Is Language Finished?

A shocking new study demonstrates logic, deduction and inductive reasoning are entirely separate from language.

“Together, these results indicate that linguistic representations are neither utilized nor required for inductive or deductive logical reasoning.” Kean et al 2026

For the past ten+ years Ev Fedorenko has been conducting daring research into the nature of language.

The implications are that language is a strange, illusory appendage that lacks any relationship to reason.

It’s impossible to know where the edges of this reach. If language does not engage logic, reason areas of the brain, can it transmit these?

Fedorenko’s research uses extreme cases of aphasia, subjects who’ve lost entirely verbal communication, who nonetheless exhibit normal levels of deduction, reason, logic. And her early forays demonstrated simply that thought and language were separate. https://pmc.ncbi.nlm.nih.gov/articles/PMC4874898/

Her team then tried to see if LLMs were capable of reintroducing what we imagine thought and reason to be into language models computationally, but found them lacking. https://web.mit.edu/bcs/nklab/media/pdfs/Mahowald.TICs2024.pdf

Her research is extremely surgical, carving up gestures from language, how we perceive and use software code in comparison to language, where syntax and grammar diverge. And the perplexing problem of just what language is, as our problems with using it seem to mount daily in the phenomenon known as post-literacy, the generational collapse of language use. Our social, economic, political chaos may be directly related to our illusory even delusional reliance on language to transmit logical behaviors, deductive reasoning. Something it’s both unable to do and deceives us that is offers these capabilities. Where the edges reach grows day by day.

But possibilities include: nothing in language is valid. The famous symbol-grounding problem where real world meaning feeds through arbitrary symbols may have never been crossed or solved. It never happened, and that would mean many things in terms of A.I. It’s possible that the vanishing role of language takes LLMs with it. LLMs either disprove language or vice versa. That the process of logic, deduction, induction, the foundations of reason are silent, wordless, effects or actions fully separated from language means AI has no access to these processes through symbol, math or language.. And it means importantly that this or these processes precede us in other animals. And we are unable, despite our intelligence, to impart these processes or merge them with language. And if language isn’t reasoning, then it is tacitly interference, impedance, impairment. Only by creating a language of reason do we stand a chance of solving big problems.

The overall evolutionary effect is the echoing shocker that culture is maladaptive, that it leads to our demise. Boyd-Richerson, key evolutionary thinkers, have stressed since the 1990s that this may be the case, and now here is evidence. (here is Colin Allen’s chapter “Culture as Maladaptive” from their 2004 book).

A 2024 Royal Society Philosophical Transactions B issue dealt with the evolutionary problem of extinction and polycrisis, but was unable to find any key correlation to our inability to solve these problems, but of course, a language that can’t communicate logic or reason would obviously take center-stage now. (eg: “Continuities and Discontinuities in the Cultural Evolution of Global Consciousness”)

And this suggests, if logic, reason, deduction are highly successful adaptations, then our species is being bypassed by evolution, since we cannot exapt a language that imparts, shares, transmits these processes externally from our bodies. This is a monumental hitch to our potential survivability. Language may be the niche that extincts us.

Otherwise the only way we might solve climate collapse (insert any major problem) is only by bypassing language.

The question is what kind of mental process that invokes reference in shared signaling as communication can tie into logic, deduction or induction?

That’s the next big thing.

The paper in question:

https://www.pnas.org/doi/10.1073/pnas.2520095123

Pre-print

https://www.biorxiv.org/content/10.1101/2025.07.26.666979v1

Select quotes

“we find that distinct neural systems support language processing vs. logical (inductive and deductive) reasoning. These results establish that language does not underpin logical inference and point to distinct representational systems for the logical LOT.” 2

“a degree of isomorphism between certain thoughts and linguistic expressions need not entail that specifically linguistic representations are used for thinking, any more than the fact that language shares hierarchical structures with music entails that language is the substrate for music.” 3

“empirical data have been accumulating that suggest that linguistic representations are neither utilized nor necessary for thinking.” 3

“developmental psychology and suggests that the timelines of linguistic and logic development diverge. Inductive reasoning capacities appear to come online very early (e.g., Gopnik, 1982; Goddu & Gopnik, 2025). The representations are argued to be sensorimotor, not linguistic, in nature,” 4

“deductive reasoning, the picture is less clear: some have argued that one-year-old preverbal infants can already reason disjunctively (Cesana-Arlotti et al., 2018), which implies a separation of logical and linguistic ability. However, others have reported failures in simple disjunctive inferences as late as age 2.5 years (Mody & Carey, 2016). These late failures may suggest that a certain level of linguistic competence is required for the development of these capacities, but they are also consistent with the slow developmental trajectory of executive abilities” 4

