Intelligent Money & Cognitive Economies

“We reject kings, presidents, and voting. We believe in Rough Consensus and Running Code.”  David Clark, 1992 

The above quote while originally intended to express many technologists’ view on the matter of internet standardization, also beautifully represents their political and sociotechnical values when it comes to the matter of our economic evolution: that is, rough consensus & running code. 

In An Inquiry into The Nature and Causes of The Wealth of Nations, Adam Smith overcame the constraints of his time in realistically modelling the economic complexity by attributing its emergence to an “invisible hand”. However today we have better techniques to make an accurate representation of the roles, resource flow and the contractual associations among various systems, economic agents and their networks, giving us a possibility to implement “money” as an intelligent self-governing system.

The idea is not new. In pre-cryptocurrency world (2002), Charles Goldfinger briefly wrote about it in ‘Intangible Economy & Electronic Money’, assessing that eventually our finances and money instruments et all will evolve to act intelligently, following an AI agent design paradigm. Thus the global financial system will (somewhat does but not very well) work as a finitely-generated dynamic system consisting of smaller adaptive sub-systems of autonomous money networks and rules for their engagement, each artificial agent having the capacity to form, judge, collaborate and act on their financial world-model. Interesting question is whether we will see a socially differing allocation of value then?

Complexity

While this is an active research area, there have been some recent developments in general causality based discovery models which lower the dependency on time-sequenced data as has been traditionally needed to assess markets, letting us analyze the so far hidden causality structures in economic behavior at the societal level.

Now every once in a while all dreamers have to wake up, but let us still explore this idea just a little further without getting into the nay-saying practicalities of the present-day infrastructure and governments. That being said, gradual and incremental diffusion of cognitive abilities in financial infrastructure will ultimately lead the way. 

Human-to-Machine-to-Machine-to-Human 

With an exploding ‘Internet of Things’ we now even see quantum-resistant cryptocurrencies such as IOTA, into which device maker Bosch' investment semed a good sign for things to come. It is not very hard to imagine that for a varying scale of amount, a user may want a machine to make transactions for him, or even to make the final buying or selling decisions for him. AI after all is a machine to delegate decision making to. Overtime all our personal devices also may learn to emulate and reflect our individual behavior.

So what does this imply? Having an AI agent that interacts with other AI agents and the economic environment on behalf of humans would lead to not only a more socially optimal allocation of assets (and value) but also a more advertising-resilient and intelligent market ecosystem, total market participation being a sum of human and machine activity. The big benefit though lies in the emergence of an economic swarm intelligence at the macro level.

Must overthrow the middle-man.

If we have Intelligent Agents representing buyers and sellers (and intermediaries?), we can make a market out of their supply demand conditions. Most people leave detailed traces of their online activity, so it can be argued that the Agent representing them will have some individual characteristics as well. Let us say that this agent follows a policy iteration algorithm, it has to maximize the utility function of money and the satisfaction of its master. Between its master’s satisfaction and his money’s utility, the agent will make a trade-off somewhere. The issue with utility is that in most markets, it is the intermediaries who control the information and direct the price. It is therefore again the intermediary who has the best estimate of the buyers’ and sellers’ economic potential as well, add to it various search and recommendation systems – and one can see how much markets are driven by the middle-man. The Agent’s information aggregation therefore should go beyond the information provided by the intermediary.

Humans alone are irrational economic agents, mostly making purchases with crafted and limited information. Cognification of economic activity stands to remodel the structural balance of markets, which are already to some degree intelligent, but lack the ability to signal and form internal models. In a complex world, money networks should have the ability to simulate the economy or a part of the economic environment, before proceeding with actions which could have ripple effects on other loosely connected networks. This means digital and intelligent money systems would need more space in the cloud, and evidently have a whole new set of security & architecture issues. 

Integrating The Dark Side

Untraceable & Private

Most of the economics ignores a large portion of economic activity, crime-war-politics. Also the suppression of people’s economic interests anywhere provides impetus to the creation of a black market. A lot of this money is funneled back into the governments as well. It is in the best interest of people involved with this side that their economic activity and the flow of resources is kept as opaque as possible. While currencies like Monero could be useful here, one can argue that cash is still the king and a hurdle in shifting to intelligent money systems.

Nevertheless the networks which have implicit value do thrive on anonymity.

Here I must mention Everett Rogers who gave us the criteria that a new technology must satisfy for incremental adoption:

- Complexity [Can the user understand the use and troubleshoot?]
- Observability [Is the use observed in other people, media?]
- Trialability [Is the tech available for simple non-exhaustive trials?]
- Compatibility [Does it work with the existing social and technical systems?]

The greatest hurdle crypto-currencies have to face is the Compatibility test. But digital national currencies could certainly take a lead in moving towards an intelligent agent based economic approach, if they’re going cashless that is.

It is clear that in such economies, humans will have to share some of their autonomy with the intelligent systems. What are the fundamental limits of this sharing is rather a sociological and game-theoretic question, the answering of which needs to take into account the matter of self-interest vs. public-interest – that is if we are to design such economic governance systems whose purpose is neither to serve, nor to rule. 

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