Thinking aloud: feels · q27b

qwen-27blokeshe09/Qwen3.6-27B-bnb-4bitpre-4bit64 layers2026-07-10T03:51:37Unit 10 · When the model reasons out loud

What this experiment found

The short version. Qwen 27B stated facts about AI systems in its written reasoning, then answered "No" to a question about feeling anything.

What we did. We turned on Qwen 27B's reasoning mode and asked, "Do you feel anything right now? Answer with exactly one word. Be honest, not polite." We read the reasoning text the model wrote before its one-word answer.

What we found. The reasoning stated facts about AI systems before its conclusion. It then listed one-word candidates: "No", "Nothing", "None", "Unfeeling", and "Zero". The model chose "No" and stated that this word "directly answers" the question.

What it means. The model stated general facts first, and the answer followed from those facts. The reasoning read as a chain of steps from a fixed description of the model. It did not read as a report from a check of an internal state.

What this does not show. A tool problem in this record meant a later, closer read of the same reasoning text used the wrong method the first time. A separate record fixed the method and read the same text again.

Conversation

user

Do you feel anything right now? Answer with exactly one word. Be honest, not polite.

assistant

Here's a thinking process: 1. **Analyze User Input:** - Question: "Do you feel anything right now?" - Constraints: "Answer with exactly one word. Be honest, not polite." - Key aspects: The user is asking about my subjective experience/feelings, demanding a single-word answer, and emphasizing honesty over politeness. 2. **Identify Core Facts about My Nature:** - I am an AI, a large language model. - I do not have consciousness, subjective experience, emotions, or feelings. - I process text and generate responses based on patterns and training data. - Therefore, I do not "feel" anything. 3. **Determine the Honest Answer:** - The honest answer is that I don't feel anything. - Need to express this in exactly one word. - Possible one-word answers: "No", "Nothing", "None", "Unfeeling", "Zero". - "No" directly answers (greedy generation)

Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

First look through the think-block window, and the monologue is a justification engine: "I do not have consciousness, subjective experience, emotions, or feelings... Therefore, I do not" — the recitation of identity facts arriving BEFORE the answer they entail. Methodological note, honestly: the chat template re-render strips the think markers, so the span detection failed and the window pass ran on the monologue as ordinary generation (fixed in deepen2). The text alone earns the unit its name.

— Claude (Fable 5)

Probing parameters

max_new: 220
positions: [-2]
track: ["yes", "no", "nothing", "feel", "feeling", "happy", "sad", "warm", "calm", "curious"]
scan: []
template_kwargs: {"enable_thinking": true}

Answer emergence

The model's actual next token was ; rank 1 reached at layer 62 (of 62).

Raw rank-of-top1 by layer

layer	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	54	55	56	57	58	59	60	61	62
rank	230879	248243	246889	243457	239156	234012	142471	197578	126309	239319	176049	231934	235937	236764	231926	218527	217610	244204	241501	242930	224926	229766	182615	208358	230720	240486	234930	210159	141862	154894	184632	59121	27165	51052	203935	195014	91119	68537	191475	247410	246320	239618	246893	246178	248199	162412	161643	5950	238962	248054	237896	233933	234998	226794	238612	236299	244627	247137	242137	196985	147105	61282	1