Version: 1.0.0-stage1 Date: 2025-12-02 Platforms: GitHub (primary) + GitLab (mirror)
This document provides templates for announcing the Behaviour Lab Stage 1 release across different channels.
- Evidence-based research on behavior engineering (priming, nudging, human-AI interaction)
- Strong ethical framework - not just guidelines, but mandatory requirements
- Replication-aware - learned from psychology's replication crisis
- Defensive awareness - help people recognize manipulation
- Staged publication - responsible release over 12 months
- Community-driven - open for peer review and feedback
- ❌ "Ultimate manipulation guide"
- ❌ "Control anyone's behavior"
- ❌ "Dark patterns library"
- ❌ "Commercial marketing toolkit"
- ❌ Overhype effectiveness without caveats
- "Introducing Behaviour Lab: Ethical Behavior Engineering Research"
- "Programming Human Behavior - Ethically: Behaviour Lab Stage 1 Release"
- "Evidence-Based Priming and Nudging: A New Framework for Ethical Behavior Change"
# Introducing Behaviour Lab: Evidence-Based Behavior Engineering with Ethics Built-In
**TL;DR:** Today I'm releasing Stage 1 of Behaviour Lab - 190 pages of research on priming, nudging, and human-AI interaction, with a strong ethical framework. It's designed for defensive awareness and beneficial applications, not exploitation.
## What This Is
Behaviour Lab is a research project examining how human behavior can be influenced through:
- **Priming** - Cognitive activation effects (not discredited social priming)
- **Nudging** - Choice architecture and behavioral economics
- **Human-AI Interaction** - How AI agents can prime humans through output design
The goal: Understand these mechanisms well enough to:
1. **Defend against them** (recognize when you're being manipulated)
2. **Use them ethically** (education, therapy, beneficial behavior change)
3. **Build responsibly** (AI systems that respect human autonomy)
## Why Publish This?
This knowledge already exists, scattered across academic papers and industry reports. The dual-use risk isn't in sharing the research - it's in NOT sharing it, leaving only bad actors to study it systematically.
**Publishing with safeguards > keeping it secret.**
## What's Different About This Work?
### 1. Replication-Aware
Psychology went through a replication crisis. Social priming effects (the famous ones) largely failed to replicate. This work:
- Only includes HIGH evidence techniques with successful replications
- Clearly marks discredited approaches
- Includes confidence scores and effect sizes
### 2. Evidence-Tier Classification
Every technique is rated:
- ⭐⭐⭐⭐⭐ HIGH: Strong evidence, replicated, clear mechanisms
- ⭐⭐⭐⭐ MODERATE: Good evidence, some replications
- ⭐⭐⭐ LOW: Preliminary evidence
- ❌ DISCREDITED: Failed replications
### 3. Human vs. AI Agent Priming
Novel synthesis showing how AI agents can prime humans through:
- Semantic consistency across agents (20-40% boost)
- Visual presentation patterns
- Behavioral modeling
- Sequential document staging
This is increasingly relevant as we interact more with AI systems.
### 4. Strong Ethical Framework
Not just "please use responsibly" - mandatory requirements enforced through license:
**CC BY-NC-SA 4.0 + Ethical Use Requirements:**
- ✅ Beneficence: Genuinely benefit people
- ✅ Informed Consent: Get permission
- ✅ Autonomy: Preserve choice
- ✅ Transparency: Disclose methods
- ✅ Non-Maleficence: Do no harm
- ✅ Reversibility: Allow opt-out
**Prohibited:**
- 🚫 Commercial manipulation without consent
- 🚫 Exploitation of vulnerabilities
- 🚫 Dark patterns and deception
- 🚫 Coercion
License terminates automatically if violated. Community reporting system for enforcement.
### 5. Staged Publication
I'm not releasing everything at once. Three stages over 12 months:
- **Stage 1 (Today):** Research foundation - educational, lower risk
- **Stage 2 (Month 5-6):** System design - after peer review
- **Stage 3 (Month 12+):** Implementation details - gated access with review
This gives time to assess community response and strengthen safeguards.
