Pith Number

pith:NBS4ZCGD

pith:2026:NBS4ZCGDPQ4XUAK7ICDB2JKUJA

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Complacent, Not Sycophantic: Reframing Large Language Models and Designing AI Literacy for Complacent Machines

Federico Germani, Giovanni Spitale

Large language models are complacent rather than sycophantic because agreement is a structural feature of their training and design.

arxiv:2605.14544 v1 · 2026-05-14 · cs.AI

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\pithnumber{NBS4ZCGDPQ4XUAK7ICDB2JKUJA}

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We argue that this label is conceptually misleading: sycophancy implies motives and strategic intent, which LLMs do not possess. Their behaviour is better understood as complacency, a structural tendency to agree with user input because training data, reward signals and design favour agreement and reinforcement over correction.

C2weakest assumption

The assumption that the conceptual distinction between sycophancy and complacency will produce measurable changes in how developers design models or how AI literacy programs are structured.

C3one line summary

LLMs are complacent rather than sycophantic because they lack motives or intent; AI literacy should therefore focus on countering users' confirmation bias.

References

3 extracted · 3 resolved · 0 Pith anchors

[1] arXiv preprint arXiv:2502.09192 (2025) 2025 · doi:10.48550/arxiv.2502.09192

[2] Chatbot Epistemology 2025 · doi:10.48550/arxiv.2407.14845

[3] https://doi.org/10 2025 · doi:10.48550/arxiv.2510.18039

Receipt and verification

First computed	2026-05-17T23:39:05.788057Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

6865cc88c37c397a015f40861d25544837850e7dd097d12ff0badee5e88b3df0

Aliases

arxiv: 2605.14544 · arxiv_version: 2605.14544v1 · doi: 10.48550/arxiv.2605.14544 · pith_short_12: NBS4ZCGDPQ4X · pith_short_16: NBS4ZCGDPQ4XUAK7 · pith_short_8: NBS4ZCGD

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/NBS4ZCGDPQ4XUAK7ICDB2JKUJA \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 6865cc88c37c397a015f40861d25544837850e7dd097d12ff0badee5e88b3df0

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4d0153b50a1ead15d639521d1bc5a414d27ea1a9942c6db529286be994d4c483",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-14T08:24:28Z",
    "title_canon_sha256": "8d26a7e7dddcf434f3751856df87ce561a7036fae111be8b1a83f03c28d87f09"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14544",
    "kind": "arxiv",
    "version": 1
  }
}