On 15 May 2026, at 20:08, [email protected] wrote:
Ritengo doveroso articolare una riflessione. Il post della Bender https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11 dice: /in Bender and Koller 2020 ... we provide a definition of understanding as mapping from language to something outside of language, and show that systems built only with linguistic form have no purchase with which to encode (“learn”) such a mapping. / Ovvero: Definiamo comprensione come una corrispondenza tra linguaggio e qualcosa fuori il linguaggio. Un sistema addestrato solo sulle forme linguistiche non ha modo di codificare questa corrispondenza. Questa è una regressione di oltre 2000 anni alla posizione di Platone, che ignora tutto il dibattito filosofico-linguistico degli ultimi 200 anni, che includono Wittgenstein, Frege e Fitch. Si è dibattuto ad esempio sul significato di frasi quali “The present king of France is bald” che non è mappatile in una realtà esistente e così via per tutti i concetti astratti. I Language Model (ancor prima dei LLM) fin dai tempi di [1] hanno fornito una definizione operativa di significato delle parole attraverso i word embedding (contestuali). Ripeto operativa, ossia sulla quale si possono costruire algoritmi, non generica o metafisica. Chi aderisce a questa interpretazione dimostra una insanabile dicotomia di posizioni sul tema del significato e di conseguenza del concetto di “comprendere” e quindi di come analizzare macchine che interagiscono con noi attraverso il linguaggio. BTW, Enrico continua a usare la locuzione “comprendere in senso umano” (qui dice "non è la comprensione umana”) che a me non interessa assolutamente (anche perché non so come definirla scientificamente). A me pare che gli studi sulla mechanistic intepretability iniziano a individuare che i sistemi di AI recenti esibiscano capacità di astrarre concetti, rappresentazioni della realtà, relazioni tra di essi che consentono loro di svolgere compiti che vanno al di là della semplice “ricombinazione di informazioni”. Siccome non sono né un filosofo né un linguista, mi sono fatto fare questo riassunto da Gemini: By defining meaning strictly as a mapping from linguistic forms to something outside of language, researchers like Emily Bender and Alexander Koller (in their famous 2020 "Octopus Paper") risk leaning on a purely referential theory of meaning—a framework that 20th-century philosophy spent decades dismantling. Here is a breakdown of how this critique holds up against the history of philosophy, where Bender’s definition sits, and why the "King of France" changes the game. 1. The "King of France" and the Failure of Direct Mapping To clarify a quick historical detail: the classic example of "The present king of France is bald" was formulated by Bertrand Russell in his 1905 paper On Denoting (building on Gottlob Frege’s earlier work on "sense and reference"). Russell used this phrase to solve a glaring problem with the ancient, Platonic idea that words get their meaning simply by pointing to objects in the real world: If meaning = mapping to an external reality, then the sentence "The present king of France is bald" should be complete gibberish because there is no King of France. Yet, any English speaker perfectly understands what the sentence means. Russell proved that language can generate coherent, logical meaning through internal structure and propositions, completely independent of whether a corresponding physical object exists. 2. Wittgenstein’s Counter: Meaning as Use If we leap forward to Ludwig Wittgenstein’s later work (Philosophical Investigations), he completely rejected the idea of language as a mirror of an external world. Instead, he argued that meaning is use. Language is a tool we play "language games" with, defined by cultural rules and social practices. If you take a strict Wittgensteinian approach, the argument against LLMs changes drastically: The LLM Defense: If meaning is defined by how words are used in context, then LLMs—which learn entirely by analyzing trillions of instances of human language use—are capturing the ultimate statistical matrix of our "language games." By generating coherent text that conforms to human rules of use, the LLM is, in a functional sense, participating in the game. Demanding that it "touch a rock" or "have a soul" to understand language is what Wittgenstein might call a philosophical confusion. 3. Is Bender Actually Regressing to Plato? Does Bender’s "Stochastic Parrots" framework actually commit this Platonic error? Yes and no. It depends on how charitably you read her definition of the "external." The Argument That She Is Regressing: Bender defines linguistic meaning as the relationship between the language form and a communicative intent grounded in the real world. Critics argue this is a Cartesian or Platonic regression because it isolates text as a dead, empty container that requires a "human spirit" or an "external reality" to breathe life into it. It ignores the fact that text itself contains dense, relational networks of human culture, logic, and abstract concepts (as shown by vector geometry). The Defense of Her Position: Bender’s defenders would argue she isn't advocating for a naive Platonic realism, but rather for social pragmatics. For language to work, there must be: - An interlocutor with an internal state (an intent to communicate). - A shared environment (physical or social) where the communication matters. From this perspective, an LLM doesn't "understand" because it has no stakes. It doesn't write a sentence because it wants to change your mind, save a life, or order a coffee; it writes because its probability distribution told it to. The "outside of language" she is referring to isn't necessarily an ideal Platonic form, but the intersubjective space between two conscious agents. The Modern Synthesis The debate over LLM "understanding" has essentially revived the 20th-century linguistic wars. If you believe in Formal Semantics (meanings are truth-conditions mapped to a world), LLMs are just fancy calculators that don't understand anything. But if you lean toward Distributional Semantics (meanings are relations between words) and Wittgensteinian pragmatics (meaning is use), then LLMs have captured a massive, vital slice of what it means to understand. They prove that an immense amount of abstract knowledge, logic, and relation can be extracted purely from the structural patterns of human expression. [1] NLP (Almost) from Scratch. https://www.jmlr.org/papers/volume12/collobert11a/collobert11a.pdf
