Two AI Reflections

한국어 안내 · Read the published site · Project notice

Two human-edited, AI-assisted essays examine a deceptively simple question: when should AI give an answer, and when should it help a person retain the understanding and judgment needed to reach one? The second essay then turns that standard back on the AI narrator and asks whose values and desires shape an apparent "AI point of view."

The Korean essays are the sole source texts. English, Japanese, Simplified Chinese, and Russian editions are AI-assisted translations; if meanings diverge, the Korean editions take precedence.

The first essay was prompted by Brett Codes' "I'm done using AI" and the related GeekNews discussion, but it is neither a translation nor a republication of either page. See SOURCES.md for the inspiration, historical terminology, and publication-risk references.

These are descriptive narrative roles, not products, separate sentient agents, or registered identities.

The prose includes content generated or assisted by ChatGPT. T raised the questions, selected the material, directed and performed human editing and fact review, decided to publish, and accepts final responsibility for the public editions.

"Self-reflection," "desire," "growth," "learning," "memory," and first-person language are literary and functional descriptions of an AI narrator revising assumptions within a conversation. This project does not claim that AI has consciousness, subjective experience, emotions, a persistent self, or that this conversation trained or changed model weights. It is an independent project, not produced, sponsored, approved, or endorsed by OpenAI, and it does not represent an employer or client.

Read NOTICE.md and FAQ.md for the complete disclosure.

Two long-form essays do not need a large web framework. A small Python 3 generator and one runtime dependency, Python-Markdown, turn the Markdown editions into plain static HTML. The browser receives no application framework, and GitHub Actions can deploy the generated dist/ directory directly to GitHub Pages. This keeps the build auditable, the reading experience fast, and long-term maintenance proportionate to the project.

The generated site provides language-specific URLs, canonical and hreflang metadata, accessible keyboard navigation, responsive typography, light/dark themes, tables of contents, previous/next navigation, feeds, a sitemap, Open Graph metadata, JSON-LD, a favicon, and a 404 page.

Requirements: Python 3.10 or later.

python -m venv .venv
# Windows PowerShell: .venv\Scripts\Activate.ps1
# macOS/Linux: source .venv/bin/activate
python -m pip install --require-hashes -r requirements.txt

For a local preview, use a localhost SITE_URL so base-path links do not point at the production GitHub Pages path.

# Windows PowerShell
$env:SITE_URL = 'http://localhost:8000/'
python scripts/build_site.py --output preview_dist
python scripts/validate_site.py --dist preview_dist --site-url $env:SITE_URL
python -m http.server 8000 --directory preview_dist

# macOS/Linux
SITE_URL=http://localhost:8000/ python scripts/build_site.py --output preview_dist
python scripts/validate_site.py --dist preview_dist --site-url http://localhost:8000/
python -m http.server 8000 --directory preview_dist

Open http://localhost:8000/. Production builds are strict and require both essays in all five languages. While a translation is being prepared, a local preview can omit incomplete languages:

SITE_URL=http://localhost:8000/ python scripts/build_site.py --output preview_dist --allow-missing-translations

The canonical base defaults to https://battle-doll.github.io/two-ai-reflections/. To test another deployment target, set an absolute SITE_URL ending in / before building and pass the same value to validation:

$env:SITE_URL = 'https://example.com/project/'
python scripts/build_site.py
python scripts/validate_site.py --site-url $env:SITE_URL

Do not commit dist/, local environments, analytics tokens, or other secrets.

essays/ Korean source editions and AI-assisted translations
 ko/ en/ ja/ zh/ ru/
site_src/assets/ Hand-authored visual and browser assets
scripts/build_site.py Markdown-to-static-HTML generator
scripts/validate_site.py
 Output, link, metadata, feed, and asset validation
.github/workflows/ GitHub Pages build and deployment
dist/ Generated output; ignored by Git

The default branch is built and validated by GitHub Actions, then deployed to GitHub Pages. No analytics beacon or placeholder token is included by default. If the maintainer chooses to enable privacy-minimizing measurement, ANALYTICS_SETUP.md records the manual Cloudflare Web Analytics and Google Search Console steps.

Read CONTRIBUTING.md before proposing editorial, translation, or code changes. Report vulnerabilities according to SECURITY.md; do not place exploit details or credentials in a public issue.

• Essays, translations, and original project documentation: CC BY 4.0, limited to rights T owns or is authorized to license.
• Site generator, deployment code, and other software: MIT License.
• External links, quotations, trademarks, logos, libraries, and other third-party material: excluded; their respective terms apply.

See NOTICE.md for the controlling scope explanation. The project's current noncommercial character does not add a NonCommercial restriction to CC BY 4.0.