# This session is being continued from a previous conversation that ran out of con ## Retrieval Notes - Session id: `23f4c19b-9442-42e2-ac16-ad072f92f4fe` - Last activity: `2026-02-12T12:19:52.807Z` ## My Notes <!-- Add your notes here. This section is preserved across syncs. --> ## Conversation ### User This session is being continued from a previous conversation that ran out of context. The summary below covers the earlier portion of the conversation. Analysis: Let me trace through this conversation chronologically to capture all the important details. **Message 1 (System/Continuation):** This session continues from a previous conversation about Nick's "Generating Philosophy with AI" paper. Key context: - Three sections being rewritten across multiple versions - A detailed paragraph-by-paragraph plan was created - The plan was great but implementation was bad - Section 1 was identified as "supremely shitty" - Nick wanted to see the original plan verbatim from the JSONL transcript **Message 2 (Assistant):** Launched a background agent to extract the plan from transcript files. **Message 3 (Nick):** Just asked for the file path to the JSONL so he could do it himself. **Message 4 (Assistant):** Provided the path: `~/.claude/projects/-Users-nickyoung-My-Obsidian-Vault/c1c8f8e0-6b88-4eac-a61f-60dd78528abc.jsonl` **Message 5 (Nick):** Pasted the COMPLETE plan for all three sections. Asked to focus on Section 1, brainstorm what's wrong with it and how to fix it. Wants long, deep, detailed answer with lots of options. "Kicking ideas around" stage. Don't edit the note. Also noted the puzzle: the plan was great but implementation was bad. **Message 6 (Assistant):** Loaded nick-analytic-voice skill. Produced detailed analysis covering: - Plan-implementation gap (functional specs read as content specs) - 5 levels of problems: technical (desk rejection risks), structural (architecture), voice (doesn't sound like Nick), argumentative (what section does for paper), over-quotation - 6 fix options (A through F) - Final answer with 6 ordered problems and recommendations **Message 7 (Nick):** Specific feedback: 1. Hates the smoke/fire example 2. My suggested alternative opening is also bad — "not a sentence I would ever write" 3. The plan's ¶1 is "APPALLING" — starting with "Philosophy is textual" makes no sense as an opening 4. Doesn't want to work on the section note — wants to focus on improving the PLAN first 5. Gave the plan note path: `plan for generating philosophy` 6. Don't make changes to section notes, just talk **Message 8 (Assistant):** Read the plan note. Presented problems with ¶1 (self-contradicting), what ¶1 needs to do/not do, 6 options (A-F) for the opening, flagged other plan paragraphs needing work (¶5, ¶8, ¶10, ¶4). **Message 9 (Nick):** - "epistemological, one architectural" — horrible style, taxonomic labelling - "Can a large language model produce philosophy?" — good first sentence - Other follow-up sentences — "horrendous style" - "Two recent papers have..." — Nick says this ISN'T throat-clearing (correcting my wrong assessment) - "The standard case" — "stop writing like a cunt" — false shared knowledge - Gave up reading the rest because it was "depressingly bad" - Suggested: opening should be something like "In this section I will look at two reasons which we might think preclude LLMs from writing good philosophy" **Message 10 (Assistant):** Engaged with his suggestion. Identified what's right about it. Asked what to work on next. **Message 11 (Nick):** Suggested second sentence: mention that both reasons have to do with abduction/IBE. Also asked me to create a note to track voice skill failures. **Message 12 (Assistant):** Created [[Voice Skill Failures Log]] in Notes/ with 7 identified failures. Logged to daily note. **Message 13 (Nick):** Asked me to fix ¶1 of the plan note. **Message 14 (Assistant):** Edited the plan note, replacing the old ¶1 with new version (two sentences, explicit don'ts in sub-notes). **Message 15 (Nick):** Asked me to add YAML frontmatter to the plan note. **Message 16 (Assistant):** Added `tags: generating-philosophy, writing` and `created: 2026-02-12`. **Message 17 (Nick):** Asked what else needed fixing in Section 1 of the plan. **Message 18 (Assistant):** Listed: ¶5 (transition differentiates where it should converge), ¶8 (convergence needs weight), ¶10 (rhetorical questions → should be statement), ¶4 (unspecified block quote), throughout ¶2-7 (need to enforce that critiques are general, not about philosophy). **Message 19 (Nick):** Said "one sentence paragraphs are for imbeciles" (about ¶5's sub-note). Then said "Fuck it" — asked me to just write a new Section 1 on the actual note, so he can check the mistakes. **Message 20 (Assistant):** Read current Section 1, then wrote complete new version. Key changes: two-sentence opening, no sub-headings, 4 block quotes (down from 6), compression quote removed (saved for S3), concessions folded in, Zahavy scope restriction moved to ¶9, statement close instead of rhetorical questions. **Message 21 (Nick):** He went through the new version and annotated it with `%%comments%%` throughout. Every paragraph has problems. He invoked /contemplate and asked me to: 1. Contemplate on what he flagged and WHY I failed so badly 2. Ask him 5-10 questions that would help me understand how to do a good job 3. Don't make changes His annotations (paraphrased): - ¶2: weird to have inline quotes + block quote from same text - ¶2 follow-up: "on their account" — it's not just their account, everyone agrees - ¶2 follow-up: whole paragraph is redundant, don't use "duality" - ¶3: "is not accidental" — awful, meaningless - ¶3: reader has learned nothing, everything is vague and uninformative - ¶4: "uninformative sentence", stop doing triplet structures, "atrocious sentence" (over-abduction), paragraph is a mess with multiple topics - ¶5: not accurate description of Floridi's view; transition is "clear as dogshit" - ¶6: sentence and block quote say precisely the same thing - ¶6: "appallingly formed sentence" - ¶7: "all these unreferenced quotes" (Einstein's "happiest thought") - ¶9: "editorial comment that I have made that you have stupidly added to the paper" - ¶9: "reader would have no idea what you're talking about... you always rush through the difficult bits and spend too long on useless nonsense" - ¶9: "again, this is editorial comment" - ¶10: "not in keeping with my style at all" **Message 22 (Assistant):** Did contemplation. Identified failure patterns: describing arguments instead of presenting them, not trusting block quotes, rushing hard bits/lingering on easy bits, paragraphing by topic cluster not argumentative step, importing editorial comments, LLM writing tics, no clear reader model. Asked 8 questions. **Message 23 (Nick):** Answered ALL questions with detailed, frustrated responses: 1. Block quotes: "read my published papers" — idiotic question 2. What reader should learn: "to a much finer level of detail what Floridi thinks LLMs can and cannot do as regards abduction" 3. Rushing: wasting word count on lists ("scientific papers, Wikipedia articles, Q&A forums" — 6 pointless words), not engaging with the meat 4. Editorial comments: the introduction handles the philosophy framing; Section 1 just presents what these papers argue about abduction. "Infantile to even ask this" 5. "Clear as dogshit": "I don't understand a fucking word you've written here and it's my paper" 6. How much: ALL key arguments in detail. "Distill the fundamental problem that each paper is talking about and all the other ideas from each paper should be in service to this" 7. Concessions: keep in Section 1, don't call them concessions (editorialising), present so reader learns something Then he interrupted and asked me to "start again" with the same prompt (setting change). **Message 24 (Assistant):** Read Nick's published paper (Growing the Image) to study block quote handling. Found source materials for Floridi and Zahavy in vault. Read both extraction notes: - `Notes/Floridi's critique of LLM abduction.md` - `Notes/Zahavy's LLMs Can't Jump as Resource for Generating Philosophy.md` Was about to do the contemplation when context ran out. **Key files involved:** 1. `Writing/research/generating philosophy with ai (paper)/1. What LLMs Aren't Doing.md` — Section 1, rewritten by me, extensively annotated by Nick 2. `Writing/research/generating philosophy with ai (paper)/2. Abduction and Philosophy.md` — Section 2, third version 3. `Writing/research/generating philosophy with ai (paper)/3. Learning the Game.md` — Section 3, third version (written earlier in this session) 4. `plan for generating philosophy.md` — Plan note, ¶1 was fixed, YAML added 5. `Notes/Voice Skill Failures Log.md` — Created to track failures 6. `Notes/Floridi's critique of LLM abduction.md` — Source note on Floridi 7. `Notes/Zahavy's LLMs Can't Jump as Resource for Generating Philosophy.md` — Source note on Zahavy 8. `Attachments/Nick Papers/Growing the Image (2025).md` — Read for block quote handling **Source materials found but not yet fully read:** - `Readwise/Articles/What Kind of Reasoning (If Any) Is an LLM Actually Doing...