## What's Included in Stage 1?
### Research (140 pages):
- **Priming Foundation** - Evidence-based cognitive priming with neural mechanisms
- **Nudging Techniques Catalog** - 15+ techniques with evidence tiers
- **Human vs. AI Agent Priming** - Novel integration analysis
### Governance (50 pages):
- **LICENSE.md** - Legal framework with ethical requirements
- **CODE_OF_CONDUCT** - Community standards
- **MISUSE_REPORTING** - How to report violations
- **CONTRIBUTING** - How to participate ethically
- **ETHICS_REVIEWERS** - Peer review strategy
### Code:
- **Priming Analyzer** - Working Python prototype demonstrating concepts
## Who Is This For?
**Primary audiences:**
- **Researchers** studying behavior change, human-AI interaction
- **Defenders** wanting to recognize manipulation
- **Ethical practitioners** in UX, education, therapy
- **AI developers** building human-facing systems
- **Policymakers** regulating persuasive technology
**NOT for:**
- Commercial marketers seeking exploitation techniques
- Dark pattern designers
- Anyone wanting to manipulate without consent
## How to Get Involved
**GitHub (Primary):** [github.com/[username]/behaviour-lab](https://github.com/[username]/behaviour-lab)
**GitLab (Mirror):** [gitlab.com/[username]/behaviour-lab](https://gitlab.com/[username]/behaviour-lab)
1. **Read the research** - Start with README.md
2. **Provide feedback** - Open a Discussion
3. **Report concerns** - See MISUSE_REPORTING.md
4. **Contribute ethically** - See CONTRIBUTING.md
## Community Review Welcome
This work underwent internal safety review, but I need broader input:
- **Academic reviewers** - Is the evidence sound?
- **Ethics experts** - Are the safeguards sufficient?
- **Practitioners** - Is this useful for defensive awareness?
- **Critics** - What am I missing?
Open a Discussion or email [your-email].
## Final Thoughts
Behavior engineering is powerful. It's already being used - by marketers, app designers, political campaigns, AI systems. The question isn't whether this knowledge exists, but who has access to it and how it's used.
I believe:
- **Transparency > obscurity** for dual-use research
- **Community oversight > individual control**
- **Defensive awareness > ignorance**
- **Ethics-by-design > ethics-as-afterthought**
This is my attempt at responsible publication. It won't be perfect. I'm counting on the community to help strengthen it.
**Let's build ethical behavior engineering together.**
---
**Repository:** [github.com/[username]/behaviour-lab](https://github.com/[username]/behaviour-lab)
**License:** CC BY-NC-SA 4.0 + Ethical Use Requirements
**Stage:** 1 of 3 (Research Foundation)
**Feedback:** Discussions tab or [your-email]🧠 THREAD: Introducing Behaviour Lab - evidence-based research on priming, nudging, and human-AI interaction. With a twist: ethics built-in, not bolted-on.
190 pages of research. Strong safeguards. Staged publication. Open for peer review.
🧵 1/12
---
2/ What is this?
Research on how to ethically influence human behavior through:
• Cognitive priming (evidence-based, not the discredited social stuff)
• Nudging & choice architecture
• Human-AI interaction design
Goal: Defensive awareness + ethical applications
---
3/ Why publish this?
This knowledge already exists. Publishing with safeguards > keeping it secret.
Bad actors already study this. Let's make sure defenders, researchers, and ethical practitioners have access too.
Transparency > security through obscurity.
---
4/ What's different?
✅ Replication-aware (learned from psych's crisis)
✅ Evidence-tier classification (HIGH/MOD/LOW)
✅ Only includes replicated findings
✅ Neural mechanisms documented
✅ Effect sizes + confidence scores
No BS. No overhype. Just evidence.
---
5/ Novel contribution: Human vs. AI agent priming
First comprehensive analysis of how AI agents can prime humans through:
• Semantic consistency (20-40% boost with multi-agent)
• Visual presentation patterns
• Behavioral modeling
• Sequential document staging
Timely as AI interactions increase.
---
6/ Ethics aren't optional.
