The world as we know it is built on a series of rules. Some of these are defined by the foundational principles of the universe, thermodynamics, gravity. They are unchanging. We observe them, our understanding may change, we may push against them, but we do not change the rules.
But there are other rules that are governed by us, the people. These are societal rules, they are rules of how we operate. And though some things do change, many of our current structures have been designed and operate in ways that haven’t been updated for the current world, or for the world we want to see.
Since the invention of computers and the entrance of programming into mainstream society, people have been exploring different rules. Programmers inventing, adapting, collaborating on new languages, new frameworks, new methods of how to operate. And we’ve come far in that space.
We’ve taken huge leaps, at least in part because we are unbound by the normal rules of our society. People have worked together across borders to create new languages. We have placed an emphasis on open collaboration. We have developed new methods of governance. We have defined new possibilities.
We’ve now moved into a new era, one where AI is hailed as the new saviour, promising to fundamentally change the world. Whether you believe that or not, it’s clear that the growing potential of AI is changing the way we work, but perhaps we should be thinking about how to go deeper and fundamentally change how we work in the future.
Data as code
I think if we explore some of the concepts of AI and apply them to the non-digital world, perhaps we could change how we view our world and our work. If for example we look at this definition of AI from the oecd, we see that any AI system is a combination of the model + input + data. What is important, at least for me, is a recognition that the training data is as integral to an AI system as the model itself, shaping its functionality and effectiveness.
And where does this training data come from? Most of the larger LLM’s are trained on data scraping from the web, or content from Reddit, Twitter, or Facebook. The vast majority of this content has been produced by us, the people. This content is a fundamental part of the code of most AI systems. The data is as much of the code as the model is.
The progress we have made in the digital and data space has been both rapid and sustained. With each new development, there has been an effort to build supporting infrastructure so that new developments can be built upon the foundations of what came before. We are rarely starting from scratch, with methodology, documentation, repositories, tools all created and maintained for the commons which help to advance development. In the digital world, we can make progress individually and contribute to the commons simultaneously, in the open.
From the digital playground to real life
In many ways, it feels like we have devoted more time and effort to reshaping how we want the world to be in the digital playground, than we have in society. This is especially true in the social purpose sector.
The UK charity sector has over 160k organisations, employing nearly 1m people. And if we add in community businesses and social enterprises we see a social purpose sector that may be approaching 250k organisations, all of which work to support a better world.
But we also see a sector often working individually, starting from scratch again and again because the open infrastructure and ways of working are not there to support people and organisations. The way we operate and the systems we have are designed for individualism, for duplication, for top down efficiency, for static concepts and fragmented development. We have created our own closed loop systems, with a constant recycling of old ideas. We’ve limited ourselves, stifled creativity and lost so much learning.
Couldn’t we do better?
People as code
What if we blend some of the concepts being explored in the digital and data space, with real world human concepts of how to work, especially in the social purpose sector? What if we, as creators and contributors, re-envision ourselves not just as code providers but as the code itself?
I’ve framed this blending of ideas as People as Code.
I think of People as Code as more than a concept; it’s a call to action to change how we work, by adopting approaches that we’ve shown to be successful in the digital playground. I believe if we adopt these principles we can eventually set out a blueprint for a future where technology and data serve humanity in its most inclusive, participatory, and dynamic form. I see it as a future where we adapt the learnings from the digital playground into real world applications and bring them together with the capabilities of data & technology, reshaping how we work to improve our world.
I’m particularly interested in exploring how People as Code alters how we view and operate in the philanthropic ecosystem. What if in the future, a set of philanthropic foundations become more than just funders; they are catalysts for sustainable, people-driven change? What if these funders are now framework builders, establishing platforms for innovation, for generating open ideas, for facilitating data-driven decision-making, providing the structure, resources, and guidance, but the ‘code’ — the actual implementation and adaptation of social initiatives — is in the hands of the people.
Within this approach we adopt principles of open-source development, shifting governance and decision making to be open, transparent, and documented. People are not just challenges to be addressed, nor data points, but active contributors, akin to developers in an open-source project, who collaboratively shape and evolve the policies and programs that affect them.
In this future vision people and organisations have and use data to understand, improve, adapt, and to act, rather than demonstrate. In this future we design technology to fit around and support how we want to work. And in this future these foundations, this foundation which is tended by many, supports all other actors to understand, learn, build and act in collaboration, in the open.
Exploring the future
So at this point, I’m left with a lot of questions. Some of these questions are about what a future could look like. Some of these questions are about how we get there. For now I’ll explore some questions, which I hope are prompts for a discussion with you, the reader.
- We move to a model of both short and long term thinking where rapid development is supported by the frameworks and open source libraries built and maintained by collaborators?
- We create & grow technologies and methods that meet the needs of those doing the work?
- People and organisations act as autonomous agents within the model in the short term, and actively redefine the model in the long term?
- We work on both the micro and macro scale, all at once?
- We know who is working on what and how, and they are connected?
- Exploration is valued, encouraged and supported in the open?
- Focused on technology and data to help work more effectively rather than more efficiently?
- Data is owned and governed by people who choose how and where data can be used?
- We are more attuned to how ethical and equitable our approach to data and technology is?
- We maintained sector wide digital warehouses to host open source products built by and for social good?
- Invested what is needed to build and maintain social good digital infrastructure?
Next time i’ll be exploring what this might look like in practice, at least to me.
This is me exploring a concept I’ve been pondering. I don’t know where this will end up, how long this will take, nor even if it is a good concept. It may be that you’ve already had this idea, or that nothing here is new. But I will write, as a way of exploration.
I plan to write about the concept, what it is, where it comes from, and most importantly how it could shape things in practical ways in areas I’m most interested in. Feel free to join me.