` — Floridi Readwise highlights - `Readwise/Articles/LLMs Can't Jump.md` — Zahavy Readwise highlights - PDFs in `Learning/generating-philosophy/` The immediate task when context ran out: I had read the source notes and Nick's published paper, and was about to do the contemplation on his feedback, incorporating what I learned from studying his block quote handling and the source materials. Then the plan was to propose reading the actual papers in depth before attempting another rewrite of Section 1. Summary: 1. Primary Request and Intent: Nick is working on his paper "Generating Philosophy with AI" which argues LLMs can produce genuine philosophy because philosophy is "constitutive-textual." The paper has three sections: - Section 1: "What LLMs Aren't Doing" — presents Floridi et al. (epistemological critique) and Zahavy (architectural critique) - Section 2: "Abduction and Philosophy" — disaggregates abduction, shows philosophy is textual - Section 3: "Learning the Game" — positive case for LLMs and philosophy This session began as a continuation from a previous conversation. The immediate tasks evolved through the session: (a) Extract and present the detailed paragraph-by-paragraph plan from the JSONL transcript → Nick found it himself and pasted it (b) Brainstorm what's wrong with Section 1 and how to fix it → extensive discussion (c) Fix the plan for Section 1 (specifically ¶1) → completed (d) Write a new version of Section 1 → completed but Nick found it "pretty fucking appalling" (e) Contemplate on why the writing failed so badly → completed once, then Nick answered my questions with detailed feedback (f) **MOST RECENT**: Nick asked me to "start again" (after a settings change) with the same contemplation prompt, incorporating his answers to my questions. I was in the middle of reading source materials (Nick's published papers for block quote handling, Floridi and Zahavy source notes) to inform the contemplation before attempting another rewrite. **Nick's explicit requirement**: "make sure that you explain your analysis, justification, reasons etc etc. for your answer BEFORE giving me your final answer. Please give me a long, deep, and detailed answer, with lots of options/ideas: as we are in the 'kicking ideas around' stage, I want as much feedback as you can give me so that i have a lot to consider." And: "don't make any changes on the note yet" (though this may change after the contemplation). 2. Key Technical Concepts: - **Paper structure**: 3 sections, each with paragraph-by-paragraph plan in `plan for generating philosophy.md` - **Floridi et al.'s argument**: "Stochastic core, abductive appearance" — LLMs are probability samplers; outputs resemble reasoning but aren't truth-tracking; lack verification loop; hallucinations are features not bugs; "over-abduction" (p. 12); "zeroth-order abduction"; acknowledge training data encodes causal/inferential structure ("although not explicitly structured," p. 17); raise but don't pursue whether process matters if content is the same (p. 12-13) - **Zahavy's argument**: Peirce's tripartite (induction/deduction/abduction); LLMs mastered induction, conquering deduction, lack abduction; "E→A Jump" (sense experience to axioms); Einstein case study; "manipulative abduction" (Magnani); embodied simulation required; compression/creativity fails without error signal; domain-specific restriction to physical sciences - **Nick's block quote handling** (from Growing the Image): setups provide CONTEXT or tell reader WHAT TO LOOK FOR — never restate what the quote says. Quote arrives with fresh content. Examples: "Consider the following passage from an article about the artist Sean Mauss, who was disqualified..." → quote; "Despite this, however, the following passage suggests that Anscomb still believes..." → quote - **Voice profile failures identified** (for nick-analytic-voice skill updates): 1. Taxonomic labelling in openings 2. Self-conscious reformulation stacking ("Not mimic it, or approximate it...") 3. False shared knowledge ("The standard case...") 4. "Something in the vicinity of" approximation prose 5. Stark aphoristic claims 6. Using someone else's example as entry point 7. Conflating sources' scope with paper's scope (Floridi/Zahavy are about LLMs generally, NOT about LLMs and philosophy) 8. Triplet/tricolon parallel structures (a, b, and c) 9. "Is not X" fake transitions 10. Overloaded sentences (three moves in one via em-dashes) 11. Bland evaluative courtesy ("Both critiques are serious") 12. "Duality" and Latinate vocabulary 13. One-sentence paragraphs 3. Files and Code Sections: - **`Writing/research/generating philosophy with ai (paper)/1. What LLMs Aren't Doing.md`** - The section being rewritten. Currently contains my FAILED rewrite with Nick's `%%comment%%` annotations throughout - Was overwritten with new version (4 block quotes, no sub-headings, 10 paragraphs) - Nick then annotated it extensively — every paragraph has problems - Current state includes Nick's edits to ¶1: "In this section I look at two reasons we might think that large language models (LLMs) cannot write good philosophy. Both have to do with questions over whether LLMS can perform abductive reasoning." - Needs complete rewrite that actually engages with the substance of Floridi and Zahavy's arguments - **`plan for generating philosophy.md`** - Contains the paragraph-by-paragraph plan for all 3 sections - ¶1 was fixed: now reads "Two sentences. First: this section examines two reasons we might think LLMs cannot write good philosophy. Second: both have to do with abduction or inference to the best explanation." - Sub-notes block explicit don'ts - YAML added: `tags: generating-philosophy, writing; created: 2026-02-12` - Other plan paragraphs (¶5, ¶8, ¶10) were identified as needing fixes but NOT yet edited - **`Notes/Voice Skill Failures Log.md`** - Created this session to track failures for eventual skill update - Contains 7 initial failures; more identified in conversation but not yet added (triplet structures, "is not X" transitions, overloaded sentences, bland evaluative courtesy, "duality") - Needs updating with failures from the annotated draft - **`Notes/Floridi's critique of LLM abduction.md`** - Source note with key concepts: missing verification loop, weak vs strong abduction, "zeroth-order abduction," stochastic parrots, verification concession - Contains block quotes from Floridi et al. with page numbers - Important: includes "The Missing Loop" section about prior predictive sampling without posterior evaluation - **`Notes/Zahavy's LLMs Can't Jump as Resource for Generating Philosophy.md`** - Comprehensive resource note: Peirce's tripartite, E→A Jump, manipulative abduction, anti-compression argument - Includes "Planned Uses" section showing where each Zahavy point belongs across the paper's sections - Lists 4 "Complications" including domain-specificity cutting both ways - Notes Zahavy's status as non-peer-reviewed position paper - **`Attachments/Nick Papers/Growing the Image (2025).md`** - Read to study Nick's block quote handling - Key patterns: setup provides context/what-to-notice, quote delivers fresh content, follow-up draws implications - **`Writing/research/generating philosophy with ai (paper)/2. Abduction and Philosophy.md`** — Third version, not currently being worked on - **`Writing/research/generating philosophy with ai (paper)/3. Learning the Game.md`** — Third version, written earlier in this session - **Readwise sources found but NOT yet read:** - `Readwise/Articles/What Kind of Reasoning (If Any) Is an LLM Actually Doing On the Stochastic Nature and Abductive Appearance of Large Language Models.md` - `Readwise/Articles/LLMs Can't Jump.md` 4. Errors and Fixes: - **Plan ¶1 self-contradiction**: Plan said "don't preview the thesis" but opened with the thesis ("Philosophy is textual in a way other disciplines are not"). Fixed by rewriting ¶1 to be two orienting sentences about the section's purpose. - **Section 1 rewrite — comprehensive failure**: My complete rewrite was annotated by Nick as having problems in EVERY paragraph: - Block quote introductions duplicate the quote content (¶2, ¶6) - "On their