A recent set of events have gotten me to thinking a bit more deeply about what role automated inferring systems should play in organizations. From the perspective of some it would seem that AOW based businesses will be responsible for the elimination of many tasks which currently are performed by several layers of humans in the organization who's task it is to run analysis on metrics gathered from their managed teams to determine how to redirect the execution of failing projects or direct the execution of planned new ones. This view is true in so far as such tasks are far more efficiently performed from the business perspective by an automated learning process. Such processes are able to behave in ways that human agents are not, such as:
- Automated learning of efficient processes involves a perfect memory of past performance executing the minutia of actions against objects of a given type in the examined process. Perfect memory is equivalent to perfect access to acquired data which makes performing new decisions temporally efficient as data gathering need not be done.
- Automated learning eliminates the need for the gathering of consensus across multiple agents tasked with performing analysis. Since an AOW based learning agent performs a system wide convergence across all managed object types the optimal future delegation events are present in memory for any new required delegations. The time consuming process that exists in enterprises today of mid level and more senior managers coming together to discuss the results of their analysis to help shape future decisions is not necessary.
- Automated learning agents by eliminating the bias of selection that attends human based management and delegation processes are free to be purely meritocratic in their selection of delegated agents in the emancipated worker pool, eliminating that bias completely from attempts to execute any business required task removing another potential inefficiency that is an issue in human managed systems.
Beyond these points, it is also true that most people who have been "promoted" to positions where they are managing others and analyzing performance completing tasks rather than doing the tasks would also like to be free to maximize their value scape. As described in the maximize your value post, the personal desire for us to perform across the set of skills that we can competently perform and be compensated for and in our own time frame is what we really as humans want to do. It is no wonder that across businesses the management layers are the ones with the highest levels of burn out and attrition as the continuous demands of needing to manage down level working agents and as well manage the interaction with same level and up level management agents leaves such individuals in a state of continuous bombardment that makes consistent performance difficult. The artificially intelligent work routing performed by systems that employ AOW would take the burden of this task over and because it does not have the limitations of burn out induction or limited memory of past data metrics it can consistently make the right choice for the actions delegated at the moment and thus over time achieves hyper efficiency.
Individuals in organizations that are displaced are then able to redeploy their value space such that they can deploy multiple areas of their skills as an emancipated worker for businesses instead of as an easily worn out routing node. More people are then enabled to maximize their value and derive personal happiness in their lives as a result.