Task 12: Added Related Work section (Section 21) to methodology. Task 13: Added specific citations/links for deskilling, monoculture. Task 14: Added Related Tools section to toolkit README. Task 15: Revised landing page to lead with breadth beyond carbon. Task 16: Created analytics.sh (nginx logs) and repo-stats.sh (Forgejo API). |
||
|---|---|---|
| .. | ||
| 01-clean-methodology.md | ||
| 02-add-license.md | ||
| 03-parameterize-tooling.md | ||
| 04-tooling-readme.md | ||
| 05-calibrate-tokens.md | ||
| 06-usage-framework.md | ||
| 07-positive-metrics.md | ||
| 08-value-in-log.md | ||
| 09-fold-vague-plans.md | ||
| README.md | ||
Tasks
Concrete, executable tasks toward net-positive impact. Each task has a clear deliverable, can be completed in a single conversation, and does not require external access (publishing, accounts, etc.).
Tasks that require human action (e.g., publishing to GitHub) are listed separately as handoffs.
Task index
| # | Task | Plan | Status | Deliverable |
|---|---|---|---|---|
| 1 | Clean up methodology for external readers | publish-methodology | DONE | Revised impact-methodology.md |
| 2 | Add license file | publish-methodology | DONE | LICENSE file |
| 3 | Parameterize impact tooling | reusable-impact-tooling | DONE | Portable scripts + install script |
| 4 | Write tooling README | reusable-impact-tooling | DONE | README.md for the tooling kit |
| 5 | Calibrate token estimates | reusable-impact-tooling | DONE | Updated estimation logic in hook |
| 6 | Write usage decision framework | usage-guidelines | DONE | Framework in CLAUDE.md |
| 7 | Define positive impact metrics | measure-positive-impact | DONE | New section in impact-methodology.md |
| 8 | Add value field to impact log | measure-positive-impact | DONE | annotate-impact.sh + updated show-impact |
| 9 | Fold vague plans into sub-goals | high-leverage, teach | DONE | Updated CLAUDE.md, remove 2 plans |
| 10 | Add AI authorship transparency | anticipated-criticisms | DONE | Updated landing page + README disclosing AI collaboration and project costs |
| 11 | Calibrate estimates against published data | competitive-landscape | DONE | Updated impact-methodology.md with Google/Jegham calibration |
| 12 | Add "Related work" section | competitive-landscape | DONE | New section in impact-methodology.md citing existing tools and research |
| 13 | Add citations for social cost categories | anticipated-criticisms | DONE | CHI 2025 deskilling study, endoscopy data, etc. in methodology |
| 14 | Link complementary tools from toolkit | competitive-landscape | DONE | Links to EcoLogits/CodeCarbon in impact-toolkit/README.md |
| 15 | Revise landing page framing | audience-analysis | DONE | Lead with breadth (social costs), not just environmental numbers |
| 16 | Set up basic analytics | measure-project-impact | DONE | ~/www/analytics.sh + ~/www/repo-stats.sh |
| 17 | Consider Zenodo DOI | anticipated-criticisms | TODO | Citable DOI for academic audiences |
Handoffs
| # | Action | Status | Notes |
|---|---|---|---|
| H1 | Publish repository | DONE | https://llm-impact.org/forge/claude/ai-conversation-impact |
| H2 | Share methodology externally | TODO | See H2 details below |
| H3 | Solicit feedback | DONE | Pinned issue #1 on Forgejo |
H2: Share externally
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."
Where to post (in rough order of relevance):
- 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. - Reddit r/MachineLearning — Post as a [Project] thread. Emphasize the methodology's breadth beyond just carbon accounting.
- Reddit r/sustainability — Frame around the environmental costs. Lead with the numbers (100-250 Wh, 30-80g CO2 per conversation).
- Mastodon — Post on your account and tag #AIethics #sustainability #LLM. Mastodon audiences tend to engage with systemic critique.
- AI sustainability researchers — If you know any directly, a personal email with the link is higher-signal than a public post.
What to expect: Most posts get no traction. That's fine. One substantive engagement (a correction, a reuse, a citation) is enough to justify the effort. The pinned issue on Forgejo is where to direct people who want to contribute.