“Critically, the language-processing brain areas show little or no response to the inductive and deductive reasoning contrasts” 6

“Our results showing that the left-lateralized fronto-temporal language network is not engaged in logical induction nor deduction adds to a growing body of evidence for the selectivity of the language network for linguistic computations. In particular, prior studies have evaluated diverse hypotheses about overlap between linguistic processing and different perceptual and cognitive tasks. Some have focused on the socialcommunicative function of language and argued for overlap with other social functions (Grice, 1968, 1975; Sperber & Wilson, 1986), but studies have shown that non-verbal communicative signals, such as facial expressions and gestures, are processed in brain areas distinct from the language network (e.g., Deen et al., 2015; Pritchett et al., 2018; Jouravlev et al., 2019). Others emphasized the hierarchical structure of language and argued for overlap with the processing of other structured stimuli, such as music (Patel, 2003; Fitch & Martins, 2014), but studies have shown that music perception tasks do not engage the language areas (Fedorenko et al., 2011; Rogalsky et al., 2011; Chen et al., 2023). Yet others have argued that language processing requires reliance on domain-general executive resources (Thompson-Schill, 2005; Kaan & Swaab, 2002; Novick et al., 2005, 2014; January et al., 2009), but executive tasks do not engage the language system (Fedorenko et al., 2011; Malik-Moraleda, Ayyash et al., 2022; Hiersche et al., 2024), and demanding linguistic computations are processed within the language network (Blank et al., 2016; Shain et al., 2020, 2022; Quillen et al., 2021; Wehbe et al., 2021; see Fedorenko & Shain, 2021 for a review). Finally, and of greatest relevance to the current investigation, some hypotheses have highlighted the similarity between linguistic structure and structure in some domains of abstract reasoning, such as mathematical or logical thinking (Chomsky, 1957; Marcus, 2001; Carruthers, 2002), or even reasoning in particular domains, such as intuitive physics (McCarthy & Hayes, 1969; Kowalski & Sergot, 1986; Pinto & Reiter, 1993) or social reasoning (de Villiers & de Villiers, 2000). A number of studies have examined the relationship between language processing and these types of reasoning and found no overlap: e.g., mathematical reasoning (Fedorenko et al., 2011; Amalric & Dehaene, 2016; Amalric et al., 2019; for evidence from aphasia, see Varley et al., 2005), computer code comprehension (Ivanova et al., 2020; Liu et al., 2020), physical reasoning (Kean et al., 2025), or social reasoning (Paunov et al., 2019, 2022; Shain, Paunov, Chen et al., 2022; Du et al., 2024; for evidence from aphasia, see Varley & Siegal, 2000; Apperley et al., 2006; Willems et al., 2011). Our study adds to this body of work, showing that formal logical reasoning—including both induction and deduction—does not recruit nor require linguistic representations.” 8

“Why do language processing and logical reasoning dissociate? Despite the fact that language can be used to express complex ideas, the representations and computations that support linguistic processing (i.e., retrieving words from memory and combining them into structured representations) appear to be distinct from those that mediate formal reasoning abilities, such as mathematical and logical reasoning. This dissociation presumably stems from the distinct demands associated with linguistic communication vs. formal reasoning. One key difference may have to do with the kinds of meanings that language vs. these other systems typically express: namely, natural languages tend to express meanings related to the external and internal world, but mathematics, logic, and computer code express mostly abstract, relational meanings that do not available under a CC-BY 4.0 International license. was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made bioRxiv preprint doi: https://doi.org/10.1101/2025.07.26.666979; this version posted July 29, 2025. The copyright holder for this preprint (which bear a direct or necessary connection to the external world (see Malik-Moraleda et al., 2025 for further discussion). Another reason may be that the linguistic format is actually not well-suited for formal reasoning, in spite of superficial similarities in the structured nature of both linguistic expressions and formal logical expressions. In particular, linguistic representations are noisy and ambiguous in ways that make them unreliable for supporting formal inference. Natural language is riddled with referential vagueness, scope ambiguities, and under-specification, requiring pragmatic enrichment, all of which can obscure the logical structure of a sentence. Evidence from AI research shows boosts in LLM performance on reasoning tasks when linguistic inputs are converted into first-order logic, which can then be fed into an external theorem solver (e.g., the LINC system; Olausson, Gu, Lipkin, Zhang, et al., 2024; the SatLM system; Ye et al., 2023; the LogicGuide system; Poesia et al., 2023; the Logic-LM system; Pan et al., 2023; and many others, e.g. Nye et al., 2021; Borazjanizadeh and Piantadosi, 2024). This work suggests that natural language is not a reliable medium for inference, which requires context-independent, structurally explicit representations.” 9

For deeper research, here copious dissections of language and AI are cross-fertilized with Aristotlean non-contradiction: