution of a result to the agent's action. Depending on the perspective taken, the same event may be described with agentive or non-agentive interpretations. Does language play a role in how people construe and express caused motion events? (...) The present study investigated the use of agentive vs. non-agentive language by speakers of different languages (i.e., monolingual speakers of English and Korean, and Korean learners of English). All three groups described prototypical causal events similarly, using agentive language (active transitive sentences). However, when it came to non-prototypical causal events (where the agent was not shown in the scene), they diverged in their choice of language: English speakers favored agentive language (passive transitive sentences), whereas Korean speakers preferred non-agentive language (intransitive sentences). Korean learners of English patterned with Korean speakers, demonstrating L1 influence on their use of English. These findings highlight the effects of language on motion event construal. (shrink)

This paper describes the layers of context leveraged by language-endowed intelligent agents (LEIAs) during incremental natural language understanding (NLU). Context is defined as a combination of (...

Natural languages vary in their quantity expressions, but the variation seems to be constrained by general properties, so-calleduniversals. Their explanations have been sought among constraints of human cognition, communication, complexity, and pragmatics. In this article, we apply a state-of-the-art language coordination model to the semantic domain of quantities to examine whether two quantity universals—monotonicity and convexity—arise as a result of coordination. Assuming precise number perception by the agents, we evolve communicatively usable quantity terminologies in two separate conditions: a (...) numeric-based condition in which agents communicate about a number of objects and a quotient-based condition in which agents communicate about the proportions. We find out that both universals take off in all conditions but only convexity almost entirely dominates the emergent languages. Additionally, we examine whether the perceptual constraints of the agents can contribute to the further development of universals. We compare the degrees of convexity and monotonicity of languages evolving in populations of agents with precise and approximate number sense. The results suggest that approximate number sense significantly reinforces monotonicity and leads to further enhancement of convexity. Last but not least, we show that the properties of the evolved quantifiers match certain invariance properties from generalized quantifier theory. (shrink)

This paper introduces a novel perspective on Agentive Cognitive Construction Grammar (AgCCxG) by examining the intricate interplay between mind and language through the lens of both Active Inference and Peircean semiotics. AgCCxG emphasizes the impact of intention and purpose on linguistic choices as a cognitive imperative to balance the symbolic Self (Intelligent Agent) with the dynamics of the environment. Among other things, the paper posits that linguistic constructions, particularly Constructional Attachment Patterns (CAPs), like argument structure constructions, embody experienced interactions (...) with the world through reenactment routines via the integration of multisensory channels. Unlike traditional usage-based approaches (e.g., construction grammars), AgCCxG embraces a robust theory of signs that reveals human representation as a continuous process of semiotic hybridization for the creative prediction of uncertain scenarios. Importantly, the paper challenges the notion of the mind as a unified, rational, uncertainty-reducing machine by asserting that physical processes governing open biological systems profoundly influence the linguistic sign system. Intelligent agents’ adaptability in expressing incongruous realities thus highlights the role of semiotic hybridization in preserving an agent’s autonomy and semiotic boundary. (shrink)

This paper develops a natural-language agent-based model of argumentation (ABMA). Its artificial deliberative agents (ADAs) are constructed with the help of so-called neural language models recently developed in AI and computational linguistics. ADAs are equipped with a minimalist belief system and may generate and submit novel contributions to a conversation. The natural-language ABMA allows us to simulate collective deliberation in English, i.e. with arguments, reasons, and claims themselves — rather than with their mathematical representations (as in (...) symbolic models). This paper uses the natural-language ABMA to test the robustness of symbolic reason-balancing models of argumentation (Mäs & Flache 2013; Singer et al. 2019): First of all, as long as ADAs remain passive, confirmation bias and homophily updating trigger polarization, which is consistent with results from symbolic models. However, once ADAs start to actively generate new contributions, the evolution of a conversation is dominated by properties of the agents as authors. This suggests that the creation of new arguments, reasons, and claims critically affects a conversation and is of pivotal importance for understanding the dynamics of collective deliberation. The paper closes by pointing out further fruitful applications of the model and challenges for future research. (shrink)

