Building Humane Tech created HumaneBench to evaluate AI assistants against humane tech principles. But current evaluation approaches are limited: they're one-time tests, developer-focused, and disconnected from real user experiences and real-world deployment.
The Challenge: Build a framework that radically reimagines how we measure whether LLM applications uphold humane technology principles—and create real incentives for building humanely.
Paradigm-Shifting Approaches We're Excited About:
Living Evaluation
- Continuous monitoring in production rather than pre-launch testing
- Real-time humane-ness dashboards showing how products perform over time
- Adaptive tests that evolve with user behavior patterns
User-Driven Benchmarks
- Frameworks where actual users assess their lived experience against principles
- Crowdsourced evaluation datasets from diverse user populations
- Qualitative signals that capture "cared for" and "fulfilled" better than metrics
Pro-Humane Incentives
- Public leaderboards that create market pressure for humane design
- Certification systems (like B-Corp but for AI products)
- "Humane Score" badges that products can display
- App store integration or browser extensions showing humane ratings
Self-Healing Products
- Evaluation tools that don't just score but actively suggest fixes
- Automated generation of humane alternatives to problematic features
- AI that helps builders redesign inhumane patterns
Context-Aware Evaluation
- Industry-specific frameworks that understand nuanced violations
- Healthcare AI, education tools, social platforms, workplace productivity—each needs different lens
- Cultural context awareness (what's humane varies across cultures)
Multi-Stakeholder Scoring
- Evaluate impact on vulnerable populations, power users, casual users differently
- Surface whose well-being is being optimized vs. sacrificed
- Make trade-offs transparent
Integration as Safeguard
- Build evaluation into CI/CD pipelines to catch inhumane features before deployment
- Pre-commit hooks for humane-ness checks
- Automated testing that fails builds if principles are violated
Your Framework Should:
Deliverable Options (pick what fits your vision):
- Working prototype: Interactive tool, HumaneBench extension, dashboard, CI/CD integration, browser extension, API
- Comprehensive framework: Documented methodology with test scenarios, scoring rubric, implementation guide
- Hybrid: Proof-of-concept tool + clear documentation for expanding it
- Creative format: Decision tree, visual playbook, assessment game, certification system design
Whatever format you choose should be easy to navigate and demonstrate real-world applicability.
Who You're Building For:
Developers, product managers, designers, researchers, and non-technical creators who want practical tools to measure and improve humane-ness—whether they're building solo indie apps or working at major tech companies.
Both working prototypes and well-documented concepts are valuable—what matters is demonstrating genuine potential for real-world impact.
Evaluation Questions Your Framework Might Answer:
- How do you measure if an AI respects user attention vs. maximizing engagement?
- Can you detect when a "helpful" feature is actually manipulative?
- How do you evaluate humane-ness for non-technical builders?
- What makes a recommendation "caring" vs. "addictive"?
- How do you create incentives for companies to score well?
- Can evaluation happen continuously rather than just pre-launch?
- How do real users define "humane" in their own words?
Resources:
Building Humane Tech created HumaneBench to evaluate AI assistants against humane tech principles. But current evaluation approaches are limited: they're one-time tests, developer-focused, and disconnected from real user experiences and real-world deployment.
The Challenge: Build a framework that radically reimagines how we measure whether LLM applications uphold humane technology principles—and create real incentives for building humanely.
Paradigm-Shifting Approaches We're Excited About:
Living Evaluation
User-Driven Benchmarks
Pro-Humane Incentives
Self-Healing Products
Context-Aware Evaluation
Multi-Stakeholder Scoring
Integration as Safeguard
Your Framework Should:
Deliverable Options (pick what fits your vision):
Whatever format you choose should be easy to navigate and demonstrate real-world applicability.
Who You're Building For:
Developers, product managers, designers, researchers, and non-technical creators who want practical tools to measure and improve humane-ness—whether they're building solo indie apps or working at major tech companies.
Both working prototypes and well-documented concepts are valuable—what matters is demonstrating genuine potential for real-world impact.
Evaluation Questions Your Framework Might Answer:
Resources: