As a child, I used to believe in endless linear progress. There were ever higher buildings in the world, ever more TV channels, ever-faster computers and spacecraft. Records were broken, numbers got bigger, the complexity of everything increased. I saw this as the absolute good; actually, it was the only thinkable way of how a universe could work. Pop culture products such as Star Trek and Sid Meier's Civilization enforced this dogma.

In my teens, I started to notice the dark sides. New computer programs seldom showed progress in code quality anymore; on the contrary, it seemed that the growing hardware specs were making developers lazy, indifferent and incompetent. The way how tech media praised the growing clock rates started to sound idiotic, and the ever-growing mass of people buying high-spec PCs without even being interested in their deep internals was ever more despicable.

As a response, I started to embrace an opposite kind of esthetic and technological ideology: small is beautiful, bits are beautiful, hacks are beautiful. True progress is about deepness and compression instead of maximization and accumulation. Even apparently very simple structures may yield unexpected complexity – of an emergent, "countercomplex" kind instead of the "straightforwardly complex" kind.

At first, I took it mosty as a computer-related problem and a computer-related battle. But then I started to realize its relevance to the entire human technological civilization. Our economical-industrial system basically has a resource leak bug that most of us have learned to regard as a feature rather than a bug. Fixing it requires an overall shift to a mentality that values compression more than expansion and accumulation.

This is a kind of change that needs pioneers who experiment with more compressed technologies and societies before the planetary conditions force everybody to. I want to be among them.

II

Over the past few years, I have been hanging out and living with people who have interests and ambitions towards ecovillages, permaculture, appropriate technology and the like. I have also been deepening my relationship with natural processes by growing some edible plants on a field and gotten eer more fascinated about various neo-lowtech and "off-the-grid" ways of constructing dwellings, securing food production and holding up human culture.

My parents had a small organic farm when I was a kid, so it was not an alien world for me. However, when trying to learn about natural processes and their grassroots-level application in my usual analytical way, I noticed that I would have needed new tools to handle the complexity, uncontrollability and uncertainty. My existing methods of building mental models are not very good for learning about slow and complex natural processes.

Basically, I have two major studying modes. One is the aforementioned analytical mode I adopted when growing up with computer programming: get down to the lowest level of abstraction (such as ones and zeros) and then build up from there, layer by layer. If the mode does not seem effective, I tend to switch to the opposite mode that resembles the way how I explored my childhood forests: forget the strictness, just let your intuition guide your trial-and-error experiments. I was also studying neural networks at the time, making me even more anxious about the ineffectivity and limits of blocky intellectual analysis. I did not entirely realize that I would have needed some kind of an intermediate mode.

The trial-and-error mode is not problematic per se, it just needs a lot of cycles. After getting lost often enough in the same forest, a map gradually forms in the mind without any systematic mapping effort. Years ago, when learning to cook, I tried to find some kind of a theoretical ruleset of how the different ingredients and processes work but couldn't find any. So, I just went on with trial-and-error and let an intuitive "ruleset" form organically in my head, and I think I'm an okayish cook nowadays. When experimenting with the likes of plant-growing, however, the cycle is far too long for effective learning, so it needs decades to build a decent intuition about it.

Back in the seventies, computer hackers such as Ted Nelson advocated computers as a means of learning about how the world works. Simplified models of various real-world systems could be simulated by computer programs, allowing people to use the trial-and-error learning method to grow intuitive understanding about them. When trying to absorb the wisdom of Bill Mollison's Permaculture Designer's Manual, I started to hunger after a simulator where I could try to implement all kinds of crazy ideas in order to test them against the theory. Additionally, as a simulator like this would be necessarily based on knowable mathematics, I would also be able to use my analytical mode with it.

III

I have now been working for some time on this kind of "world simulator". Its work title is "Ovys", from the Finnish for "self-sufficient community simulator". It will be more like a game, a learning toy or an imagination assistant than a serious design/modelling tool, but I hope it will eventually end up being useful for some real-world planning as well. I also dream about coupling it with a machine learning system that could discover low-tech ideas from the blind spots of human visionaries.

I will write more about Ovys once it is closer to the first prototype stage. Anyway, it currently simulates solar radiation, airflow and heat transfer in various materials in a 3D grid world. After the first prototype (and perhaps some crowdfunding), I plan to implement the likes of the water cycle, plant growth, nutrient cycles and human agents at least in some kind of a "minecrafty" way that can be improved in later versions by other people.

As a game, one might describe it as a realism-oriented reimagination of Dwarf Fortress. Some day, one might perhaps even describe it as a realism-oriented reimagination of Civilization.