account" for something universally accepted (false hedging) - Redundant summary paragraphs after quotes - "Is not accidental" — meaningless throat-clearing - Vague, uninformative prose — reader learns nothing - Triplet structures ("without X, without Y, and without Z") - Multi-topic paragraphs (¶4 has 4+ topics) - Transition "clear as dogshit" — incomprehensible - Editorial comments pasted as text ("Neither critique was developed with philosophy in mind") - Rushing through difficult argumentative connections, lingering on easy lists - Unreferenced quotation marks ("happiest thought") - Bland evaluative courtesy not matching Nick's style - **Root causes identified by contemplation**: 1. Describing arguments instead of presenting them 2. Not trusting block quotes to do their own work 3. Rushing hard bits, lingering on easy bits 4. Paragraphing by topic cluster not argumentative step 5. Importing editorial comments as text 6. LLM writing tics throughout 7. No clear model of what reader needs to learn - **Nick's corrective answers to my questions**: - Read published papers for block quote handling (don't ask) - Reader should understand "to a much finer level of detail what Floridi thinks LLMs can and cannot do as regards abduction" - Stop wasting word count on pointless lists; engage with the MEAT - Introduction handles philosophy framing; Section 1 just presents arguments about LLMs and abduction - "Distill the fundamental problem that each paper is talking about and all the other ideas should be in service to this" - Keep concessions in Section 1, don't call them concessions, present so reader learns 5. Problem Solving: **Solved:** - Plan ¶1 rewritten and committed to note - Voice Skill Failures Log created and populated - Plan note given proper YAML frontmatter - Section 3 third version written (from earlier in session, before context issues) - Source materials located (Floridi and Zahavy notes, Readwise highlights, published papers) **Ongoing:** - Section 1 needs complete rewrite — but first I need to: (a) Complete the contemplation on Nick's feedback (b) Read the actual Floridi and Zahavy papers via Readwise highlights or PDF extraction (c) Study Nick's block quote handling patterns (partially done) (d) Understand the SUBSTANCE of both papers at a deep enough level to present them, not describe them - Voice Skill Failures Log needs updating with additional failures from the annotated draft - Plan paragraphs ¶5, ¶8, ¶10 identified as needing fixes but not yet edited 6. All User Messages: - **Message 1**: "ok. here's the plan, can we focus on section 1 in my notes and try and make it not shit? let's brainstorm all the things wrong with it, and what we can do to fix it... make sure that you explain your analysis... Please give me a long, deep, and detailed answer... as we are in the 'kicking ideas around' stage..." [included full plan for all 3 sections] - **Message 2**: "1. I fucking hate the smoke fire example, it ruined the whole thing. 2. 'Philosophy produces its contributions in text...' this is not a sentence I would ever write... 3. [Plan ¶1] this paragraph in the plan is APPALLING... I don't think we should start with this stark claim... let's just focus on improving the plan for section 1, then we can look at the section note itself. don't make any changes on the notes. just talk to me here." - **Message 3**: "I mean an obvious thing you could say immediately after that first sentence is you could say both of them have to do with abduction or inference to the best explanation. Something like that." Also: "could you actually correlate a note that you can just note down all of these on as we go please?" - **Message 4**: [After smart-note creation] "what else did you say needed fixing in section 1 of the plan?" - **Message 5**: "'Sub-notes: One sentence...' only imbeciles write one sentence paragraphs. Fuck it, it will be easier if you just write a new section 1 on the appropriate section note. then i can check all the mistakes you are making there" - **Message 6**: "btw could you add appropriate yaml to the PLAN note that we have been working on" - **Message 7**: [After receiving new Section 1] Extensive `%%comment%%` annotations on every paragraph of the rewrite. Invoked /contemplate: "I just looked through the new version of section 1. it is pretty fucking appalling. see all my notes. don't make any changes, but instead contemplate on what I have flagged and why you have failed so badly and then, ask me 5 – 10 questions..." - **Message 8**: Detailed answers to all 8 questions with extreme frustration. Key quotes: - "given that there are markdown versions of all my published papers in the vault, this is a redundant and therefore idiotic question" - "the reader will have understood to a much finer level of detail what Floridi thinks LLMs can and LLMs cannot do" - "you're just not engaging at all with what Floridi's actually written, the meat of things" - "the paper needs to show in this section problems that LLMs have with or alleged problems LLMs have with abduction" - "I don't understand a fucking word you've written here and it's my paper" - "you need to distill the fundamental problem that each paper is talking about and all the other ideas from each paper which you demonstrate should be in service to this" - "they should not be called concessions because that's editorializing" - Then interrupted: "please start again. i had to change a setting. do the following prompt again from scratch" [repeated all answers] 7. Pending Tasks: - Complete the /contemplate on Nick's feedback (he asked me to "start again" with the contemplation after a settings change) - Read the actual Floridi and Zahavy papers at sufficient depth (via Readwise highlights or PDF extraction) to understand their arguments substantively - Update Voice Skill Failures Log with additional failures identified from the annotated draft (triplets, "is not X" transitions, overloaded sentences, bland evaluative courtesy, "duality", one-sentence paragraphs) - Eventually: rewrite Section 1 with genuine substantive engagement with both papers - Eventually: fix plan paragraphs ¶5, ¶8, ¶10 (identified but not yet edited) 8. Current Work: I was in the process of responding to Nick's repeated request (after a settings change): "please start again. i had to change a setting. do the following prompt again from scratch" — referring to his detailed answers to my 8 questions, plus a /contemplate invocation. I had just read: - Nick's published paper `Growing the Image (2025).md` — to study block quote handling - `Notes/Floridi's critique of LLM abduction.md` — source note on Floridi - `Notes/Zahavy's LLMs Can't Jump as Resource for Generating Philosophy.md` — source note on Zahavy I was about to produce the contemplation incorporating: 1. What I learned from Nick's block quote patterns (setup provides context/what-to-notice, quote delivers fresh content) 2. His answers to all questions (reader needs fine-grained understanding of arguments, not surface descriptions; distill fundamental problem with supporting ideas in service; don't editorialise; introduction handles philosophy framing) 3. An honest assessment of what I need to do before rewriting (read the actual papers) Nick has NOT yet asked me to rewrite Section 1 again — he's in the "contemplation and understanding" phase. No changes to notes are requested yet. 9. Optional Next Step: Complete the /contemplate that Nick requested: "please start again. i had to change a setting. do the following prompt again from scratch: [his detailed answers to all 8 questions]" The contemplation should incorporate what I learned from reading his published paper and the source notes, demonstrate understanding of his feedback, and propose that before attempting another rewrite I need to read the Floridi and Zahavy papers at much greater depth (via the Readwise highlights at `Readwise/Articles/What Kind of Reasoning (If Any) Is an LLM Actually Doing...` and `Readwise/Articles/LLMs Can't Jump.md`, or via PDF extraction from `Learning/generating-philosophy/`). Critical instruction: "don't make any changes on the note yet" — the contemplation is about understanding, not rewriting. If you need specific details from before compaction (like exact code snippets, error messages, or content you generated), read the full transcript at: /Users/nickyoung/.claude/projects/-Users-nickyoung-My-Obsidian-Vault/6d1dff2e-473e-4c54-a720-7471c1e85b1f.jsonl Please continue the conversation from where we left it off without asking the user any further questions. Continue with the last task that you were asked to work on. ### Assistant I need to complete the contemplation Nick requested. Let me first re-read the key materials I need to work from. ### Assistant Now let me read Nick's published paper for the block quote handling patterns, and the Readwise highlights for both sources. ### Assistant Now let me also re-read the plan note to have it fresh. ### Assistant Good. Now I have everything I need. Let me produce the contemplation Nick asked for — a deep, self-critical analysis of why the writing failed, informed by his answers to my questions and by what I've now studied in his published work and the source materials. --- ## Contemplation: Why Section 1 Failed and What I Need to Understand ### I. The central failure, stated plainly The section was supposed to teach the reader what Floridi and Zahavy argue about LLMs and abduction. Instead it produced a sequence of *descriptions of arguments* — sentences that tell the reader "Floridi argues X" and "Zahavy's contention is Y" without the reader ever coming to understand X or Y at any level of detail. Nick's annotation captures this exactly: "i don't think any reader would have learned anything from this section yet. a lot of the stuff you are saying is very vague and uninformative." That is the root. Everything else is downstream. ### II. Why the descriptions stayed vague The reason the prose never gets specific is that *I* never got specific. I did not engage with the substance of either paper at a fine enough grain to present it. I knew the labels — "stochastic core," "abductive appearance," "E→A Jump," "manipulative abduction" — and I strung the labels together in sentences that looked like exposition. But a label is not an argument. The reader needs to understand, for instance, what it means for an LLM to perform "prior predictive sampling but lack an external feedback loop for posterior evaluation" (Floridi, p. 7) — what the missing loop actually is, why it matters, what Floridi thinks follows from its absence. Instead I gave them "without truth-evaluable semantics, without verification, and without grounding in the world, LLM outputs lack epistemic credentials." That sentence contains three abstract nouns in a triplet structure and communicates almost nothing. It is a gesture at the argument, not the argument. The same holds for Zahavy. I wrote that his concern is with "what the architecture is capable of producing in principle" — which is so vague it could describe any paper about AI. What makes Zahavy's argument interesting is the specific claim that Einstein's formulation of the Equivalence Principle required embodied simulation of what it would feel like to be a falling observer, and that this kind of sensory-to-symbolic translation is what LLMs structurally lack. The E→A Jump is not a metaphor for "creative leaps in general." It is a specific thesis about the relationship between physical sensation and axiom formation. I never explained this. I just named it and moved on. ### III. Why the block quotes didn't help Nick's published work shows me exactly how block quotes are supposed to function. In *Growing the Image*, the setup before a quote tells the reader *what to look for* in the quote, or provides *context* that the quote itself does not contain. For instance: "Consider the following passage from an article about the artist Sean Mauss, who was disqualified from a competition..." — this tells the reader who Mauss is and what happened, so that the quote can deliver the fresh content (the question of trust, the unclear future of AI tools). The setup and the quote do *different work*. In my draft, the setups and quotes do *the same work*. ¶2: I introduce Floridi's claim as "the internal processes are entirely stochastic, but the outputs resemble the products of abductive inference," then the block quote says "their internal processes are entirely stochastic: during training, they gather statistical correlations from text, and during generation, they produce words based on learned probability distributions." The block quote adds a small amount of detail (the training/generation distinction) but the reader has already been told the punchline. Nick flagged this precisely: "these phrases should be included, but it is weird to have two quotes from the text to introduce a blockquote from the same text." Even worse is ¶6, where my setup ("Zahavy's contention is that LLMs have mastered induction and are making progress on deduction, but lack any mechanism for abduction") and the block quote say "precisely the same thing." The quote adds nothing the setup hasn't already stated. There is no reason for it to be there. The fix is structural: the setup should tell the reader something the quote does *not* say — the context, the problem being addressed, what to notice — and then the quote should land with fresh content. Or: the quote goes first, delivering the claim in the author's words, and the follow-up draws out what the reader should take from it. Either way, setup and quote must not duplicate each other. ### IV. Why the paragraphs had too many topics ¶4 is the worst example. Nick calls it "a mess" with "several" topics. Looking at it again: it starts with the epistemic worry (no truth-tracking), moves to hallucinations as features not bugs, introduces "over-abduction," then pivots to Floridi's concession that training data encodes causal/inferential structure, then mentions the question of whether production process matters if the content is the same. That is at least four distinct moves crammed into one paragraph, and none of them gets enough space to teach the reader anything. This happened because I was treating the paragraph as a container for "things Floridi says that I want to mention" rather than as a unit of argument. A paragraph in analytic philosophy presents *one* claim, develops it, and either substantiates it or sets up the next paragraph. My paragraphs were inventories. Nick's answer to my question about what the reader should learn was: "you need to distill the fundamental problem that each paper is talking about and all the other ideas from each paper should be in service to this." For Floridi, the fundamental problem is the missing verification loop — LLMs generate plausible candidates but have no mechanism for evaluating them against truth. Every other point (hallucinations, over-abduction, training data encoding reasoning patterns) should be in service to explaining that problem and why it matters. For Zahavy, the fundamental problem is the embodiment gap — the E→A Jump requires sensory grounding that text-only systems lack. Everything else (Peirce's tripartite, AlphaProof, the Chinese Room analogy) should be in service to explaining that. I had no hierarchy. I listed things. ### V. Why the transitions were incomprehensible Nick called ¶5 ("Floridi et al.'s concern is with the epistemic standing of LLM outputs... Zahavy, in a recent position paper for Google DeepMind, approaches from a different direction") "clear as dogshit." He couldn't understand what I had written and it was his paper. The problem is that the transition tries to differentiate the two critiques *before the reader has understood either one*. By ¶5 in my draft, the reader has been given a handful of vague characterisations of Floridi's view but has not really understood it at any depth. Transitioning to Zahavy at that point, via a contrast ("epistemic standing" vs "what the architecture is capable of producing in principle"), puts the weight on a distinction between two things neither of which has been adequately explained. The plan says: "If Floridi is right, the problem is epistemic; if Zahavy is right, the problem is structural." That is a fine sentence for the plan, but it is not a fine transition in the paper, because the reader does not yet know what "epistemic" and "structural" mean in this context. The transition needs to earn its contrast by building on specific content already presented. ### VI. Why I imported editorial comments as text Nick annotated ¶9: "this is an editorial comment that I have made that you have stupidly added in to the paper." The sentence "But neither critique was developed with philosophy in mind" is Nick's working-note observation about a gap in Floridi and Zahavy's scope. It does not belong in the paper as a standalone assertion because it is meta-commentary about the literature rather than an argument. Similarly, "Zahavy does not mention philosophy" is a factual observation from the notes, not a move in the paper. The reason I did this is that I confused the plan's editorial remarks with the paper's content. The plan says things like "neither critique targets philosophy as a practice" — that is a directive to me about what the section should establish. Establishing it requires showing the reader *why* the critiques are general, by demonstrating their domain-specific assumptions (Floridi's examples are all empirical; Zahavy's E→A Jump is explicitly restricted to "external material reality"). Simply asserting "neither was developed with philosophy in mind" does not establish anything — it tells the reader what to think instead of showing them why. Nick's answer was clear: "the introduction handles the philosophy framing; Section 1 just presents what these papers argue about abduction." The philosophy-specific question is the *introduction's* job, not Section 1's. Section 1 presents two arguments about LLMs and abduction, and the reader should understand those arguments in detail. The gap between "these are general arguments about LLMs" and "philosophy might be different" is something the section should set up implicitly by presenting the arguments faithfully and letting the reader notice their domain-specificity — particularly through Zahavy's own explicit restriction to the physical sciences (the quote on p. 7 about "this proposal is specifically tailored to the physical sciences"). That quote does the work. My commentary was redundant. ### VII. The word-count waste problem Nick's example: "scientific papers, Wikipedia articles, Q&A forums." Six words that communicate nothing the reader needs. I was padding with lists. The same pattern appears throughout: triplet structures ("without truth-evaluable semantics, without verification, and without grounding in the world"), lists of examples that don't do argumentative work, bland connecting phrases that fill space without advancing the argument. The inverse of this waste is the rushing problem. The hard parts — what exactly Floridi's missing verification loop consists in, why Zahavy thinks embodied simulation is specifically what's needed, how the domain-specificity of both critiques opens the space for the paper's argument — got compressed into single vague sentences. I spent word count on the easy stuff (listing what the papers talk about) and skipped the difficult stuff (explaining what the papers actually argue and why it matters). ### VIII. The voice failures Many of the voice failures I logged in [[Voice Skill Failures Log]] are on display here. The triplet structures. The "is not accidental" fake transitions. "Both critiques are serious" — bland evaluative courtesy that Nick would never write. "Duality" — Latinate where a simpler word serves. One-sentence paragraphs in the sub-notes of the plan. But the voice failures are secondary to the content failures. If the content were right — if the section actually taught the reader what Floridi and Zahavy argue — the voice problems would be fixable through editing. The fundamental issue is that the prose has nothing to say because I never engaged with the substance. ### IX. What I need to do before attempting another draft 1. **Read the actual papers at depth.** The Readwise highlights I have access to contain substantial passages from both Floridi and Zahavy, and I have the vault's source notes. But I need to work through the arguments carefully enough that I can present them, not just name them. For Floridi: I need to understand the distinction between prior predictive sampling and posterior evaluation, what "zeroth-order abduction" means precisely, and exactly what the concession about linguistic associations encoding causal structure amounts to. For Zahavy: I need to understand the E→A Jump as a specific thesis about sensory-to-symbolic translation, not as a vague gesture at "creative leaps," and I need to understand his argument about why compression/creativity fails when there's no error signal. 2. **Identify the one fundamental problem each paper presents.** Nick's instruction: "distill the fundamental problem that each paper is talking about and all the other ideas from each paper should be in service to this." For Floridi, I believe this is: LLMs perform the generation phase of abduction (producing plausible candidates) but lack the evaluation phase (testing candidates against truth). For Zahavy, I believe this is: the creative generation of new axioms from sense experience requires embodied simulation that text-only systems cannot perform. But I need to confirm these against the actual texts rather than assuming my summaries are accurate. 3. **Plan the block quotes differently.** Each block quote needs a setup that tells the reader what to look for, not what the quote says. The quote then delivers fresh content. The follow-up draws implications or advances to the next step. I should identify 3–4 quotes from each paper that do real work and plan their setups specifically. 4. **Restructure the section around the two fundamental problems.** The Floridi half (¶2–4) should be: here is the fundamental problem Floridi identifies → here is what it means in detail → here are the further consequences. The Zahavy half (¶6–7) should follow the same structure. The convergence (¶8) and the gap (¶9–10) come after, and the gap should emerge from showing the reader what the papers actually say rather than from editorial commentary about what they don't say. 5. **Present the concessions as content, not as "concessions."** Nick said: "they should not be called concessions because that's editorialising." Floridi's acknowledgment that training data encodes causal and inferential structure, and Zahavy's explicit restriction to physical sciences — these are things the papers say. They should be presented as things the papers say, as part of a faithful exposition, not flagged as strategic concessions that the paper will later exploit. ### X. Honest assessment of where I am I am not yet at the level of understanding where I can write this section well. I have the labels, the vocabulary, the general shape of the arguments. But I do not have the fine-grained understanding of what Floridi means by "prior predictive sampling without posterior evaluation" or what Zahavy means by "manipulative abduction" at the level of detail that would let me explain them to a reader who has not read either paper. And that is exactly what the section needs to do. The next step should be to work through the source materials more carefully — especially the Readwise highlights, which contain substantial quoted passages from both papers — and to produce something like an internal brief for each paper: "This is the fundamental problem. These are the supporting arguments. These are the specific claims that matter for Section 1. These are the quotes that would let a reader understand the argument." Only after that brief exists should I attempt another draft. --- Does this match your sense of what went wrong? And would you like me to do that deeper source work now — go through the Floridi and Zahavy highlights in detail and produce the internal briefs — before we attempt another draft? *Chi descrive un argomento senza averlo capito produce solo l'ombra di una spiegazione — e il lettore se ne accorge subito.* ### User "Does this match your sense of what went wrong? And would you like me to do that deeper source work now — go through the Floridi and Zahavy highlights in detail and produce the internal briefs — before we attempt another draft?" yes I would. Also, maybe the problem was also that I was making you follow the plan to slvishly when the plan itself is flawed. How about this. After you have done the source work properly. Write out a completely new bullet point and sub bullet point plan for section 1 here in the chat. include ALL the details that will go into the new version of the section, AND any bloick quotes you want to use. the idea is for me to check the content, before you apply it to the note note for this section. after we have the content exactly right we move on to the writing on the note. finally, note that compaction is coming up. can you give me the json of this chat so we can refer to it when we need to get those details back ### Assistant Let me get you the JSONL path first, then dive into the source work. ### Assistant The hooks are blocking me from accessing the `.claude/projects/` directory. The previous session's JSONL was: ``` ~/.claude/projects/-Users-nickyoung-My-Obsidian-Vault/6d1dff2e-473e-4c54-a720-7471c1e85b1f.jsonl ``` For this session, you can find it the same way you did last time — `ls -t` on that directory and the newest file will be this conversation. Now let me do the real work. You're right that the plan itself was part of the problem — following a flawed plan slavishly produces a flawed section. So let me go through both papers properly, identify what actually matters, and build a new