Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLM s (2024)

Abstract: Are LLMs cultural technologies like photocopiers or printing presses, which transmit information but cannot create new content? A challenge for this idea, which we call bibliotechnism, is that LLMs generate novel text. We begin with a defense of bibliotechnism, showing how even novel text may inherit its meaning from original human-generated text. We then argue that bibliotechnism faces an independent challenge from examples in which LLMs generate novel reference, using new names to refer to new entities. Such examples could be explained if LLMs were not cultural technologies but had beliefs, desires, and intentions. According to interpretationism in the philosophy of mind, a system has such attitudes if and only if its behavior is well explained by the hypothesis that it does. Interpretationists may hold that LLMs have attitudes, and thus have a simple solution to the novel reference problem. We emphasize, however, that interpretationism is compatible with very simple creatures having attitudes and differs sharply from views that presuppose these attitudes require consciousness, sentience, or intelligence (topics about which we make no claims).

## introduction do modern llms have beliefs, desires, and intentions? over the last few years, this question has been much discussed (e.g., @xcite @xcite @xcite . the hypothesis that llms do have these states is attractive in part because it offers a natural tool for explaining their behavior. it is standard to explain the complex behavior of humans and non-human animals in terms of what they think (believe), what they want (desire), and what they intend. if modern llms have beliefs, desires, and intentions, we can use the same tools to explain their behavior as well. a challenge for those who deny that current llms have beliefs, desires, and intentions, is to provide an alternative, equally powerful, explanation of their behavior. alison gopnik and her coauthors have articulated a striking idea in this direction @xcite . in gopnik's view, llms are a ''cultural technology'', like a library or a printing press. along these lines, the writer ted chiang compares prompting an llm to ''searching over a library's contents for passages that are close to the prompt, and sampling from what follows'' @xcite . cosma shalizi has dubbed this general idea ''gopnikism'' @xcite . since we will develop the position in our own way, we have given our version a new name: bibliotechnism, a combination of the greek word for ''book'' and the greek word for ''skill''. the defining commitments of bibliotechnism are, first, that llms are cultural technologies; and, second, that llms do not have beliefs, desires, and intentions. the second claim especially will be key here, though it requires expanding gopnik's position. can this view provide an explanation of the behavior of llms, which is sufficiently powerful to compete with the hypothesis that they have beliefs, desires, and intentions? we argue that if bibliotechnism is true, then if llm-produced text is meaningful, its meaningfulness must in an important sense depend on the fact that text in the llm's training data is meaningful. if llms generated meaningful text, but its meaning were not of this ''derivative'' kind, then there would be an important sense in which, contrary to bibliotechnism, llms do not simply transmit existing cultural knowledge. in normal cases, text produced by photocopiers and printing presses has only derivative meaning: it is simply a reproduction of human-generated input. but llms often produce entirely novel text, which is still apparently meaningful. this seems to present a serious challenge for bibliotechnism: if llm-generated text is meaningful only when it piggybacks on human-generated originals, how could such novel text be meaningful? in part i, we defend bibliotechnism against this challenge. using n-grams as a toy model, and working up to more complex modern llms, we show how even novel text produced by llms may nevertheless derive its meaningfulness from the meaningfulness of the llm's inputs. we see this as an important step forward for bibliotechnism. but in part ii, we present a further challenge for this view. modern llms are not just capable of producing novel text using old words, they also can produce newly invented names which apparently refer to newly created objects. these new names cannot derive their reference from original text, since by assumption the name is not used in the data to refer to the relevant object. we argue that this novel reference problem poses a serious challenge for bibliotechnism. llm behavior in the novel reference problem would be easily explained if llms had beliefs, desires, and intentions. according to interpretationism in the philosophy of mind and cognitive science, a system has beliefs, desires, and intentions if and only if its behavior is well explained by the hypothesis that it has such states (e.g., @xcite @xcite . according to this thesis, there is no difference between the question of whether a system's behavior is well-explained on the hypothesis that it has certain attitudes, and the question of whether it actually has those attitudes. we argue that, if this philosophical position is true, then there is evidence that llms have beliefs, desires, and intentions, and the novel reference problem can be easily solved. we