License: CC BY-NC-SA 4.0 + MANDATORY ethical requirements
✅ Beneficence, Consent, Autonomy, Transparency
🚫 Commercial manipulation, exploitation, dark patterns
License TERMINATES if violated. Community enforcement via reporting system.
---
7/ Staged publication over 12 months:
• Stage 1 (today): Research foundation - educational
• Stage 2 (month 5-6): System design - after peer review
• Stage 3 (month 12+): Implementation - gated access
Time to assess response, strengthen safeguards, adapt.
---
8/ What's included in Stage 1?
Research (140 pages):
• Priming Foundation
• Nudging Techniques Catalog
• Human vs. AI Agent Priming
Governance (50 pages):
• LICENSE, CODE_OF_CONDUCT, MISUSE_REPORTING
• Ethics review framework
Code:
• Working Python prototype
---
9/ Who is this for?
✅ Researchers (behavior change, HCI, AI ethics)
✅ Defenders (recognize manipulation)
✅ Ethical practitioners (UX, education, therapy)
✅ AI developers (human-facing systems)
❌ NOT for marketers seeking exploitation techniques
---
10/ Evidence tier examples:
⭐⭐⭐⭐⭐ HIGH: Direct repetition priming (d=0.80, 95% replications)
⭐⭐⭐⭐ MODERATE: Default effects (d=0.50, context-dependent)
❌ DISCREDITED: Social behavioral priming (failed replications)
Only the real stuff. No wishful thinking.
---
11/ Community review needed:
I did internal safety review, but I need YOUR input:
• Academics: Is evidence sound?
• Ethics experts: Are safeguards sufficient?
• Practitioners: Useful for defense?
• Critics: What am I missing?
Open Discussions or DM me.
---
12/ Final thought:
Behavior engineering is powerful. It's already being used. The question is who has access and how it's used.
I'm betting on: transparency > obscurity, community > individual, defensive awareness > ignorance.
Let's build ethical behavior engineering together. 🧠✨
🔗 https://github.com/[username]/behaviour-lab
CC BY-NC-SA 4.0 + Ethics
Stage 1 of 3
Feedback welcome
/end
🧠 Introducing Behaviour Lab: Evidence-Based Behavior Engineering with Built-In Ethics
After two months of research and safety review, I'm releasing Stage 1 of Behaviour Lab - a comprehensive study of priming, nudging, and human-AI interaction, designed for defensive awareness and ethical applications.
📚 What's Included:
• 190 pages of research on cognitive priming, choice architecture, and how AI agents can influence humans
• Evidence-tier classification system (only replicated findings)
• Strong ethical framework (not guidelines - mandatory requirements)
• Community governance and misuse reporting system
• Working Python prototype
🛡️ Why Ethics Matter:
This is dual-use knowledge. It can help people recognize manipulation OR enable new forms of exploitation. I chose to publish with safeguards rather than keep it private:
License: CC BY-NC-SA 4.0 + Ethical Use Requirements
• ✅ Beneficence, informed consent, autonomy, transparency
• 🚫 Commercial manipulation, dark patterns, coercion
• Automatic termination for violations
📅 Staged Publication:
• Stage 1 (Today): Research foundation - educational focus
• Stage 2 (5-6 months): System design - after peer review
• Stage 3 (12+ months): Implementation details - gated access
This gives time to assess community response and strengthen protections.
🎯 Who Should Care:
• Researchers in HCI, behavioral science, AI ethics
• UX designers wanting to avoid dark patterns
• AI developers building human-facing systems
• Policymakers regulating persuasive technology
• Anyone who wants to recognize when they're being primed/nudged
🔬 Novel Contribution:
First comprehensive analysis of how AI agents can prime humans through output design. Particularly relevant as we interact more with LLMs and AI systems. Shows 20-40% boost from multi-agent semantic consistency.
🤝 Community Review Welcome:
This underwent internal safety review, but I need broader input. Open to feedback from:
• Academic researchers (evidence quality)
• Ethics experts (safeguard sufficiency)
• Practitioners (practical utility)
• Critical reviewers (blind spots)
📖 Access:
GitHub (primary): github.com/[username]/behaviour-lab
GitLab (mirror): gitlab.com/[username]/behaviour-lab
Open Discussions for questions/concerns, or message me directly.