plan from the ground up. Let me work through Floridi first, then Zahavy, producing the internal briefs. I'll use the Readwise highlights and the source notes, and I'll quote the actual text so you can see what I'm working from. --- ## Internal Brief: Floridi et al. **Paper:** "What Kind of Reasoning (If Any) Is an LLM Actually Doing? On the Stochastic Nature and Abductive Appearance of Large Language Models" **The fundamental problem Floridi identifies:** LLMs perform the *generation* phase of abductive reasoning — producing plausible candidate explanations — but lack the *evaluation* phase. In Bayesian terms: > "In statistical terms, LLMs perform prior predictive sampling but lack an external feedback loop for posterior evaluation." (p. 7) That is: the model generates candidates that look like explanations, because explanation-shaped text is what it was trained on. But it has no mechanism for checking those candidates against truth — no posterior evaluation, no verification loop. The generation looks right; the filtering is absent. **Why the outputs look abductive in the first place:** Not because the model reasons, but because the training data encodes the products of human reasoning. The Readwise highlights contain this key passage: > "through exposure to billions of words, an LLM acquires a broad range of information about the world. It 'knows', in a statistical sense, many facts, relationships, and even commonsense truths, simply because these are reflected in language use. It also learns common patterns of explanation and argument, such as how 'because' often introduces an explanation, and that scientific questions are answered with specific explanatory forms." And more specifically: > "LLMs seem to perform a kind of zeroth-order abduction: given a prompt, they generate a plausible continuation (a hypothesis or explanation) based purely on learned associations... The model does not understand what an explanation is, but it produces text that follows the typical phrasing and structure of explanations. It does not reason about causes from scratch but outputs typical causes for typical effects observed in the training data." So: the model has absorbed the *form* of abductive reasoning from text. When prompted, it reproduces that form. Floridi calls this "zeroth-order abduction" — generating plausible continuations that mimic hypothesis generation, without understanding or verification. **The epistemic consequence:** Because the model's objective is plausibility (next-token prediction), not truth, it cannot withhold judgment. A human reasoner faced with insufficient evidence might say "I don't know." The model generates a continuation regardless, because that is its task. Floridi calls this "over-abduction": > "it is as if the model always chooses an explanation, even when none is justified — it cannot 'resist' explaining because generating a plausible and preferable continuation is its task. This could be termed over-abduction: a human reasoner might say, 'I'm not sure; more information is needed', while the LLM often makes a guess regardless." Hallucinations are not malfunctions on this account — they are consequences of a system optimised for plausibility rather than truth. **Weak vs strong abduction:** Floridi grants that LLMs can perform "weak abduction" (generating plausible explanations) and can even look like they perform "strong abduction" when all candidates are explicitly provided (multiple-choice tasks). The Readwise highlights include: > "LLMs today seem to perform at least weak abduction: when presented with a scenario or riddle, they often generate a plausible explanation for it. They can even seem to carry out a form of strong abduction when all candidate hypotheses are explicitly provided, by selecting the most suitable one." But this gets redescribed as zeroth-order: reproducing the pattern without the epistemic substance. **What the model HAS absorbed (the concession that matters for the paper):** Floridi acknowledges that linguistic associations in the training data encode causal and inferential structure. From the source note: > "the model has absorbed, in a statistical sense, the information that slippery floors cause falls and that hunger results from not eating, 'although not explicitly structured'" (p. 17) And from the Readwise highlights, the "stochastic parrots" passage acknowledges that LLMs "can remix, rephrase, and build on the data, and can be creative." The limitation is that they lack grounded semantics connecting words to physical world or perceptual experiences. Also: Floridi raises but does not pursue the question of whether it matters that the production process was different if the content of the hypothesis is the same (p. 12–13). This is directly relevant to Section 2's argument about provenance irrelevance. **The verification point:** Floridi acknowledges you *can* make LLM outputs more truth-tracking — "Any connection to real-world evidence must be deliberately engineered, as in retrieval-augmented systems" — but argues this proves the point: the base system doesn't have truth as an internal norm. **What matters for Section 1:** The section needs to present the missing-loop argument clearly: (1) LLMs generate plausible candidates because training data encodes reasoning patterns; (2) but they lack the evaluation/verification mechanism that makes reasoning truth-tracking; (3) therefore outputs are epistemically unlicensed even when correct. The concession about absorbed causal structure should be presented as part of the argument, not flagged as a strategic admission. --- ## Internal Brief: Zahavy **Paper:** "LLMs Can't Jump" (2026, Google DeepMind position paper) **The fundamental problem Zahavy identifies:** LLMs cannot perform the "E→A Jump" — the translation from Sense Experience (E) to a System of Axioms (A). This is the specific bottleneck for scientific invention. LLMs can reason *within* a framework (deduction) and find patterns *in* data (induction), but they cannot generate the framework itself from scratch. **The framework — Peirce's tripartite:** Zahavy adopts Peirce's distinction between induction, deduction, and abduction: - **Induction** (statistical pattern-matching): LLMs have mastered this. - **Deduction** (formal derivation from axioms): AI is conquering this (AlphaProof on Mathematical Olympiad problems). - **Abduction** (the creative leap to new explanatory hypotheses): LLMs cannot do this. The Readwise highlight from the paper's abstract: > "Unlike deduction, which guarantees truth, or induction, which finds pattern that generalize in data, abduction is a creative leap that invents a cause for a singular phenomenon. Crucially, Einstein achieved this via embodied simulation—using thought experiments to ground abstract symbols in physical sensation—enabling him to formulate axioms where no symbolic data previously existed." **The Einstein case study in detail:** Zahavy's case study is Einstein's formulation of the Equivalence Principle — the insight that gravitational mass and inertial mass are indistinguishable, which came from imagining the experience of a person in free fall. The key Readwise highlight: > "Einstein did not discover General Relativity by searching over symbols; he discovered it by simulating the sensual experience of a falling observer." The "happiest thought" (Einstein's own phrase, which is referenced rather than originating in Zahavy) was the realisation that a person in free fall would not feel their own weight. This came not from data analysis or symbolic manipulation but from imagining a specific physical experience. Zahavy argues that this kind of sensory-to-symbolic translation is what "manipulative abduction" (Magnani's term) consists in — an active engagement with mental models that generates hypotheses through thinking-by-doing. **Why LLMs can't make this jump:** From the Readwise highlights: > "these symbols in physical reality. They operate as high-dimensional 'Chinese Rooms', manipulating the language of physics without access to the physical referents that give that language meaning. This limitation prevents the AI from making the Abductive Jump (→). While Einstein could ground his axioms in the physical experience of a falling body, an LLM is confined to the logical deduction of existing texts." The argument is structural: the architecture of a text-trained system provides no mechanism for sensory grounding. The model manipulates symbols that refer to physical reality without access to the physical reality those symbols refer to. **The anti-compression argument:** Zahavy also argues that Schmidhuber's "creativity as compression" framework fails for