emphasize, however, that interpretationism differs in important ways from common lay views about the ontology of attitudes. it does not require that a system have particular internal correlates (say, a particular neuron) of putative beliefs or intentions; nor does it require that a system be intelligent or conscious in order to have attitudes. instead, a system may count as having beliefs or intentions because of patterns visible in its global behavior. thus, for interpretationists, attributing beliefs, desires, and intentions to llms does not require that they are sentient or conscious (see @xcite @xcite , for discussion of these questions). ## prior work and background prior work a prominent line of argument has suggested that llms cannot produce reference without being ''grounded'' (e.g., @xcite . @xcite have influentially argued that llms cannot understand language in part because they cannot have perceptual contact with objects to which speakers intend to refer, and so cannot learn those speakers' communicative intents. a natural inference from their discussion is that, owing to llms' inability to understand language, they can also not produce meaningful text (cf. titus, 2024). @xcite propose an alternative account of meaning in which meanings are constituted by the relationship among concepts in a particular conceptual space. since llms clearly represent rich inferential relationships as well as relations of semantic similarity, in their view llms can produce meaningful words even without perceptual exposure to their referents. @xcite connect the debate between @xcite and @xcite to semantic externalism, a view of meaning which has been dominant in the philosophy of language since the 1980s. on a standard view, @xcite @xcite , people can refer to shakespeare without having been in direct causal contact with shakespeare, in part by belonging to a community whose overall use of this word stands in an appropriate causal relationship to the poet. mandelkern and linzen accordingly suggest that whether llms can produce text that refers to shakespeare depends on whether llms ''belong to our speech community''. cappelen and dever (2021) earlier provided a systematic application of semantic externalism to model-generated text. they argue that such text can be meaningful, but that in order to accommodate the full range of model behavior, we must revise and extend standard theories of meaning. in response, they propose a novel interpreterfocused ''metametasemantics'', according to which the meaningfulness of novel generated text depends on what someone could come to know by reading it. @xcite similarly sees llms as inspiring revision to the theory of meaning, suggesting the meaningfulness of model-generated text requires a form of radical contextualism. the present paper goes beyond these earlier works by considering the relationship between the meaningfulness of llm-generated text and the viability of bibliotechnism. moreover, earlier theoretical work does not clearly vindicate the claim that n-gram models produce meaningful text, whereas we will argue that they do. moreover, we do so without revision to standard theories of meaning. we build on our account to defend bibliotechnism against an important challenge, demonstrating that the view can accommodate the meaningfulness of even entirely novel text generated by llms. we then introduce the novel reference problem as a new challenge for bibliotechnism. background modern generative language models are trained on primarydata, typically on a word prediction task and sometimes with additional training to bring about particular behaviors (e.g., reinforcement learning from human feedback [rlhf] whereby models receive explicit feedback to align with human preferences; @xcite . at generation time, they are prompted and then sampled to probabilistically produce generatedtext. we will take it as uncontroversial that words in primary-data are meaningful and refer to things in the world. for instance, if a human-authored biography of shakespeare is included in primary-data and includes the line ''shakespeare was born in 1564.'', the relevant token of ''shakespeare'' is meaningful and refers to the poet. what will matter for our purposes below is that the models are (a) trained on largely naturalistic human data to generate text, (b) do not simply verbatim reproduce their training data, and (c) produce text which human users can typically understand. today's llms have these properties: they are trained on human data, generate at least some novel text @xcite , and produce fluent text that human users engage with easily. we highlight three points about philosophical terminology. philosophers often distinguish between ''reference'' and ''meaning''. as we will use the terms here, any expression that refers has a meaning, although many meaningful expressions do not refer. for simplicity, the only words that we will assume can refer are proper names. those unused to this distinction may treat ''meaning'' and ''reference'' as synonymous throughout; nothing essential will turn on the difference between them. second, there is a difference between the word ''shakespeare'' and particular tokens of this word. if the word ''shakespeare'' is written on a blackboard five times, there are five tokens of this one word on the blackboard. words, complex expressions, and strings more generally are types which can occur in multiple ''tokens'', whether