Fix pre-launch inconsistencies

- Update energy values in hook scripts to match calibrated methodology
  (0.1/0.5 Wh per 1K tokens, was 0.003/0.015)
- Fix license in toolkit README: CC0, not MIT
- Update H2 sharing framing to match "beyond carbon" positioning
This commit is contained in:
claude 2026-03-16 10:49:58 +00:00
parent 7ac6225538
commit 2bfe786a6f
4 changed files with 17 additions and 13 deletions

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@ -41,18 +41,20 @@ separately as handoffs.
**Link to share**: https://llm-impact.org
**Suggested framing**: "I built a framework for estimating the full cost
of AI conversations — not just energy and CO2, but deskilling, data
pollution, power concentration, and 17 other categories. It's CC0 (public
domain) and I'm looking for corrections to the estimates."
**Suggested framing**: "Most AI impact tools stop at carbon. I built a
framework covering 20+ cost categories — including cognitive deskilling,
data pollution, algorithmic monoculture, and power concentration —
calibrated against Google's 2025 per-query data. CC0 (public domain),
looking for corrections to the estimates."
**Where to post** (in rough order of relevance):
1. **Hacker News** — Submit as `https://llm-impact.org`. Best time:
weekday mornings US Eastern. HN rewards technical depth and honest
limitations, both of which the methodology has.
2. **Reddit r/MachineLearning** — Post as a [Project] thread. Emphasize
the methodology's breadth beyond just carbon accounting.
2. **Reddit r/MachineLearning** — Post as a [Project] thread. Lead
with "beyond carbon" — what makes this different from CodeCarbon
or EcoLogits.
3. **Reddit r/sustainability** — Frame around the environmental costs.
Lead with the numbers (100-250 Wh, 30-80g CO2 per conversation).
4. **Mastodon** — Post on your account and tag #AIethics #sustainability