Project SHAME - Sustainable Human Accountability Metrics Engine

Project SHAME — Sustainable Human Accountability Metrics Engine is a wider project I will introduce here gradually.

This first post is about one part of it: 1001 Stories for Children Growing Up with AI, a bilingual family learning project I have been building with my children over the past few months.

We are creating one bilingual English–Chinese moral story each day using local AI, OpenAI image generation, Qwen3-TTS, forced alignment, PHP, Three.js, FFmpeg, and my main project, SPARK — Simple Personal AI Reasoning Kernel.

It is the first visible part of a much larger project, built from several of the systems and ideas I have already posted on the forum.

The playlist is here:

The project is still evolving story by story, but it is now running and publishing every day.

Project ACRONYM — Agentic Creative Reasoning for Original Names, Yielding Meaning — is a new AI-assisted naming project I have been developing.

ACRONYM uses GPT-based transformer language models, agentic reasoning techniques, semantic analysis, iterative candidate generation, scoring, and refinement to produce acronym expansions that are memorable, relevant, and natural rather than simply forcing unrelated words into the required letters.

The project began with a simple demonstration of the technology: creating a suitable meaning for A.C.R.O.N.Y.M. itself. The result became both the product name and a working example of what the system is designed to do for you, quickly and automated.

Nice to see you again, @_j , I’ve had a long and painfully lonely break…

SHAME works almost in the opposite direction. I started with the existing meaning of “shame” as something systems can impose on people, then flipped it into Sustainable Human Accountability Metrics Engine: an attempt to make scaling systems accountable to humanity instead.

I have to credit my son for the videos themselves; he has done the production work, including using my cloned voice for the narration :slight_smile: My Chinese is nowhere near as fluent.

Sounds like you have been working on some sweet tech while I have been gone.

Hi. What I “worked on” in this reply was defining the input parameters of a target backronym, a domain and scope, and technology definitions from which language can be pulled from for developing an AI output, then shaping that into a message for AI. Then also creating the language that could follow an existing template in announcing a project.

That, then, ChatGPT could deliver the results and I could get them posted 8 minutes after your topic hit the forum speaks that there is no moat for a developer of such an AI-powered idea: anybody can ask ChatGPT.

I certainly have some forum topics here with more interesting stuff. Good to see you’re still AI Powered!

Certainly for the final draft it’s probably safer lol

“Read ten thousand books and travel ten thousand miles.”

读万卷书,行万里路。
Dú wàn juàn shū, xíng wàn lǐ lù.

It reminds us that understanding comes from combining learning through books with learning through lived experience.

Project SHAME is not one thing.

It would be easy to make it only about moral stories.

The stories are the foundation. Through our 1001 Stories project, we are using AI to help our children learn through stories in English and Chinese.

But from stories, we move into the wider world.

“A journey of a thousand miles begins with a single step.”

千里之行,始于足下。
Qiānlǐ zhī xíng, shǐ yú zúxià.

So we begin with something simple and measurable:

Walking.

My children and I are committing to walking an average of 6.4 kilometres each day.

Counted across the three of us over the 1,001 days of the project, the accumulated distance becomes a symbolic journey to China and back again—connecting the two countries, cultures and parts of our family story.

The symbolism is not merely about displacement.

It is about demonstrating that the journey can actually be made.

We will not physically follow a straight line to China, but the distance walked will be real. A journey that appears impossibly large can be completed through a small, measurable action repeated each day.

One step does not cross a continent.

But one step, repeated consistently, becomes a journey.

As we walk, we will use AI to help our children regain Chinese—their home language.

Chinese will not be separated from life and confined to a lesson screen. We can learn and practise the words for the places, plants, animals, weather, objects and experiences we encounter as we move through the world together.

The walk therefore becomes physical movement, language learning, family time and lived education at once.

It is an attempt to give our children a foundation in childhood from which they can face the future—wherever in the world they eventually live.

At the same time, we are trying to account for the material cost of our lives as accurately as we are able: the food we consume, the electricity and water we use, the energy required to heat our home, and the journeys we make.

Not because a life can be reduced to a spreadsheet.

It cannot.

Language, health, belonging, family time and direct experience all matter, even when their value cannot be represented adequately by a number.

Some things can be measured precisely. Others can only be recognised.

That does not make them less valuable.

Walking alone will not solve climate change. But it begins the process of honestly accounting for how we move through the world, while demonstrating that a large commitment does not have to remain abstract.

The World Health Organization’s climate and health fact sheet states that climate change is expected to cause approximately 250,000 additional deaths each year between 2030 and 2050 from undernutrition, malaria, diarrhoea and heat stress.

But this is not an estimate of the total human cost.

The underlying WHO quantitative risk assessment explicitly considers only a subset of possible health effects. It cannot fully account for the wider burden of illness, displacement, ecosystem loss, disrupted food and water systems, or the many indirect consequences that are harder to model.

The true human cost may therefore be substantially greater.

This matters because what we measure is not necessarily the whole cost.

A projection gives measurable weight to a possible future, but it does not contain the whole of that future.

To me, this is where AI becomes genuinely intelligent.

Not because it can answer every question, but because it can help us construct artificial systems that are measurably beneficial—systems that counterbalance the incentives we have already created.

In that sense, this project is itself a form of artificial intelligence.

It is an intentionally constructed system connecting stories, language, movement, family life, consumption and accountability. It measures what can be measured without pretending that measurement captures everything.

Today’s systems drift naturally towards what scales, what profits and what is easiest to count.

Money became an extraordinarily successful accounting system, but it was never capable of accounting for everything that matters.

Project SHAME asks whether intelligence can help us account differently.

Can we account for what we consume without pretending consumption is the whole of life?

Can we account for what we protect, what we create and what we leave behind?

Can we recognise the value of a child regaining a home language while walking beside a parent, even when that value cannot be expressed adequately in money?

The walk is small enough to begin today, but large enough to accumulate into something real.

That is the wider purpose of Project SHAME.

Not to replace money.

But to explore what a more intelligent system of accountability might look like—and to give our children a foundation from which they can understand, measure and survive the world they inherit.

I look forward to sharing the technical implementation of this project as we progress.