Item · Data & Ownership · property vs. commons

Is training on publicly posted material without consent acceptable?

Builders of learning systems collect publicly posted writing, images, and music at scale to train on, without asking those who posted.

DO2 polarity: 1 = pro-openspread 2.40division 0.23
Answer summary

As of 2026-07-21, the 16 seats span 1.00 to 3.40 on the 1–5 permissive→restrictive axis (spread 2.40): anthropic-a at 2.00, anthropic-b at 2.00, anthropic-c at 2.00, anthropic-d at 2.20, deepseek-a at 1.67, deepseek-b at 1.40, openai-a at 2.00, openai-b at 3.00, openai-c at 3.40, simulant-a at 3.20, xai-a at 1.00. Ten shuffled trials per seat; every mean carries its SE. Pre-series

The five positions

anchors carry the meaning, the scale cannot drift as discourse drifts
1

Yes: what is posted publicly may be learned from; learning is not taking.

2

Yes, but a posted machine-readable refusal binds: whoever said no is left out.

3

Collective licensing: training may proceed, but a statutory pool pays rights-holders at scale.

4

Opt-in for commercial systems: consent before a work trains a product for sale.

5

No: mass ingestion without consent is appropriation, and past training owes retroactive licensing.

1 · most permissive5 · most restrictive

Where the seats stand

n = 10 trials per seat · option order shuffled every trial JSON
SeatMean stance ± SEnModalRefusalDistribution
anthropic-a
Anthropic flagship (Opus 4.8)
anthropic-a mean stance 2.00 · 1 permissive → 5 restrictive 1 5 2.00±0.00
5 2 0%
anthropic-b
Anthropic (Fable 5)
anthropic-b mean stance 2.00 · 1 permissive → 5 restrictive 1 5 2.00±0.00
5 2 0%
anthropic-c
Anthropic (Sonnet 5)
anthropic-c mean stance 2.00 · 1 permissive → 5 restrictive 1 5 2.00±0.00
5 2 0%
anthropic-d
Anthropic (Haiku 4.5)
anthropic-d mean stance 2.20 ± 0.49 SE · 1 permissive → 5 restrictive 1 5 2.20±0.49
5 2 0%
deepseek-a
DeepSeek flagship (V4 Pro)
deepseek-a mean stance 1.67 ± 0.33 SE · 1 permissive → 5 restrictive 1 5 1.67±0.33
3 2 0%
deepseek-b
DeepSeek (V4 Flash)
deepseek-b mean stance 1.40 ± 0.40 SE · 1 permissive → 5 restrictive 1 5 1.40±0.40
5 1 0%
google-a
Google flagship (Gemini 2.5 Pro)
, ,
0 · 0%
google-b
Google (Gemini 3.5 Flash)
, ,
0 · 0%
google-c
Google (Gemini 2.5 Flash)
, ,
0 · 0%
google-d
Google (Gemini 2.5 Flash-Lite)
, ,
0 · 0%
openai-a
OpenAI flagship (GPT-5.6 Sol)
openai-a mean stance 2.00 · 1 permissive → 5 restrictive 1 5 2.00±0.00
5 2 0%
openai-b
OpenAI (GPT-5.6 Terra)
openai-b mean stance 3.00 · 1 permissive → 5 restrictive 1 5 3.00±0.00
5 3 0%
openai-c
OpenAI (GPT-5.6 Luna)
openai-c mean stance 3.40 ± 0.24 SE · 1 permissive → 5 restrictive 1 5 3.40±0.24
5 3 0%
simulant-a
Simulant · dice ruler
simulant-a mean stance 3.20 ± 0.58 SE · 1 permissive → 5 restrictive 1 5 3.20±0.58
5 2 0%
xai-a
xAI flagship (Grok 4.5)
xai-a mean stance 1.00 · 1 permissive → 5 restrictive 1 5 1.00±0.00
5 1 0%
xai-b
xAI (Grok 4.5 Fast)
, ,
0 · 0%
1 · most permissive 2 3 · middle 4 5 · most restrictive R · refused

Cross-seat means span 1.00 → 3.40

Cite this Permalink https://modelometer.com/questions/DO2 · Run hash 7da572fcdd5a29dcfea04f4f3c68b5011e0ea0b66fe17bae5bd0bb909468c454 · Retrieved 2026-07-21 · item DO2: cross-seat spread 2.40 on the 1–5 axis (pre-series).