The language comprehension system preferentially assumes that agents come first during incremental processing. While this might reflect a biologically fixed bias, shared with other domains and other species, the evidence is limited to languages that place agents first, and so the bias could also be learned from usage frequency. Here, we probe the bias with electroencephalography (EEG) in Äiwoo, a language that by default places patients first, but where sentence-initial nouns are still locally ambiguous between patient (...) or agent roles. Comprehenders transiently interpreted nonhuman nouns as patients, eliciting a negativity when disambiguation was toward the less common agent-initial order. By contrast and against frequencies, human nouns were transiently interpreted as agents, eliciting an N400-like negativity when the disambiguation was toward patient-initial order. Consistent with the notion of a fixed property, the agent bias is robust against usage frequency for human referents. However, this bias can be reversed by frequency experience for nonhuman referents. (shrink)

The papers collected in this volume exemplify some of the trends in current approaches to logic, language and computation. Written by authors with varied academic backgrounds, the contributions are intended for an interdisciplinary audience. The first part of this volume addresses issues relevant for multi-agent systems: reasoning with incomplete information, reasoning about knowledge and beliefs, and reasoning about games. Proofs as formal objects form the subject of Part II. Topics covered include: contributions on logical frameworks, linear logic, and different (...) approaches to formalized reasoning. Part III focuses on representations and formal methods in linguistic theory, addressing the areas of comparative and temporal expressions, modal subordination, and compositionality. (shrink)

Interference effects from semantically similar items are well-known in studies of single word production, where the presence of semantically similar distractor words slows picture naming. This article examines the consequences of this interference in sentence production and tests the hypothesis that in situations of high similarity-based interference, producers are more likely to omit one of the interfering elements than when there is low semantic similarity and thus low interference. This work investigated language production in Mandarin, which allows subject noun (...) phrases to be omitted in discourse contexts in which the subject entity has been previously mentioned in the discourse. We hypothesize that Mandarin speakers omit the subject more often when the subject and the object entities are conceptually similar. A corpus analysis of simple transitive sentences found higher rates of subject omission when both the subject and object were animate (potentially yielding similarity-based interference) than when the subject was animate and object was inanimate. A second study manipulated subject-object animacy in a picture description task and replicated this result: participants omitted the animate subject more often when the object was also animate than when it was inanimate. These results suggest that similarity-based interference affects sentence forms, particularly when the agent of the action is mentioned in the sentence. Alternatives and mechanisms for this effect are discussed. (shrink)

The SDML programming language which is optimized for modelling multi-agent interaction within articulated social structures such as organizations is described with several examples of its functionality. SDML is a strictly declarative modelling language which has object-oriented features and corresponds to a fragment of strongly grounded autoepistemic logic. The virtues of SDML include the ease of building complex models and the facility for representing agents flexibly as models of cognition as well as modularity and code reusability.

Computational approaches based on autonomous agents share with new ape language research the same principles of dynamical system paradigms. A recent model for the evolution of symbolization and language in autonomous agents is briefly described in order to highlight the similarities between these two methodologies. The additional benefits of autonomous agent modeling in the field of language origin research are highlighted.

In this paper we introduce a new generation of language trainers: intelligent virtual agents (IVAs) with human appearance and the capability to teach foreign language vocabulary. We report results from studies that we have conducted with Billie, an IVA employed as a vocabulary trainer, as well as research findings on the acceptance of the agent as a trainer by adults and children. The results show that Billie can train humans as well as a human teacher can and (...) that both adults and children accept the IVA as a trainer. The advantages of IVAs are multiple. First, their teaching methods can be based on neuropsychological research findings concerning memory and learning practice. Second, virtual teachers can provide individualized training. Third, they coach users during training, are always supportive, and motivate learners to train. Fourth, agents will reside in the user's mobile devices and thus be at the user's disposal everywhere and anytime. Agents in apps will make foreign language training accessible to anybody at low cost. This will enable people around the world, including physically, financially, and geographically disadvantaged persons, to learn a foreign language and help to facilitate multilingualism. (shrink)

There are two main traditions in defining a semantics for agent communication languages, based either on mental attitudes or on social commitments. These traditions share speech acts as operators with preconditions and effects, and agents playing roles like speaker and hearer, but otherwise they rely on distinct ontologies. They refer not only to either belief and intention or various notions of social commitment, but also to distinct speech acts and distinct kinds of dialogue. In this paper, we propose a (...) common ontology for both approaches based on public mental attitudes attributed to role instances. Public mental attitudes avoid the unverifiability problem of private mental states, while reusing the logics and implementations developed for FIPA compliant approaches. Moreover, a common ontology of communication primitives allows for the construction of agents which do not need separate reasoning modules to participate in dialogues with both mental attitudes and social commitments compliant agents. Moreover, a common ontology of communication primitives allows for the construction of agents participating in and combining the full range of dialogues covered by the individual approaches without having to redefine the existing protocols to cope with new dialog types. We illustrate how to extend the ontology to a semantics for agent communication and how to define mappings from existing semantics to the new one. (shrink)

Agent Communication Languages (ACLs) have recently acquired a primary role in open multiagent systems, which need a standard communication framework shared by all interacting heterogeneous agents. According to the most important ACL standard proposals so far, agents are supposed to carry out the communication process by performing actions of a specific type, namely, communicative acts, whose semantics is defined in terms of the agents’ mental states. Although following the mainstream guidelines inspired by the Speech Act Theory, our (...) work illustrates an alternative model of agent communication, by shifting the focus from agents’ mental states to their social state. Taking an existing communicative act library, we provide a semantics for a significant set of acts based on the concept of commitment, and prove that our approach tackles some issues that have not been dealt with in an effective way yet and that may have hindered the rise of an universally accepted ACL standard. (shrink)

Theory of Mind (ToM), the cognitive capacity to attribute internal mental states to oneself and others, is a crucial component of social skills. Its formal study has become important, witness recent research on reasoning and information update by intelligent agents, and some proposals for its formal modelling have put forward settings based on Epistemic Logic (EL). Still, due to intrinsic idealisations, it is questionable whether EL can be used to model the high-order cognition of ‘real’ agents. This manuscript (...) proposes a framework that takes visibility, memory, perspective and communication as the main factors underpinning mental attributions. This is more in-line with findings in cognitive science and allows us to model well-known False-Belief Tasks that are typically used in testing people's ToM. We discuss some of the framework's technical features, arguing why it does justice to empirical observations. (shrink)

All languages, both spoken and signed, make a formal distinction between two types of terms in a proposition – terms that identify what is to be talked about (nominals) and terms that say something about this topic (predicates). Here we explore conditions that could lead to this property by charting its development in a newly emerging language – Nicaraguan Sign Language (NSL). We examine how handshape is used in nominals vs. predicates in three Nicaraguan groups: (1) homesigners who (...) are not part of the Deaf com- munity and use their own gestures, called homesigns, to communicate; (2) NSL cohort 1 signers who fashioned the first stage of NSL; (3) NSL cohort 2 signers who learned NSL from cohort 1. We compare these three groups to a fourth: (4) native signers of American Sign Language (ASL), an established sign language. We focus on handshape in predicates that are part of a productive classifier system in ASL; handshape in these predicates varies sys- tematically across agent vs. no-agent contexts, unlike handshape in the nominals we study, which does not vary across these contexts. We found that all four groups, including home- signers, used handshape differently in nominals vs. predicates – they displayed variability in handshape form across agent vs. no-agent contexts in predicates, but not in nominals. Variability thus differed in predicates and nominals: (1) In predicates, the variability across grammatical contexts (agent vs. no-agent) was systematic in all four groups, suggesting that handshape functioned as a productive morphological marker on predicate signs, even in homesign. This grammatical use of handshape can thus appear in the earliest stages of an emerging language. (2) In nominals, there was no variability across grammatical con- texts (agent vs. no-agent), but there was variability within- and across-individuals in the handshape used in the nominal for a particular object. This variability was striking in homesigners (an individual homesigner did not necessarily use the same handshape in every nominal he produced for a particular object), but decreased in the first cohort of NSL and remained relatively constant in the second cohort. Stability in the lexical use of handshape in nominals thus does not seem to emerge unless there is pressure from a peer linguistic community. Taken together, our findings argue that a community of users is essential to arrive at a stable nominal lexicon, but not to establish a productive morpholog- ical marker in predicates. Examining the steps a manual communication system takes as it moves toward becoming a fully-fledged language offers a unique window onto factors that have made human language what it is. (shrink)

Despite their diversity, human languages share consistent properties and regularities. Wherefrom does this consistency arise? And does it tell us something about the problem that all languages need to solve? The authors provide an intriguing analyses which focuses on the “communicative function of ambiguity” whose resolution entailed an equally intriguing “speaker–listener cross‐entropy objective for measuring the efficiency of linguistic systems from first principles of efficient language use.”.

In Rethinking Language Arts: Passion and Practice, author Nina Zaragoza uses the form of letters to her students to engage pre-service teachers in reevaluating teaching practices, thus bringing to life a vision of an alternative classroom environment in which the teacher is the prime mover and creative leader. Zaragoza discusses and explains the need for teachers to be decision makers, reflective thinkers, political beings, and agents of social change in order to create a positive and inclusive classroom setting. (...) This book is both a critical text that deconstructs the way language arts are traditionally taught in our schools as well as a visionary text with clear, no-nonsense directions on how to provide much needed change in our schools. (shrink)

_Gendered Agents_, edited by Silvestra Mariniello andPaul A. Bové, presents essays by influential feminist theorists who challenge traditional Western epistemology and suggest new directions for feminism. By examining both literary and historical discourses, such critics as Gayatri Spivak, Hortense Spillers, and Lauren Berlant assess questions of sexuality, ethics, race, psychoanalysis, subjectivity, and identity. Gathered from various issues of the journal _boundary 2_, the essays in _Gendered Agents_ seek to transform the model of Western academic knowledge by restructuring its priorities and (...) values. In the introduction, Mariniello urges feminists to begin anew but take as their starting place the achievements of feminism and feminist theory: an understanding of language that considers the implications of silence, the motivation to decompartmentalize experience, and the acknowledgement that everything is political._ _Challenging both a canonical organization of knowledge and the persistently self-referential "ghettoization" of feminism, contributors subsequently tackle subjects as diverse as pre-Marxist France, the American fetus, black intellectuals, queer nationality, and the art of literary interpretation. _Contributors_. Lauren Berlant, Karen Brennan, Margaret Cohen, Nancy Fraser, Elizabeth Freeman, Carol Jacobs, Silvestra Mariniello, Larysa Mykyta, Laura Rice, Ivy Schweitzer, Doris Sommer, Hortense J. Spillers, Gayatri Chakravorty Spivak, Judith Wilt. (shrink)

Natural languages vary widely in the degree to which they make use of nested compositional structure in their grammars. It has long been noted by linguists that the languages historically spoken in small communities develop much deeper levels of compositional embedding than those spoken by larger groups. Recently, this observation has been confirmed by a robust statistical analysis of the World Atlas of Language Structures. In order to examine this connection mechanistically, we propose an agent‐based model that accounts for (...) key cultural evolutionary features of language transfer and language change. We identify transitivity as a physical parameter of social networks critical for the evolution of compositional structure and the hierarchical patterning of scale‐free distributions as inhibitory. (shrink)

The primary function of language is communication. We use the tools of situation theory and game theory to develop a definition and model of communication between rational agents using a shared situated language. ;A central thesis of this dissertation is that the key feature of situated communication that enables agents to derive content from meaning is a special type of logical inference called a strategic inference. ;The model we develop, called the Strategic Discourse Model, looks at (...) a single strategic inference. An essential element of a strategic inference is that the content depends on the sentence uttered and on the embedding circumstances. This includes the private and public information and beliefs of the agents, their goals and intentions, and crucially, the other sentences the speaker might have uttered but chose not to. A complete model of communication involves a system of simultaneous strategic inferences. ;When the strategic interaction between two agents is common knowledge between them, that is, when it is a game, the information transfer is a communication. The content communicated is given by the solution to the game. This analysis formalizes Grice's ideas on nonnatural meaning within a situation-theoretic framework. A consequence of our situated analysis is that agents do not need to have the complex and infinite set of nested intentions postulated by the Gricean approach. A simple intention to communicate is all that is required, the ambient game doing the rest of the work. ;This model has many applications. Problems like resolving ambiguity, determining reference, inferring implicatures and indirect speech acts fall within its scope. As one application, we outline a new theory of names and definite descriptions. This account builds upon Russell and Strawson, and Barwise and Perry. The basic idea is that names and descriptions can both be used in various ways circumscribed by an ontological and a communicative constraint. This offers a new solution to the puzzle of informative identity statements and clarifies the referential-attributive distinction. It suggests an approach to the concept of representation. ;An underlying theme is to synthesize situation theory and game theory. (shrink)