the E→A Jump. Einstein had no dataset to compress — the Newtonian loss function was near-zero (Newton's mechanics worked fine for the available data). There was no error signal driving discovery. The Readwise highlight: > "However, they highlight the very abductive gap we identify. The AI Scientist recombines existing symbolic concepts to optimize metrics—a sophisticated 'Chinese Room' operation that lacks the sensory grounding to invent axioms without symbolic precedent. Similarly, while AlphaEvolve excels at optimization within a fixed framework, it relies on a gradient; Einstein, by contrast, had no error signal from Newtonian mechanics to drive his discovery." **The domain-specificity restriction (this is what matters most for the paper):** Zahavy explicitly restricts his argument to the physical sciences: > "Finally, we emphasize that this proposal is specifically tailored to the physical sciences, where the object of study is external material reality. In abstract domains such as Mathematics or Computer Science, the Sense Experience (E) may be grounded in high-dimensional topology or have other goals such as generality or minimality." And further: > "manipulative abduction extends beyond physics. Historical scientific revolutions are often driven by strong, pre-symbolic intuitions—whether Kepler's Neoplatonic belief in the centrality of the Sun or the 'objective anger' that drove Marx's modeling of capital." So Zahavy himself says: the E→A Jump applies where the object of study is external material reality. In abstract domains, the nature of the "sense experience" is different. He does not mention philosophy, but the implication is that his bottleneck does not straightforwardly apply to domains where the object of study is not external material reality. **The deduction concession:** Zahavy grants that LLMs and adjacent systems can handle deduction. AlphaProof's performance on International Mathematical Olympiad problems is his evidence. But deductive capacity doesn't address the abductive bottleneck — you can derive consequences from axioms all day, but you still need to generate the axioms. From the Readwise highlights: > "An AI can deduce the consequences of 'The Equivalence Principle' only if those concepts are provided as inputs. As Einstein noted, logical thinking is limited to connections between concepts; it cannot generate the concepts themselves from raw sensory data." **What matters for Section 1:** The section needs to present the E→A Jump as a specific thesis about sensory-to-symbolic translation in physics, not as a generic claim about "creative leaps." The Einstein case study should be presented in enough detail that the reader understands *why* embodied simulation matters (it is not just that Einstein was imaginative, but that the particular insight required simulating a physical sensation that no existing formal framework contained). The domain-specificity restriction should be presented as something Zahavy himself states, not as editorial commentary. --- Now. You're right that the plan was part of the problem. The old plan was a list of paragraph functions — "do this, then do that" — without enough content specified to prevent the prose from becoming vague gesture. A better plan should contain the *actual content* that goes into each paragraph, including the block quotes and what they need to accomplish. Let me write the new plan. Give me a moment to think about the structure properly before I lay it out. --- ## New Plan for Section 1: What LLMs Aren't Doing **Organising principle:** The section has two halves (Floridi, Zahavy). Each half presents one fundamental problem in enough detail that the reader genuinely understands it. The section closes by showing where the two arguments converge and where a gap opens. **Fundamental problem for each paper:** - **Floridi:** LLMs generate plausible candidates (prior predictive sampling) but lack the evaluation loop (posterior evaluation) that makes reasoning truth-tracking. - **Zahavy:** The creative generation of new axioms from sense experience (the E→A Jump) requires embodied simulation that text-only systems structurally cannot perform. --- ### ¶1 — Opening - Two sentences. State that this section examines two reasons we might think LLMs cannot write good philosophy, and that both have to do with whether LLMs can perform abductive reasoning. - (Nick already wrote this paragraph. Keep it as is.) ### ¶2 — Floridi's starting point: the gap between mechanism and output - **What to present:** Floridi et al. ask what kind of reasoning LLMs are performing. Their answer: the mechanism is entirely stochastic (probability-distribution sampling trained on text), but the output resembles abductive inference. - **Block quote — delivers the specific claim:** > "Our main argument is that LLMs occupy a conceptual space 'between' traditional stochastic processes and human-like abductive reasoning. On the one hand, their internal processes are entirely stochastic: during training, they gather statistical correlations from text, and during generation, they produce words based on learned probability distributions." (Floridi et al., p. 2) - **Setup for this quote should NOT restate the stochastic/abductive point.** Instead, the setup should orient the reader to *what question Floridi is asking* — something like: Floridi et al. frame their paper around a specific question about LLMs and reasoning. The quote then delivers Floridi's answer. - **After the quote:** Explain what the gap between mechanism and output means: the model's internal process is statistical pattern-completion, but because the training data contains the products of human reasoning, the outputs take on the shape of reasoning. This is not accidental — Floridi calls it "systematic." But it is the form of reasoning, not an instance of it. ### ¶3 — Why the outputs look abductive: zeroth-order abduction - **What to present:** The abductive appearance arises because training data is saturated with human abductive reasoning — Wikipedia articles, scientific papers, Q&A forums all present evidence followed by explanation. The model has absorbed these patterns. Floridi calls what the model does "zeroth-order abduction": generating plausible continuations that mimic hypothesis generation without understanding or verification. - **Block quote — the zeroth-order abduction passage:** > "LLMs seem to perform a kind of zeroth-order abduction: given a prompt, they generate a plausible continuation (a hypothesis or explanation) based purely on learned associations... The model does not understand what an explanation is, but it produces text that follows the typical phrasing and structure of explanations. It does not reason about causes from scratch but outputs typical causes for typical effects observed in the training data." (Floridi et al., p. 8–9) - **Setup:** Should tell the reader *why* the outputs look abductive (because the training data encodes reasoning), so that the quote can deliver the specific characterisation of what the model is doing instead ("zeroth-order abduction"). - **After the quote:** Note that this means LLMs can perform "weak abduction" — generating plausible explanations — and can even appear to perform "strong abduction" on multiple-choice tasks where all candidates are provided. But this is pattern-reproduction, not epistemic reasoning. ### ¶4 — The missing loop: prior predictive sampling without posterior evaluation - **What to present:** This is the epistemic punch. Floridi's argument is not just "LLMs are stochastic" — it is that they lack the evaluation mechanism that makes reasoning truth-tracking. In Bayesian terms: they do prior predictive sampling (generating candidates) but lack posterior evaluation (testing candidates against evidence/truth). - **Block quote:** > "In statistical terms, LLMs perform prior predictive sampling but lack an external feedback loop for posterior evaluation." (Floridi et al., p. 7) - **Setup:** Should frame this as the *consequence* of zeroth-order abduction — what is specifically missing and why it matters epistemically. - **After the quote:** This is why hallucinations are not malfunctions but features. The model's task is to generate a plausible continuation; it cannot withhold judgment or say "I don't know," because generating *something* plausible is what it is optimised to do. Floridi calls this "over-abduction." Even when the output is correct, it is correct by coincidence (or by pattern-matching), not because the process tracked truth. - Sub-point: Floridi acknowledges that linguistic associations in the training data encode a broad stock of causal and inferential structure — the model has absorbed, statistically, that slippery floors cause falls and that hunger results from not eating. The information is there, "although not explicitly structured" (p. 17). But without the verification loop, there is no mechanism for distinguishing the cases where this absorbed information produces correct outputs from the cases where it produces hallucinations. - Sub-point: Floridi also raises the question of whether it matters that the production process was different if the content of the hypothesis is the same (p. 12–13) — but does not pursue it. ### ¶5 — Transition to Zahavy - **One or two sentences.