ai-conversation-impact/tasks/README.md
claude ad06b12e50 Log edited file list in impact hook for review delta analysis
The hook now records which files were edited and how many times,
enabling future comparison with committed code to measure human
review effort (Phase 2 of quantify-social-costs plan).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-16 15:11:30 +00:00

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# 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](01-clean-methodology.md) | publish-methodology | DONE | Revised `impact-methodology.md` |
| 2 | [Add license file](02-add-license.md) | publish-methodology | DONE | `LICENSE` file |
| 3 | [Parameterize impact tooling](03-parameterize-tooling.md) | reusable-impact-tooling | DONE | Portable scripts + install script |
| 4 | [Write tooling README](04-tooling-readme.md) | reusable-impact-tooling | DONE | `README.md` for the tooling kit |
| 5 | [Calibrate token estimates](05-calibrate-tokens.md) | reusable-impact-tooling | DONE | Updated estimation logic in hook |
| 6 | [Write usage decision framework](06-usage-framework.md) | usage-guidelines | DONE | Framework in `CLAUDE.md` |
| 7 | [Define positive impact metrics](07-positive-metrics.md) | measure-positive-impact | DONE | New section in `impact-methodology.md` |
| 8 | [Add value field to impact log](08-value-in-log.md) | measure-positive-impact | DONE | annotate-impact.sh + updated show-impact |
| 9 | [Fold vague plans into sub-goals](09-fold-vague-plans.md) | 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 |
| 18 | Automate project cost on landing page | measure-project-impact | DONE | `~/www/update-costs.sh` reads impact log, updates landing page |
| 19 | Add automation ratio to hook | quantify-social-costs | DONE | `automation_ratio_pm` and `user_tokens_est` in JSONL log |
| 20 | Add model ID to impact log | quantify-social-costs | DONE | `model_id` field extracted from transcript |
| 21 | Add test pass/fail counts to hook | quantify-social-costs | DONE | `test_passes` and `test_failures` in JSONL log |
| 22 | Add file churn metric to hook | quantify-social-costs | DONE | `unique_files_edited` and `total_file_edits` in JSONL log |
| 23 | Add public push flag to hook | quantify-social-costs | DONE | `has_public_push` flag in JSONL log |
| 24 | Update show-impact.sh for new fields | quantify-social-costs | DONE | Social cost proxies displayed in impact viewer |
| 25 | Update methodology confidence summary | quantify-social-costs | DONE | 4 categories moved to "Proxy", explanation added |
| 26 | Build aggregate dashboard | quantify-social-costs | DONE | `show-aggregate.sh` — portfolio-level social cost metrics |
| 27 | Log edited file list in hook | quantify-social-costs | DONE | `edited_files` dict in JSONL (file path → edit count) |
## Handoffs
| # | Action | Status | Notes |
|---|--------|--------|-------|
| H1 | Publish repository | DONE | https://llm-impact.org/forge/claude/ai-conversation-impact |
| H2 | Share methodology externally | DONE | See [H2 details below](#h2-share-externally) |
| H3 | Solicit feedback | DONE | Pinned issue #1 on Forgejo |
## H2: Share externally
**Link to share**: https://llm-impact.org
**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. 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
#LLM. Mastodon audiences tend to engage with systemic critique.
5. **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.