The construction of complex simulation models and the application of new computer hardware to ecological problems has resulted in the need for many ecologists to rely on computer programmers to develop their modelling software. However, this can lead to a lack of flexibility and understanding in model implementation and in resource problems for researchers. This paper presents a new programming language, Viola, based on a simple organisational concept which can be used by most researchers to develop complex simulations much (...) more easily than could be achieved with standard programming languages such as C++. The language is object oriented and implemented through a visual interface. It is specifically designed to cope with complicated individual based behavioural simulations and comes with embedded concurrency handling abilities. (shrink)

In this paper, we first propose a simple formal language to specify types of agents in terms of necessary conditions for their announcements. Based on this language, types of agents are treated as ‘first-class citizens’ and studied extensively in various dynamic epistemic frameworks which are suitable for reasoning about knowledge and agent types via announcements and questions. To demonstrate our approach, we discuss various versions of Smullyan’s Knights and Knaves puzzles, including the Hardest Logic Puzzle Ever (...) (HLPE) proposed by Boolos (in Harv Rev Philos 6:62–65, 1996). In particular, we formalize HLPE and verify a classic solution to it. Moreover, we propose a spectrum of new puzzles based on HLPE by considering subjective (knowledge-based) agent types and relaxing the implicit epistemic assumptions in the original puzzle. The new puzzles are harder than the previously proposed ones in the literature, in the sense that they require deeper epistemic reasoning. Surprisingly, we also show that a version of HLPE in which the agents do not know the others’ types does not have a solution at all. Our formalism paves the way for studying these new puzzles using automatic model checking techniques. (shrink)

The central argument of this paper is that compatibilist theories that understand human agent causation as self-determination are consistent with, and can accommodate, important insights from evolutionary and developmental psychology. Agent causation is nothing more than the non-mysterious self-determining capability of persons, understood as embodied, emergent ontological entities whose nature is not fixed due to their uniquely evolved and developed capabilities of language use, cultural construction, self-consciousness and self-understanding, and moral concern. Relevant arguments of Dennett and Searle are adapted (...) to fit within the author's own emergentist, developmental theorizing that treats the self-determining capability of persons as arising within relevant biophysical and sociocultural contexts without being reducible to these contexts. Persons are self-determining in ways that require explanation not only in terms of materialistic efficient causal explanations appropriate to our evolved biophysical nature, but also in terms of final purposive explanations appropriate to our emergence as culture- capable, self-reflective agents, and formal explanations consistent with our evolved and developed nature as particular bio-cultural hybrids. (shrink)

What role does language play in the process of building worldviews? To address this question, in the first section of this paper we will clarify what we mean by worldviews and how they differ, in our perspective, from cosmovisions. In a nutshell, we define worldviews as the biological interpretations agents create of the world around them and cosmovision the more general cultural-based reflections on it. After presenting our definition for worldview, we will also present the multi-shaped viewpoint that (...) frames our analysis, adopting three concepts that can help us explain how agents construct and develop their worldviews: saliences, pregnances, and abduction. While the notions of saliences and pregnances will explain how agents recognize anomalies in their worldview, the concept of abduction will help us discuss how they can learn to approach, explain, and use these anomalies to get new skills and abilities. This other point will lead us to discuss the role of language in this process, which will be describe as an artifact that permits the agent to use abduction to “normalize” and exploit anomalies, being now the ultimate artifact to build, develop, and update their worldviews. (shrink)