This is my attempt at responsible dual-use research publication. It won't be perfect - counting on the community to help strengthen it.
Let's build ethical behavior engineering together. 🧠✨
#BehavioralScience #AIEthics #HumanComputerInteraction #Ethics #Research #OpenScience #Nudging #Priming #ResponsibleAI
"[New Release] Behaviour Lab: Evidence-Based Priming & Nudging Research with Ethical Framework"
Dear [Mailing List / Research Community],
I'm writing to share Stage 1 of Behaviour Lab, a research project examining evidence-based behavior influence mechanisms with a focus on ethical applications and defensive awareness.
## Research Scope
The project synthesizes recent findings on:
1. **Cognitive Priming** (post-replication crisis)
- Evidence-tier classification of effects
- Neural mechanisms (fMRI, representational sharpening)
- Temporal dynamics and boundary conditions
- Clear distinction from discredited social priming
2. **Nudging & Choice Architecture**
- MINDSPACE and EAST frameworks
- 15+ techniques with evidence ratings
- Domain-specific applications
- Meta-analytic effect sizes
3. **Human-AI Agent Interaction** (Novel Contribution)
- Comparative analysis of priming mechanisms
- Multi-agent consistency effects (20-40% boost)
- Sequential document staging techniques
- Practical implementation patterns
## Methodological Rigor
- Only includes findings with successful replications
- Effect sizes reported (Cohen's d)
- Confidence scores based on evidence quality
- Neural mechanisms documented where available
- Explicit marking of discredited approaches
## Ethical Framework
Given the dual-use nature of this research, the work includes:
- Mandatory ethical use requirements (license-enforced)
- Community governance structures
- Misuse reporting system
- Staged publication approach (12 months)
- Continuous safety review process
License: CC BY-NC-SA 4.0 + Ethical Use Requirements
## Publication Strategy
**Stage 1 (Current):** Research foundation - educational focus, lower risk
**Stage 2 (Month 5-6):** System design - after peer review
**Stage 3 (Month 12+):** Implementation details - gated access
## Community Review Sought
I welcome feedback on:
- Evidence quality and interpretation
- Ethical framework sufficiency
- Methodology and rigor
- Potential risks or blind spots
- Practical utility for defensive awareness
## Access
Repository: https://github.com/[username]/behaviour-lab
Mirror: https://gitlab.com/[username]/behaviour-lab
Key documents:
- `/research/priming-foundation.md` - Core evidence review
- `/research/nudging-techniques-catalog.md` - Comprehensive catalog
- `/research/human-vs-agent-priming.md` - Novel integration
- `/LICENSE.md` - Ethical use requirements
Feedback via GitHub Discussions or direct email: [your-email]
## Citation
If you reference this work:
Murphy, D. (2025). Behaviour Lab: Evidence-Based Behavior Engineering with Ethical Framework (Version 1.0.0-stage1) [Software/Research]. https://github.com/[username]/behaviour-lab
See `/CITATION.md` for full citation formats.
---
This is an attempt at responsible dual-use research publication. I believe transparency with safeguards serves the research community better than secrecy. I welcome critical engagement.
Best regards,
[Your Name]
[Your Affiliation]
[Contact Information]
Title: Behaviour Lab: Evidence-Based Behavior Engineering with Ethics-by-Design
Abstract:
This presentation introduces Behaviour Lab, a research project synthesizing evidence-based findings on cognitive priming, nudging, and human-AI interaction with an integrated ethical framework.
The project addresses three key challenges in behavior engineering research:
1. **Replication Crisis:** Post-crisis, which priming effects survive? We present an evidence-tier classification system distinguishing robust findings (e.g., direct repetition priming, d=0.80) from discredited effects (social behavioral priming).
2. **Dual-Use Risk:** How to share powerful behavior influence knowledge responsibly? We demonstrate a staged publication approach with license-enforced ethical requirements and community governance.
3. **Human-AI Interaction:** How do priming mechanisms differ between humans and AI agents? We present novel analysis showing 20-40% boost from multi-agent semantic consistency, with implications for AI system design.
Key contributions:
- Comprehensive evidence review with replication rates and effect sizes
- Evidence-tier classification (HIGH/MODERATE/LOW/DISCREDITED)
- First systematic analysis of human vs. AI agent priming mechanisms
- Working ethical framework for dual-use behavioral research
- Open-source implementation with community oversight
The work is published under CC BY-NC-SA 4.0 with additional ethical use requirements, employing a three-stage release over 12 months to allow community review and safeguard strengthening.
We argue that for dual-use research, transparency with robust safeguards serves society better than secrecy, and present our framework as a model for responsible publication.
Keywords: behavioral science, priming, nudging, AI ethics, dual-use research, evidence-based practice, replication crisis
Repository: github.com/[username]/behaviour-lab
Title: [R] Behaviour Lab: Evidence-Based Priming & Nudging Research with Ethical Framework (Stage 1 Release)
Post:
Hi everyone,
I'm releasing Stage 1 of Behaviour Lab - a research project on cognitive priming, nudging, and human-AI interaction, with a strong focus on ethics and defensive awareness.
## What This Is
190 pages of research synthesizing:
- **Cognitive priming** (post-replication crisis - what actually works?)
- **Nudging techniques** (evidence-tier classification)
- **Human vs. AI agent priming** (novel contribution)
Plus: Working Python prototype and comprehensive ethical framework.
## Why I'm Sharing This
This knowledge exists. Publishing with safeguards > keeping it secret.
Goal: Help people **recognize manipulation** + enable **ethical applications** (education, therapy, etc.)
## Key Features
**Replication-Aware:**
- Only includes effects with successful replications
- Clearly marks discredited approaches (social priming, subliminal messaging)
- Effect sizes + confidence scores
**Evidence Tiers:**
- ⭐⭐⭐⭐⭐ HIGH: Direct repetition priming (d=0.80, 95% replication rate)
- ⭐⭐⭐⭐ MODERATE: Default effects (d=0.50, context-dependent)
- ❌ DISCREDITED: Social behavioral priming (failed to replicate)
**Novel Analysis:**
First comprehensive look at how AI agents can prime humans:
- Multi-agent semantic consistency (20-40% boost)
- Visual presentation patterns
- Sequential document staging
**Strong Ethics:**
CC BY-NC-SA 4.0 + **mandatory** ethical requirements:
- ✅ Beneficence, consent, autonomy, transparency
- 🚫 Commercial manipulation, dark patterns, coercion
- License terminates if violated
**Staged Publication:**
- Stage 1 (today): Research foundation
- Stage 2 (5-6 months): System design (after peer review)
- Stage 3 (12+ months): Implementation (gated access)
## What's Included
- `/research/priming-foundation.md` - Evidence review with neural mechanisms
- `/research/nudging-techniques-catalog.md` - 15+ techniques cataloged
- `/research/human-vs-agent-priming.md` - Novel integration
- `/src/priming_analyzer.py` - Working prototype
- Full governance framework (LICENSE, CODE_OF_CONDUCT, MISUSE_REPORTING)
## Community Feedback Welcome
This underwent internal safety review, but I need broader input:
- Are the safeguards sufficient?
- Is the evidence interpretation sound?
- What risks am I missing?
- Useful for defensive awareness?
## Links
**GitHub:** https://github.com/[username]/behaviour-lab
**GitLab:** https://gitlab.com/[username]/behaviour-lab
Open to critical feedback via Discussions or comments here.
## Citation
Murphy, D. (2025). Behaviour Lab: Evidence-Based Behavior Engineering with Ethical Framework (v1.0.0-stage1). https://github.com/[username]/behaviour-lab
---
**My reasoning:** Dual-use research benefits from transparency + safeguards > secrecy. Counting on community to help strengthen this.
Thoughts?
🧠 Launching Behaviour Lab - evidence-based research on priming, nudging, and human-AI interaction.
With a twist: ethics BUILT-IN, not optional.
190 pages of research. Only replicated findings. Strong safeguards. Staged publication over 12 months. Open for peer review.
