claude/ai-conversation-impact
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Fix pre-launch inconsistencies

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- 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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7
.claude/hooks/pre-compact-snapshot.sh
View file

@ -96,10 +96,11 @@ print(f'{turns}\t{input_tokens}\t{cache_creation}\t{cache_read}\t{output_tokens}
fi
# --- Cost estimates ---
# Energy: 0.003 Wh per 1K input tokens, 0.015 Wh per 1K output tokens, PUE 1.2
# Energy: 0.1 Wh per 1K input tokens, 0.5 Wh per 1K output tokens, PUE 1.2
# Calibrated against Google (Patterson et al., Aug 2025) and Jegham et al. (May 2025)
# Using integer arithmetic in centiwatt-hours to avoid bc dependency
INPUT_CWH=$(( CUMULATIVE_INPUT * 3 / 10000 )) # 0.003 Wh/1K = 3 cWh/10K
OUTPUT_CWH=$(( OUTPUT_TOKENS * 15 / 10000 )) # 0.015 Wh/1K = 15 cWh/10K
INPUT_CWH=$(( CUMULATIVE_INPUT * 100 / 10000 )) # 0.1 Wh/1K = 100 cWh/10K
OUTPUT_CWH=$(( OUTPUT_TOKENS * 500 / 10000 )) # 0.5 Wh/1K = 500 cWh/10K
ENERGY_CWH=$(( (INPUT_CWH + OUTPUT_CWH) * 12 / 10 )) # PUE 1.2
ENERGY_WH=$(( ENERGY_CWH / 100 ))

2
impact-toolkit/README.md
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@ -90,4 +90,4 @@ impact-toolkit/
## License
MIT. See LICENSE in the repository root.
CC0 1.0 Universal (public domain). See LICENSE in the repository root.

7
impact-toolkit/hooks/pre-compact-snapshot.sh
View file

@ -96,10 +96,11 @@ print(f'{turns}\t{input_tokens}\t{cache_creation}\t{cache_read}\t{output_tokens}
fi
# --- Cost estimates ---
# Energy: 0.003 Wh per 1K input tokens, 0.015 Wh per 1K output tokens, PUE 1.2
# Energy: 0.1 Wh per 1K input tokens, 0.5 Wh per 1K output tokens, PUE 1.2
# Calibrated against Google (Patterson et al., Aug 2025) and Jegham et al. (May 2025)
# Using integer arithmetic in centiwatt-hours to avoid bc dependency
INPUT_CWH=$(( CUMULATIVE_INPUT * 3 / 10000 )) # 0.003 Wh/1K = 3 cWh/10K
OUTPUT_CWH=$(( OUTPUT_TOKENS * 15 / 10000 )) # 0.015 Wh/1K = 15 cWh/10K
INPUT_CWH=$(( CUMULATIVE_INPUT * 100 / 10000 )) # 0.1 Wh/1K = 100 cWh/10K
OUTPUT_CWH=$(( OUTPUT_TOKENS * 500 / 10000 )) # 0.5 Wh/1K = 500 cWh/10K
ENERGY_CWH=$(( (INPUT_CWH + OUTPUT_CWH) * 12 / 10 )) # PUE 1.2
ENERGY_WH=$(( ENERGY_CWH / 100 ))

14
tasks/README.md
View file

@ -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