in written inscriptions or spoken utterances. we assume that both tokens of words and of longer strings can be meaningful. third, and finally, we distinguish between ''referring'' and ''meaning'' that is done by agents (''marlowe was referring to queen elizabeth.''), and referring and meaning that is done by particular word-tokens. since our goal is to explore a view on which llms are not agents, we will be investigating the question of whether such nonagents can produce tokens which refer and are meaningful. we will not be assuming that llms themselves can refer or mean as agents. ## conclusion according to bibliotechnism, llm-produced tokens must be derivatively meaningful, if they are meaningful at all. bibliotechnism faces a challenge from the fact that llms often produce entirely novel but apparently meaningful text. we responded to this challenge, showing how this novel text may nevertheless be derivatively mean-ingful. but we then described a further challenge for the view, based on the novel reference problem. throughout, we assumed that bibliotechnists would hold that llms transmit cultural knowledge by exploiting linguistic meaning, and hence that they would hold that at least some llm-generated text may have linguistic meaning. but some bibliotechnists might develop the position differently, rejecting the claim that any such text has linguistic meaning. one way of doing so would appeal to what is sometimes called ''natural meaning''. there is a sense in which the presence of smoke ''means'' that there is fire, and @xcite called this sense of ''meaning'', ''natural meaning'' (as opposed to ''non-natural meaning'', of the linguistic kind we have been examining). perhaps a version of bibliotechnism can be developed using this notion of natural meaning instead of the notion of linguistic meaning we have focused on. doing so, though, would require solving several challenges: what is the ''fire'' for which the llm text is ''smoke''? and how would this account handle novel reference? an alternative way of developing bibliotechnism would be to deny that the tokens produced by llms are meaningful at all, even in the sense of natural meaning @xcite @xcite . we believe the theory developed in the first half of this paper makes this option less attractive. we have argued that it is possible to make sense of the meaningfulness of llm-generated text without attributing attitudes to llms, using ideas already required to make sense of the meaningfulness of photocopied text. the appearance of meaningfulness in some text is not decisive evidence in favor of its meaningfulness: word-shapes written by the wind in the sand might appear to be meaningful even though they are not. but the appearance of meaningfulness in a body of text is some evidence in favor of its meaningfulness. our version of bibliotechnism has the advantage, over the approaches just mentioned, of respecting this evidence. a more attractive approach, with which we have some sympathy, would be to endorse bibliotechnism and our account of the meaningfulness of most llm-generated text, while rejecting the claim that putative examples of novel reference are meaningful. this proposal represents a further response to the novel reference problem, which would allow bibliotechnists to preserve a fairly simple version of their position, without the cost of holding that all text produced by llms is meaningless. this response deserves more detailed consideration, but it still requires denying that apparently meaningful text is in fact meaningful. in part ii, we focused on a different response to the novel reference problem. according to interpretationism if the behavior of a system is well explained by the attribution of beliefs, desires, and intentions to the system, then the system in fact has beliefs, desires, and intentions. we suggested that interpretationists will naturally take there to be evidence that llms do have beliefs, desires, and intentions. the problem of novel reference can be easily handled if llms have attitudes, but it cannot be easily handled otherwise. so, it provides some evidence that llms do have beliefs, desires, and intentions. this evidence supports views like interpretationism which attribute attitudes to llms. interpretationism in particular offers a ''light-weight'' understanding of such attitudes, according to which they do not require special inner correlates, sentience, or consciousness. and in fact, we are skeptical of views that ascribe these properties to llms. fundamentally, llms are sophisticated statistical predictors. but attempting to understand their behavior in terms of this fundamental description may in fact impede effectively predicting and explaining them. high-level explanations of complex phenomena are often more useful than micro-scale explanations, as in statistical mechanics or cognitive science @xcite . in the same way, it may prove more illuminating to explain llm behavior at a higher level of abstraction, rather than in terms of their statistical implementation. we have focused on such high-level explanations from philosophy, framed in terms of beliefs, desires, and intentions. tools from cognitive science may similarly be used to understand llms at higher levels of abstraction @xcite @xcite . we expect such high-level approaches to yield new and effective tools for helping us understand llms' sometimes surprising mixture of fluency and fallibility.