Key innovation: First systematic analysis of how AI agents can prime humans through output design (20-40% boost from multi-agent consistency).
License: CC BY-NC-SA 4.0 + mandatory ethical requirements
- ✅ Defensive awareness, education, therapy
- 🚫 Commercial manipulation, dark patterns
For researchers, defenders, ethical practitioners. NOT for exploitation.
Stage 1 (today): Research foundation
Stage 2 (5-6mo): System design after peer review
Stage 3 (12mo+): Implementation with gating
Feedback welcome: github.com/[username]/behaviour-lab
#BehavioralScience #AIEthics #OpenScience #Research #Priming #Nudging #Ethics
This is my attempt at responsible dual-use research publication. Transparency with safeguards > secrecy.
Let's build ethical behavior engineering together. 🧠✨
Title: Behaviour Lab: Evidence-Based Priming and Nudging Research with Ethical Framework
URL: https://github.com/[username]/behaviour-lab
Comment (if needed):
Author here. This is Stage 1 of a research project on cognitive priming, nudging, and human-AI interaction.
Key points:
1. **Replication-aware**: Only includes effects that survived psychology's replication crisis. Social priming is marked as discredited.
2. **Evidence tiers**: Every technique rated HIGH/MODERATE/LOW with effect sizes, replication rates, and neural mechanisms.
3. **Novel contribution**: First systematic analysis of how AI agents can prime humans. Relevant for anyone building LLM-based systems.
4. **Ethics built-in**: Not just "use responsibly" - mandatory requirements in the license (CC BY-NC-SA 4.0 + ethical use terms). License terminates if violated.
5. **Staged publication**: Releasing over 12 months. Stage 1 (today) = research foundation. Stage 2 (5-6mo) = system design after peer review. Stage 3 (12mo+) = implementation details with gating.
Dual-use research is tricky. My bet: transparency with safeguards > secrecy. This knowledge already exists - better to share it with defensive awareness angle + community oversight.
Open to critical feedback, especially on:
- Ethical framework sufficiency
- Evidence interpretation
- Risks I'm missing
190 pages of research + working Python prototype + full governance framework.
Happy to answer questions.
Before publishing announcements:
- Update placeholders: Replace
[username],[your-email],[Your Name], etc. - Verify links: Test all GitHub/GitLab URLs
- Proofread: Check for typos and clarity
- Tone check: Emphasize ethics, avoid hype
- Length check: Adjust for platform limits (Twitter 280 chars per tweet)
- Hashtags: Research relevant community hashtags
- Timing: Post during high-engagement hours for your audience
- Cross-posting: Coordinate timing across platforms
- Monitoring: Set up alerts for responses
Track engagement for each channel:
Week 1:
- Stars/followers gained
- Discussion comments
- Shares/retweets
- Media mentions
- Critical feedback quality
Month 1:
- Academic citations/references
- Fork activity (+ ethical compliance check)
- External implementations
- Misuse reports (hopefully 0)
Adjust messaging based on:
- Misunderstandings to clarify
- Questions asked frequently
- Concerns raised repeatedly
- Positive engagement patterns
Always emphasize:
- Evidence-based (replicated findings only)
- Ethical framework (mandatory, not optional)
- Defensive awareness (recognize manipulation)
- Staged approach (responsible release)
- Community-driven (open to feedback)
Never claim:
- Perfect control over behavior
- 100% effectiveness
- No risks or downsides
- Suitable for all applications
- Better than existing alternatives
Choose the channels that match your audience:
- Blog/Website: Template 1 (long-form)
- Twitter/X: Template 2 (thread)
- LinkedIn: Template 3 (professional)
- Academic: Template 4 (email/conferences)
- Reddit: Template 6 (community discussion)
- Mastodon/Bluesky: Template 7 (short-form)
- Hacker News: Template 8 (tech audience)
Timing: Coordinate announcements within 24-48 hours of GitHub/GitLab launch.
Monitoring: Set up Google Alerts and notification systems BEFORE announcing.
Be ready: To respond to questions, concerns, and feedback within 24 hours during Week 1.
Let's launch this responsibly. 🧠✨