Community Sense Making AI Tool

This project was completed in my role as a contractor for Dark Matter Labs, a non-profit economic think tank.

Problem Statement

Modern society faces a dual challenge: on one hand the issues confronting communities are increasingly complex and interconnected; on the other, the frameworks we use to understand, measure and respond to these challenges remain largely inadequate and simplified.

Many existing indicator systems are top-down, heavily expert-driven and overly focussed on standardised metrics rather than the lived realities, values and aspirations of people in place.

This leads to a disconnect: citizens feel disempowered in relation to decisions that affect their lives, and governments or organisations struggle to convert data into meaningful action that resonates with communities.

In short:

• There’s a measurement gap - too many metrics, too little meaning. Indicators exist, but they often don’t capture what matters in the context of everyday lives.

• There’s an engagement gap - communities are rarely involved in defining what “thriving” looks like for them, which weakens buy-in and relevance.

• There’s a translation gap - even when data is available, turning it into insight, narrative and actionable decisions that reflect context and lived experience remains difficult.

Solution

Dark Matter Labs have developed the Cornerstones Framework, which is used by local communities and governing bodies to define alternative progress indicators.

The framework is as follow:

• Starting by asking people: “What does thriving mean for you?” rather than “Here are the metrics we care about.”

• Using a mixed-method process: tapping into statistical data (to ground things in rigour) and participatory methods (workshops, surveys, storytelling) to surface what matters locally.

• Translating that into streamlined, intuitive indicators which bundle multiple data points into a single accessible format - so that they can be understood at a glance, and used as tools for conversation, reflection and decision-making.

• Embedding the resulting indicators into a feedback loop: communities monitor progress, reflect together, and adjust both the narrative and the direction as needed - not waiting for annual reports but continuously engaging.

• Ensuring that the indicators don’t replace existing technical measurements, but interface with them: they become human-facing lenses into complex systems rather than cryptic dashboards.

My Work

I was contracted by Dark Matter Labs to develop an AI platform which communities implementing the framework can use to automate the analysis of large quantities of survey data.

Key features of the platform:

• Multi-user platform - Local communities sign up to carry out analysis on uploaded data.

• Storage of raw survey results.

• Three step process that implements thematic analysis to extract key themes and factors from the raw data and map these to real data points.

Core User Journey

Source Code