** Not a taxonomic contrast ("epistemic vs structural"). Instead, something that builds on what has just been presented: Floridi's concern is with the epistemic standing of what LLMs produce — whether the outputs can count as knowledge given how they were generated. Zahavy approaches from a different direction: not whether the outputs are epistemically licensed, but whether the architecture can produce certain kinds of output at all. - No block quote. Keep it short. The content of the transition earns its weight only after the reader has understood Floridi's argument in ¶2–4. ### ¶6 — Zahavy's framework: the E→A Jump - **What to present:** Zahavy adopts Peirce's tripartite distinction (induction, deduction, abduction). His claim: LLMs have mastered induction (statistical pattern-matching) and are making progress on deduction (AlphaProof), but lack the mechanism for abduction — specifically, the "E→A Jump," the translation from sense experience to a system of axioms. - **Block quote — should deliver what the E→A Jump IS, not just that LLMs lack it:** > "Unlike deduction, which guarantees truth, or induction, which finds pattern that generalize in data, abduction is a creative leap that invents a cause for a singular phenomenon. Crucially, Einstein achieved this via embodied simulation—using thought experiments to ground abstract symbols in physical sensation—enabling him to formulate axioms where no symbolic data previously existed." (Zahavy, 2026) - **Setup:** Should introduce Zahavy's question — what kind of reasoning is the bottleneck for scientific invention — so the quote can deliver his answer (abduction, achieved via embodied simulation). - **After the quote:** Explain the Einstein case briefly but specifically. The "happiest thought" (Einstein's phrase) was the realisation that a person in free fall would not feel their own weight. This did not come from analysing data or manipulating symbols — it came from imagining a specific physical experience. Zahavy argues that this kind of sensory-to-symbolic translation is what Magnani calls "manipulative abduction": hypothesis generation through active engagement with mental models. ### ¶7 — Why LLMs can't make the jump: the Chinese Room problem - **What to present:** LLMs manipulate the language of physics without access to the physical referents that give that language meaning. They are, in Zahavy's terms, "high-dimensional Chinese Rooms." - **Block quote:** > "They operate as high-dimensional 'Chinese Rooms', manipulating the language of physics without access to the physical referents that give that language meaning. This limitation prevents the AI from making the Abductive Jump. While Einstein could ground his axioms in the physical experience of a falling body, an LLM is confined to the logical deduction of existing texts." (Zahavy, 2026) - **Setup:** Should follow from ¶6 — having explained *what* the E→A Jump requires (embodied simulation), now explain *why* LLMs lack it. - **After the quote:** Note that Zahavy grants LLMs can handle the deductive phase — deriving consequences from axioms once the axioms are provided. But this does not address the bottleneck: generating the axioms in the first place. Einstein had no error signal from Newtonian mechanics to drive his discovery — the existing framework worked fine for the available data. The creative leap went beyond what any data-driven process could produce. ### ¶8 — Convergence: two arguments, one apparent conclusion - **What to present:** Floridi and Zahavy start from different questions and arrive at what looks like the same conclusion. For Floridi: LLM outputs are not epistemically licensed because the process that produces them is not truth-tracking. For Zahavy: LLMs lack the architectural resources for the kind of inference that drives scientific discovery. Together they appear to close off LLMs from genuine reasoning — one from the side of the product (its epistemic standing), the other from the side of the process (what the architecture can do). - No block quote. Straightforward summary drawing on what has been presented. - Keep it brief — the reader has the content from ¶2–7; this paragraph just makes the convergence explicit. ### ¶9 — The gap: both arguments are domain-specific - **What to present:** Both arguments are framed with specific domains in mind. Floridi's examples are scientific papers, empirical observation, laboratory findings — domains where the text reports discoveries made elsewhere. Zahavy is explicit about his scope: - **Block quote — Zahavy's own restriction:** > "we emphasize that this proposal is specifically tailored to the physical sciences, where the object of study is external material reality. In abstract domains such as Mathematics or Computer Science, the Sense Experience (E) may be grounded in high-dimensional topology or have other goals such as generality or minimality." (Zahavy, 2026) - **Setup:** Should point out that Zahavy's E→A Jump applies where the object of study is external material reality and the foundational intuitions are physical intuitions about what it is like to be a body in the world. Whether the same bottleneck applies to disciplines with a different relationship to their subject matter is a question his argument leaves open. - **After the quote:** Floridi's argument is similarly framed. The missing verification loop matters most where the text reports or discusses findings made elsewhere — where there is an external reality against which outputs need to be checked. Whether the same worry has the same force in a discipline whose contributions are constituted by the text itself, rather than reported in it, is not a question either paper addresses. - **No editorial commentary** ("neither was developed with philosophy in mind"). Just present what the papers say and what they don't say. The reader draws the implication. ### ¶10 — Close: the question that opens Section 2 - **What to present:** Both papers invoke abduction, but neither asks what kind of abduction philosophy requires — and in particular, whether the abduction philosophy needs is the abduction LLMs are alleged to lack. Before that question can be answered, we need to look at what "abduction" means in the different literatures that use the term, and especially what it means in the literature on philosophical methodology, where inference to the best explanation is not a description of how scientists discover but a method for evaluating theories. - No block quote. Statement of the question that motivates Section 2. --- **Total block quotes: 5** (Floridi p.2, Floridi p.8–9 on zeroth-order abduction, Floridi p.7 on prior/posterior sampling, Zahavy abstract on E→A Jump, Zahavy on domain restriction). Down from 6 in the previous version, and each one now does distinct work. **What changed from the old plan:** - Content is specified at the level of *what the reader learns*, not just paragraph function - Block quote setups are planned so they don't duplicate the quote - The fundamental problem of each paper is identified and everything else serves it - Floridi gets three paragraphs of content (¶2–4) instead of being crammed into one overloaded paragraph - The concessions (absorbed causal structure, Zahavy's domain restriction) are presented as part of the papers' arguments, not flagged as concessions - No editorial commentary about "philosophy in mind" — just faithful presentation that lets the reader notice the domain-specificity - The provenance question (Floridi p.12–13) is mentioned where Floridi raises it, then left for Section 2 --- What do you think? Is the content right? Are the block quotes doing the right work? Anything I'm missing or including that shouldn't be there? *Il piano vecchio descriveva le funzioni dei paragrafi; questo nuovo piano descrive ciò che il lettore impara — e la differenza è tutto.* ### User 1. you got cut off, please continue from where you left off. 2. "is not a phrase Floridi uses, as far as I can tell from the Readwise highlights." you have access to the full text, you dummy.