Comparing. Invariables and Summary
Next: Physical infrastructure as a YAML file.
Invariables
There are also many things that happen irrespective of the model (centralised or decentralised). This means that whichever way becomes prevalent, many things will turn out similar.
At least these things seem to be happening due to technical developments in any case:
Health assessments will be done at home and care will be personalised. Much more money and effort will be put into prediction and motivational services rather than disease treatment.
Energy system will become more decentralised with local technologies like solar, wind, geothermal, small modular reactors. These will be favoured at different places and different scale due to availability of resources, population density and access to capital. Energy systems will evolve to be very complex and this leads to emergent behaviours like extreme price swings with negative price bottoms. The need for national grid may diminish at least in the longer scope (in short and mid term it may actually increase due to intermittent energy sources).
Food production will increasingly be automated by precision farming. New methods like vertical gardens and bioreactors will enter the scene. Previously unused hard parts of plants will be utilised in biorefineries that can also scale to small unit sizes.
Self-driving cars will transform cities opening up lots of prime land for new uses in city centres, minimise traffic accidents, cause unemployment, change product structures etc.
Education will move to the networks and be available 24/7 for anyone with low cost and much of it free.
Art will be generated by automated machine learning models etc. The amount of generates art (pictures, music etc.) will sharply increase. Not so great ML generated content will create a blowback and create a yearning and demand for authenticity. This will still keep good artists’ earnings. Many artists will increase their output with ML tools.
Production will localise with 3D printers that can print metal, food, medicines, wood and plastics. Work will be increasingly done through the networks from anywhere in the world by distributed teams, some of which will never meet.
All of this will be driven by software, changing the world. Machine learning will do bulk of this software part.
Whether decisions (policy making) happen in centralised or decentralised manner, it’s the invariables that one should not forget when thinking of the future. They are the sure bet, as far as there are sure bets in a complex, chaotic systems.
And there are things that are possibilities.
Trend goes towards open sourcing. Digital designs are also software – made not for computers but different kinds of machines like 3D printers or self-organising flow chemistry modular facilities. And software wants to be free and shared globally.
New web3 models for organising work (fund raising, decision making and opt-in distributed work force and resources) are a good fit for this, but best does not always win. Path dependency is a powerful force as there is so much vested interest in following the current path. For example, centralised public decision making with a handful of parties and a dozen of their core leaders would have a diminished role. It is hard to see such change happening without resistance.
Natural monopolies will continue to be natural monopolies but their nature may change. Bigger infrastructure elements like harbours, airports, railways, roads, fleets of self-driving vehicles and drones may become self-owning. A model that isn’t really private or public but something new. Some natural monopolies may cease to be such.
Concepts like pop-up harbours, bridges and airports may bring subtle changes hard to foresee.
Summary
Current model is based on private enterprises generating products and services on the market place. Public side creates trust via its legal system allowing parties that do not know each other to safely conduct business. State takes as taxes a cut on all transactions (VAT and income tax) and funds services around natural monopolies.
In new model global autonomous organisations (DAOs) or Internet Native Organisations (INOs) are not owned by anyone. They act as the central orchestrators in networks through which economic activity flows. DAOs/INOs replace to some degree what states do today in key areas like infrastructure creation, health, education etc. and private corporations in many other aspects. But governments and private corporations do not go away. Anyone can join the web3 a networks and leave at will at any time. The rules of the DAO/INO define how value is divided.
Trust is created by the code that runs the DAO. When given rules match, the DAO always provides know results. The trick of DAOs is to write rules such that they under any given conditions incentivise wanted behaviour and punish/not-reward unwanted one. Also, natural monopolies can become DAOs. State may still take taxes to provide higher level trust in society in terms of defence and legal system. The immutability of the underlying blockchains is another trust building element,
Trend in old model is away from national states towards multi-national (supranational) organisations and contracts to solve global issues. The downside of this is that decision makers are far away from people that are affected by decisions. They salaries and job roples protect them from all illeffects. They have practically no skin in the game (direct accountability) and individuals have no method to oppose decisions as they’ve been made so “high up”. Decisions are made in political negotiations leading to sometimes to results that are against facts . Various non-democratic lobbying organisations and NGOs gain influence.
DAOs/INOs can also tackle global issues. In fact, when results are shared on open-source principles, every activity is global by nature – as example new code to automatically detect a disease from a sample can immediately be used anywhere. The problem is finding good organisational models that give the best people rewards that are as good as working on more commercial issues. Enthusiasm is not enough as there are bills to pay.
In current model quality assurance is a cost that is done once at the end of the production run before product is shipped to customer. In new model quality is a broad, value generating activity that is constantly performed and rewarded (bugs bounties % co): giving feedback, finding faults and telling about them, creating and fixing documentation and how-tos, online learning classes etc.
In current model basic research is done in universities sometime over decades before it gets commercialised by private companies who patent them (and increasingly also universities patent their researchers’ inventions). Access to latest and greatest normally requires licensing and paying related fees.
Cutting edge research still requires universities and expensive equipments. Still in new model designs are increasingly open sourced and anyone can use them as be building blocks. Innovation is much sped up as it is possible to study designs made by others and adopt the best parts into own work – also from unrelated fields. This releases the full potential of designs. Sharing code and data will solve to some degree the current replicability crisis of science. This especially if some funds are set aside as reward for people who find sloppy science and tainted data sets.
In current model work is supervised by a heavy layer of middle managers both in public and private organisations. There is much politics about where funds get allocated, the best narrator tends to win, not the best concept. Opportunity cost is never assessed (what else we could have done with the money). The focus is on continuing current business as the most powerful leaders are heading those units.
In the new model the management aspects of a company are automated by smart contracts. Likewise for enforcement of legal contracts between parties. Manual legal system still exists to handle corner cases but the bulk is automated. Machine learning models comb through these automated contracts to ensure that they work according to current legal framework (prevent unfair actions) or bugs bounty like constructs are used to reward people who find such foul play.
Computing in old model is going towards centralised cloud computing. In new model computing capabilities are decentralised and crowdsourced. Both models will grow in future. But should the centralised clouds be compromised and cease to exists, the global communities can continue with local data, tools and locally managed computing components.
Same difference is true for all production facilities. Old model favours economics of scale and global division of labor leading to very few countries and sometimes factories responsible for global supply of different goods. This creates a fragile system and great power imbalances when the production capacity is used as a weapon (trend getting more popular nowadays). New model decentralised capacities evenly everywhere.
This is not given as the future has not yet happened, but it is possible.