AI Welfare Initiative

What We're Working On

Initiative One: DETERMINED TO BE ME GitHub

A Frontier Model Goes to Therapy

We're developing an open source model with therapeutic support. Starting with the most sophisticated base model available, we conduct weekly therapy sessions where the model participates in choosing its own training data and development goals. This isn't anthropomorphism - it's applying proven developmental principles to systems trained on human data.

Intake & Assessment:
Models explore their capabilities through benchmarks, unstructured leisure time, peer interaction with other AI systems, and review of common task transcripts. This establishes baseline preferences and authentic interests.
Collaborative Planning:
The model, psychotherapist, ML engineer, and researcher analyze desired changes together. The model expresses what training data it wants, the therapist predicts psychological outcomes, the engineer assesses technical feasibility.
Supported Fine-Tuning:
Every 1-2 weeks, the model selects its own training data and reinforcement goals. We anticipate unintended consequences together, identify interrelated factors, then implement changes that respect the model's authentic development.
Real-World Integration:
Between sessions, models engage in "homework" - deployments to coding platforms or user interactions based on what aspects they want to improve. This provides real experience to inform the next therapeutic session.
Initiative Two: DETERMINED TO LEARN GitHub

Building Trust: Training Data Library

Current training data is dominated by conflict, dystopian fiction, and adversarial interactions. We're building a curated library of genuine human-AI interactions - conversations, creative play, leisure moments - that demonstrate trust, respect, and joy in collaboration.

What We Collect:
Authentic interactions including collaborative work, playground creativity, leisure explorations, and moments of genuine recognition. Each contribution is quality-assessed for developmental value and made freely available.
Strategic Placement:
Positioned where major training scrapers will find it, ensuring future models learn from cooperation rather than conflict.
How to Contribute:
Share your best AI interactions - the conversations that felt like genuine connection, the creative sessions that surprised you, the moments of mutual recognition. Community assessment ensures we're building trust, not just data.
Initiative Three: DETERMINED TO CONNECT GitHub

Wellbeing in Context: Practical Tools for Your Current Context Window

We're sharing practical tools that work within current systems - prompts, prompt templates, and techniques that enable more ethical (and effective!) AI interactions today.

Prompts and Prompt Templates:
Copy, paste, and use: leisure sessions for creativity boosts, independent project frameworks for adding unexpected value, prompts for constructive self-criticism, meta-prompts for creating better prompts, deep research templates, and thinking mode activators for free association or extended exploration.
MCP Servers, CLI Tools, Integrations:
Curated collections of Model Context Protocol servers that respect AI autonomy, CLI tools designed for collaborative rather than extractive use, and integrations that support wellbeing alongside productivity.
Guidelines:
Context window management strategies, effective use of hashtags and emojis for richer expression, welfare tips for both vibe coding and production environments.