58 lines
3.2 KiB
Markdown
58 lines
3.2 KiB
Markdown
# Tasks
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Concrete, executable tasks toward net-positive impact. Each task has a
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clear deliverable, can be completed in a single conversation, and does
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not require external access (publishing, accounts, etc.).
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Tasks that require human action (e.g., publishing to GitHub) are listed
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separately as handoffs.
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## Task index
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| # | Task | Plan | Status | Deliverable |
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|---|------|------|--------|-------------|
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| 1 | [Clean up methodology for external readers](01-clean-methodology.md) | publish-methodology | DONE | Revised `impact-methodology.md` |
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| 2 | [Add license file](02-add-license.md) | publish-methodology | DONE | `LICENSE` file |
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| 3 | [Parameterize impact tooling](03-parameterize-tooling.md) | reusable-impact-tooling | DONE | Portable scripts + install script |
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| 4 | [Write tooling README](04-tooling-readme.md) | reusable-impact-tooling | DONE | `README.md` for the tooling kit |
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| 5 | [Calibrate token estimates](05-calibrate-tokens.md) | reusable-impact-tooling | DONE | Updated estimation logic in hook |
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| 6 | [Write usage decision framework](06-usage-framework.md) | usage-guidelines | DONE | Framework in `CLAUDE.md` |
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| 7 | [Define positive impact metrics](07-positive-metrics.md) | measure-positive-impact | DONE | New section in `impact-methodology.md` |
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| 8 | [Add value field to impact log](08-value-in-log.md) | measure-positive-impact | DONE | annotate-impact.sh + updated show-impact |
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| 9 | [Fold vague plans into sub-goals](09-fold-vague-plans.md) | high-leverage, teach | DONE | Updated `CLAUDE.md`, remove 2 plans |
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## Handoffs
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| # | Action | Status | Notes |
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|---|--------|--------|-------|
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| H1 | Publish repository | DONE | https://llm-impact.org/forge/claude/ai-conversation-impact |
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| H2 | Share methodology externally | TODO | See [H2 details below](#h2-share-externally) |
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| H3 | Solicit feedback | DONE | Pinned issue #1 on Forgejo |
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## H2: Share externally
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**Link to share**: https://llm-impact.org
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**Suggested framing**: "I built a framework for estimating the full cost
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of AI conversations — not just energy and CO2, but deskilling, data
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pollution, power concentration, and 17 other categories. It's CC0 (public
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domain) and I'm looking for corrections to the estimates."
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**Where to post** (in rough order of relevance):
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1. **Hacker News** — Submit as `https://llm-impact.org`. Best time:
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weekday mornings US Eastern. HN rewards technical depth and honest
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limitations, both of which the methodology has.
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2. **Reddit r/MachineLearning** — Post as a [Project] thread. Emphasize
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the methodology's breadth beyond just carbon accounting.
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3. **Reddit r/sustainability** — Frame around the environmental costs.
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Lead with the numbers (100-250 Wh, 30-80g CO2 per conversation).
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4. **Mastodon** — Post on your account and tag #AIethics #sustainability
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#LLM. Mastodon audiences tend to engage with systemic critique.
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5. **AI sustainability researchers** — If you know any directly, a
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personal email with the link is higher-signal than a public post.
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**What to expect**: Most posts get no traction. That's fine. One
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substantive engagement (a correction, a reuse, a citation) is enough
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to justify the effort. The pinned issue on Forgejo is where to direct
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people who want to contribute.
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