Sunday, January 7, 2018

Educational Supply Chains: A Decentralized Role for AI

First, consider the potential for learning processes as self supporting supply chains, which in turn allow educational investments to directly disperse wealth and knowledge. Why education as a supply chain for growth? Since today's institutions mostly "random mine" skills and knowledge, the benefits of human capital are somewhat lacking in growth statistics. In "The Importance of Education and Skill Development for Economic Growth in the Information Era", Charles Hulten argues that the BLS assigns a "relatively small role to education", which he (understandably) believes is insufficient. How might we create a better organizational platform for human capital, in which education becomes a stronger component of economic dynamism?

Presently, as institutions randomly mine the investments of human capital, many aspects of knowledge use have to "wait in line" for tradable sector wealth origin - even to the extent that advanced economy workers "wait" for resource origin flows from emerging economies. Granted, these original wealth sources are supplemented via the monetary flows of physical assets (housing) and a wide array of debt backed instruments. Nevertheless, too much non tradable sector activity remains on the negative side of the ledger, in terms of a general equilibrium growth base. Possibly the non tradable sector activity of new housing (not its loan activity), is the major non tradable sector contributor, to the positive side of the wealth creation ledger.

Meanwhile, too much educational investment in general, has come up short in terms of providing directly to economic dynamism. Another way to think about this: When labour and human capital serve primarily as residuals (for both primary and secondary market activity), the potential for a knowledge continuum is broken or at least disrupted, at numerous junctures. Is it possible to provide stronger connection points - even a recognizable supply side chain - for knowledge use in general?

One way to approach this problem, is via the use of coordinated time arbitrage in knowledge use systems. Time arbitrage as a single price commodity unit, would allow individuals and groups to immediately cancel time debt, as it occurs in daily activity. Individuals would also be able to "buy" time insurance from others in the event they can't work, via voluntary service hours. This approach would allow purposeful matched time (and its accompanying knowledge use) to function as an ongoing continuum. Personal time value, along with skill and knowledge, would function as a supply chain model, making human capital a central component of growth and wealth creation.

Among the reasons people fear artificial intelligence, is the fact that human capital - despite its importance -  is still organizationally structured as a production residual. Whenever individuals need to specify their time as containing higher monetarily value than that of others, their time use becomes dependent on general equilibrium system flows. In other words, the costs of skills differentiation will frequently remove any first mover position for knowledge use we might hold, since one must enter their knowledge and skill into organizational processes which are also aligned to "wait" for the total compensation of the system.

So long as an excessive amount of labour remains in either secondary markets or residual production positioning, even professional groups end up in defensive positions, arguing for humans to remain "embedded in the loop". Calls for continued management via human judgement, have a more emotional element than the technical maintenance which AI will (more naturally) require, in the form of human assistance. In all of this: Since human capital is still organized as peripheral or "as needed", high and low skill levels are becoming default positions - even though average skill is more representative of human populations in general. Consequently, average intelligence would likely be an important characteristic, for the time based and educational supply chains of the future.

It is the central role of our time in knowledge based supply chains, that makes it possible for deep learning AI to assist us - meaning not inevitably the other way around. How so? For instance: One of the primary advantages of time based services in desirable regions, has been their ability to replicate specific and desirable skill sets - think brain surgery as an example. The deep learning of AI makes it possible to disperse specific skill replication functions as well, so that many skills sets can eventually be applied in environments which otherwise may lack "cutting edge" human skills capacity.

Decentralized services generation would mean an altogether different approach for deep learning AI is possible: One that includes helping locals assist one another with important service functions, especially during their primary educational years. It's the wealth generating capacity of equal time coordination, which allows these groups to make their dependency break with general equilibrium monetary flows for time use. By decentralizing service capacity, each group can build a continuum for progress which holds a reasonable chance of permanence, insofar as time use functions are recorded and preserved.

In knowledge use systems, humans would often seek the assistance of deep learning AI. However, this approach accentuates personal autonomy, and is quite different from that of human assistance for technology as part of a centralized system. Time arbitrage can allow for greater dispersal of knowledge use. It's the use of knowledge - not just its acquisition as investment - which drives economic dynamism and moves society forward.

When human capital functions primarily as a production residual, there's good reason to be concerned about educational investment roles, once general equilibrium capacity becomes constrained. Yet it is precisely the ability to build time based local wealth, which could allow human capital to fully function as a central part of knowledge based processes. When purposeful time serves as an economic core, deep learning AI - important though it is - would often provide a supportive role for the experiential product that people wish to share on more personal terms.

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